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+The evaluation of the child should include inquiries about the child’s behavior in different settings and with different caregivers to note any differences. Formal observations of the child and parent interactions are also important. Procedures derived from developmental research, such as the Strange Situation Procedure (Ainsworth et al. 1978) or the Crowell procedure (Zeanah et al. 2000), are relatively short observations of child and parent interaction which help the clinician systematically to observe the interaction between the child and caregiver (Zeanah et al. 2011). During the assessment, there are several other diagnoses to consider since attachment disorders may share features of some other disorders (see Table 1 for details). For example, emotionally withdrawn/inhibited RAD may be confused with autistic spectrum disorders or global developmental delay. The problems with emotional regulation and impaired social reciprocity may resemble the social difficulties of a child with an autistic spectrum disorder. On the other hand, there is little reason to expect restricted interests or repetitive behaviors in children with attachment disorders. A history of adverse caregiving as well as no selective impairment in language or pretend play should point toward a diagnosis of RAD in such children. Although children with RAD are likely to have cognitive delays, their impaired social responsiveness is not a symptom of intellectual disabilities alone. Children with intellectual disabilities should have social behavior and emotional expressiveness congruent with their cognitive ages. On the other hand, selective reductions in social reciprocity and emotional expressiveness are more indicative of emotionally withdrawn/inhibited RAD.
+An important diagnosis to consider with indiscriminately social/disinhibited RAD is attention deficit hyperactivity disorder (ADHD). In RAD, young children have social impulsivity, but this should not be confused with the broader impulsivity and hyperactivity of children with ADHD. It is important to look in detail at how the child interacts in social situations and especially with unfamiliar adults. Children with RAD lack selectivity in directing their social and sometimes attachment behaviors. Children with ADHD may share these features but also demonstrate impulsivity in nonsocial situations. Children with indiscriminately social/disinhibited RAD should show more profound misreading of social cues and situations and engage in more social and physical boundary violations.
+
+**Table 1 Differential diagnosis of attachment disorders**
+
+| Attachment disorder | Differential diagnosis | Similarities | Differences |
+|:--------------------|:-----------------------|:-------------|:------------|
+| Emotionally withdrawn/inhibited type | 1. Autistic spectrum disorder | 1. Disturbances in emotional regulation | 1. Attachment disorder does not have selective impairment in pretend play, repetitive preoccupation, or a language abnormality |
+| | | 2. Impaired or absent social and emotional reciprocity | 2. Attachment disorder has a history of seriously adverse caregiving |
+| | | 3. May involve cognitive delays | |
+| Emotionally withdrawn/inhibited type | 1. Intellectual disability | 1. Cognitive delays | 1. Attachment disorder does not have social/emotional behaviors consistent with developmental age |
+| | | | 2. Attachment disorder has evidence of deviance in social responsiveness and regulations of emotion |
+| Indiscriminately social/disinhibited type | 1. Attention deficit hyperactivity disorder | Social impulsivity and attention seeking behavior | 1. Attachment disorder in males shows a lack of selectivity in relationships with caregivers and peers |
+
+### Treatment
+
+There is only one intentional treatment study of attachment disorders that includes pre- and post-assessments and uses random assignment (Smyke et al. in preparation). The BEIP demonstrated substantial treatment effects on reduction of signs of emotionally withdrawn/inhibited RAD and more modest treatment effects of reduction in signs of indiscriminately social/disinhibited RAD for children placed in foster care compared to those who experienced continued institutional care (Smyke et al.). This study bolsters confidence in other less rigorously designed studies that all suggest that signs of emotionally withdrawn/inhibited RAD disappear rapidly when children are placed in reasonably normative caregiving environments. Similarly, the results in BEIP are compatible with studies of internationally adopted children suggesting that signs of indiscriminately social/disinhibited RAD are less responsive to more normative caregiving environments, and that a minority of children have persistent signs of the disorder over years (Smyke et al.). Future research needs to better determine recommendations for adoptive parents whose young children exhibit signs of RAD and how best to deal not only with the behavioral manifestation but also with the social cognitive abnormalities that presumably underlie the disorder. Further, although there is a clear tendency for signs of both types of disorders to diminish over time, questions about sequelae have not been adequately answered at this point.
+
+### See Also
+
+*   Feral Children
+*   Posttraumatic Stress Disorder
+*   Reactive Attachment Disorder
+*   Romanian Adoptive Children
+
+### References and Reading
+
+Ainsworth, M. S., Blehar, M. C., Waters, E., & Wall, S. (1978). Patterns of attachment: A psychological study of the strange situation. Hillsdale: Lawrence Erlbaum Associates.
+American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: American Psychiatric Association. Text Revision.
+Bowlby, J. (1969). Attachment and loss (Vol. 1). New York: Basic Books.
+Chaffin, M., Hanson, R., Saunders, B., et al. (2006). Report of the APSAC task force on attachment therapy, reactive attachment disorder, and attachment problems. Child Maltreatment, 11(1), 76–89.
+Chisholm, D. (1998). A three-year follow-up of attachment and indiscriminate friendliness in children adopted from Romanian orphanages. Child Development, 69, 1092–1106.
+Egger, H., Erkanli, A., Keeler, G., Potts, E., Walter, B., & Angold, A. (2006). Test-retest reliability of the preschool age psychiatric assessment (PAPA). Journal of the American Academy of Child and Adolescent Psychiatry, 45, 538–549.
+Gleason, M. M., Fox, N. A., Drury, S., Smyke, A. T., Egger, H. L., Nelson, C. A., et al. (2011). The validity of evidence-derived criteria for reactive attachment disorder: Indiscriminately social/disinhibited and emotionally withdrawn/inhibited types. Journal of the American Academy of Child and Adolescent Psychiatry, 50, 216–231.
+Hodges, J., & Tizard, B. (1989). Social and family relationships of ex-institutional adolescents. Journal of Child Psychology and Psychiatry, 30, 77–97.
+Oosterman, M., & Schuengel, C. (2007). Autonomic reactivity of children to separation and reunion with foster parents. Journal of the American Academy of Child and Adolescent Psychiatry, 46, 1196–1203.
+Pears, K. C., Bruce, J., Fisher, P. A., & Kim, H. K. (2010). Indiscriminate friendliness in maltreated foster children. Child Maltreatment, 15, 64–75.
+Rutter, M., Colvert, E., Kreppner, J., Beckett, C., Castle, J., Groothues, C., et al. (2007). Early adolescent outcomes for institutionally-deprived and non-deprived adoptees. I: disinhibited attachment. Journal of Child Psychology and Psychiatry, 48, 17–30.
+Rutter, M., Kreppner, J., & Sonuga-Barke, E. (2009). Emanuel Miller lecture: attachment insecurity, disinhibited attachment, and attachment disorders: where do research findings leave the concepts? Journal of Child Psychology and Psychiatry, 50, 529–543.
+Skovgaard, A. M., Houmann, T., Christiansen, E., Landorph, S., Jørgensen, T., Olsen, E. M., et al. (2007). The prevalence of mental health problems in children 1½ years of age–the Copenhagen Child Cohort 2000. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 48(1), 62–70.
+Smyke, A. T., Zeanah, C. H., Gleason, M. M., Drury, S. S., Fox, N. A., Nelson, C. A., et al. (2012). A randomized controlled trial of foster care vs. institutional care for children with signs of reactive attachment disorder. American Journal of Psychiatry, 169, 508–514.
+Tizard, B., & Rees, J. (1975). The effect of early institutional rearing on the behaviour problems and affectional relationships of four-year-old children. Journal of Child Psychology and Psychiatry, 16, 61–73.
+World Health Organization. (1992). ICD-10: International classification of diseases and related health problems. Geneva: World Health Organization.
+Zeanah, C. H., Berlin, L. J., & Boris, N. W. (2011). Practitioner review: Clinical applications of attachment theory and research for infants and young children. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 52(8), 819–833.
+Zeanah, C., & Gleason, M. M. (2010). Reactive attachment disorders: A review for DSM 5. Retrieved December 29, 2010, from http://stage.dsm5org/Proposed% 20Revision%20Attachments/APA%20DSM-5% 20Reactive%20Attachment%20Disorder%20Review. pdf.
+Zeanah, C., Larrieu, J., Valliere, J., & Heller, S. (2000). Infant-parent relationship assessment. In C. H. Zeanah (Ed.), Handbook of infant mental health (2nd ed., pp. 222–235). New York: Guilford Press.
+Zeanah, C. H., Scheeringa, M. S., Boris, N. W., Heller, S. S., Smyke, A. T., & Trapani, J. (2004). Reactive attachment disorder in maltreated toddlers. Child Abuse and Neglect: The International Journal, 28, 877–888.
+Zeanah, C., & Smyke, A. (2008). Attachment disorders in relation to deprivation. In M. Rutter & E. Taylor (Eds.), Rutter’s child and adolescent psychiatry (5th ed., pp. 906–915). Malden/Oxford: Blackwell Publishing.
+Zeanah, C. H., Smyke, A. T., Koga, S., Carlson, E., & The BEIP Core Group. (2005). Attachment in institutionalized and community children in Romania. Child Development, 76, 1015–1028.
+
+## Attention
+
+### Definition
+
+The ability to orient, sustain, and shift attention on relevant stimuli, using internal and external cues, is a critical skill for learning about the world. Prioritizing stimuli in order to process pertinent, and exclude peripheral, information facilitates selective learning, a skill necessary for many child development processes, including vocabulary development, problem solving, and later, successful classroom learning (Frick and Richards 2001; Kannass and Colombo 2007; Sillar and Sigman 2008). Children with autism often display atypical development of attention. The processes in which these abnormalities manifest, however, are yet to be determined (Ames and Fletcher-Watson 2010). Despite the high prevalence of attentional difficulties seen in children with autism, these difficulties are not considered a core characteristic of the disorder as specified by the fourth version of the Diagnostic and Statistical Handbook of Mental Disorders (DSM IV 1994), but rather an associated symptom of ASD.
+
+Behavior is acted upon using visual information from the environment. For example, safe driving is largely dependent on drivers attending to stoplights, signs, pedestrians, and other cars and ignoring distracting, irrelevant environmental stimuli. The breadth of attention literature identifies several components of domain-specific and domain-general attending. Visual attention, in particular, plays a large role in domain-specific attention, such as social attention. Social attention is the preferential selection of social over nonsocial stimuli for attention and has been the subject of much research due to its high correlation with later social developmental processes, such as joint attention, theory of mind, and language development (Adamson et al. 2009; Ames and Fletcher-Watson 2010; Mundy and Newell 2007; Sodian and Thoermer 2008). Moreover, social attention is of particular interest to the study of autism due to its relation to social interactions and communication, two core deficits of the disorder.
+
+Attention may be subdivided into the ability to focus, sustain, shift, and encode (Goldstein et al. 2001; Zubin 1975). Focused attention is the ability to concentrate and perform a task on a specific stimulus in the midst of distracting stimuli. Sustained attention is defined as the capacity to maintain attention on a target stimulus over a prolonged period of time. Shifting attention is the ability to effectively transfer concentration from one stimulus to another. Encoding attention is the ability to intake and interpret information from the environment (Goldstein et al. 2001). Research on these specific skills may be used to identify which aspects of attention children with autism seem to struggle with most and, conversely, which areas of attention develop typically.
+A comprehensive understanding of attention must include a description of environmental stimuli that help an individual to attend. Attention cueing, that is, attention directed by environmental prompts, affects what stimuli humans attend to; these environmental prompts are identified as exogenous and endogenous factors. Exogenous cues, those that activate “bottom-up” processes, are derived from stimuli properties (e.g., size, color) and evoke involuntary attention (Corbetta and Shulman 2002). Endogenous cues, on the other hand, often characterized as activating “top-down” processes, evoke conscious and voluntary attention control through cognitive processes, learned behavior, or past experiences (Corbetta and Shulman 2002; Hauer and MacLeod 2006). In this way, previous experiences and learned behaviors influence on what or where the child attends.
+The multitude of cognitive, social, and language developmental skills learned during play make free play an important setting in which to study attention in children. Ruff and Capozzoli (2003) studied the developmental trajectory of visual attention during play and identified three types of attention. Causal attention is defined at looking at objects (e.g., toys), but not physically engaging with them; settled attention is looking at and manipulating an object; and focused attention is concentrating on an object intently and may include facial expressions and extraneous body movement in order to bring the object closer to the face or body. Collectively, the study of attention covers a wide array of specific topics, all of which hold importance for a comprehensive understanding of the topic and for the development of interventions aimed at healthy development.
+
+### Historical Background
+
+Attention has been a topic of study for decades by researchers and clinicians alike. Because of the high occurrence of attention deficits in autism, this topic has been the focus of numerous studies in autism research, in particular. The discourse of processes and causes of this apparent attention deficit has evolved over time. Early researchers hypothesized that attention difficulties in children with autism were due to hypo- or hyperarousal. That is, some researchers concluded that arousal modulation in particular, was a potential cause of low attention abilities (Hutt et al. 1964; Ornitz and Ritvo 1968). Other investigators attributed limited attention skills to over-selectivity or what some referred to as “tunnel vision,” that is, intense attention to specific details in combination with a lack of interpretation of outside environmental cues (Lovaas et al. 1979; Rincover and Ducharme 1987). More recently, it has been hypothesized that attention problems may be due to difficulties in prioritizing relevant stimuli and disregarding irrelevant stimuli (Bryson et al. 1990; Burack 1994). Furthermore, Ornitz and colleagues (1988) proposed that children with autism struggle in attention shifting, in particular, because they lack an interest in people or social stimuli (Ornitz 1988). Previous studies have also dichotomized attention in studying auditory and visual attention and found that children with autism differed from typical children in auditory attention (Casey et al. 1993) but not in visual attention (Pascualvaca et al. 1998). This finding, however, is inconsistent with more recent findings concerning visual attention in the literature (Goldstein et al. 2001; Leekam et al. 2000) and may be due to differences in measurement (Ames and Fletcher-Watson 2010). With technological advances in detection tools, so came a new wave of studies addressing biological hypotheses for attention deficits. Throughout the past two decades, researchers hypothesized that inattentive behavior may be due to neural abnormalities in areas such as the parietal lobe and the frontal lobe (Courchesne et al. 1993, 1994; Ornitz 1988; Pascualvaca et al. 1998).
+
+### Current Knowledge
+
+Developmental studies on attention reveal that attention evolves over the course of childhood and different patterns of attention behaviors are observed over time. The duration of time infants spend looking at objects or people, which reflects differences in underlying attention processes (Kannass and Oakes 2008), increases from birth through 8 to 10 weeks, then decreases between 3 and 5 or 6 months, and remains stable or slightly increases thereafter (Colombo 2001, 2002). The initial increase of look duration may be due to steady increases in arousal and alertness, whereas the decrease of look duration may be indicative of improvements in information processing. The plateau reached near the first year is likely indicative of endogenous factors or top-down processes manifesting (Corbetta and Shulman 2002; Colombo 2001, 2002).
+Children with autism appear to show different patterns of attention development than their typical peers. For example, the top-down processing that develops around the first year appears to pose difficulty for children with autism as compared to typically developing children (Ames and Fletcher-Watson 2010; Ames and Jarrold 2007; Leekam et al. 2000). Goldstein et al. (2001) also found that individuals with autism were different from their typical counterparts in their abilities to focus and shift attention, but were not different in their abilities to sustain and encode attention (Goldstein et al.). Another study found that children with autism had more circumscribed, preservative, and detail-oriented attention (Sasson 2008). The results of studies involving eye tracking and visual attention in the context of social stimuli have also found differences among individuals with autism. One study indicated that when shown images of objects and people, individuals with autism generally attended to the nonsocial aspects of the picture, that is, objects rather than faces. Further, the investigation found that when individuals with autism did attend to social images, such as a human face, they looked at noncritical social elements, such as the nose rather than the eyes (Klin et al. 2002). Another study found that children with autism have difficulties processing both social and nonsocial information (Leekam et al. 2000). Collectively, the literature suggests that individuals with autism lack attention to social stimuli which undoubtedly affects social and emotional learning.
+
+### Future Directions
+
+Attention abilities, from infancy throughout childhood, can have several effects on social relationships, language development, and cognitive development. Future work on attention in autism should aim to examine these processes in natural settings to more appropriately capture variables that facilitate and inhibit successful attention for this population within a variety of contexts, such as their social relationships and academic settings. Moreover, there is a need for greater longitudinal work in this area in order to understand how attentional processes develop over time and the extent to which these processes impact social and cognitive outcomes for individuals with ASDs (Ames and Fletcher-Watson 2010). Finally, attention has the potential to be an invaluable early detection tool for autism diagnoses. Children with autism face early and pervasive abnormalities in attention abilities (Allen and Courchesne 2001; Elsabbagh et al. 2009). The developmental course of attention in typical development has been outlined by previous investigations; future research could use such knowledge to examine attention in children at risk for autism early in infancy. Earlier screening and detection to earlier intervention which has been shown to yield improved outcomes for children with autism and other developmental delays.
+
+### See Also
+
+*   Joint Attention
+*   RJA/IJA (Initiating/Responding to Joint Attention)
+
+### References and Reading
+
+Adamson, L., Bakeman, R., Deckner, D., & Romski, M. (2009). Joint engagement and the emergence of language in children with autism and down syndrome. Journal of Autism and Developmental Disorders, 39, 84–96.
+Allen, G., & Courchesne, E. (2001). Attention function and dysfunction in autism. Frontiers of Bioscience, 6, 105–119.
+American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author.
+Ames, C., & Fletcher-Watson, S. (2010). A review of methods in the study of attention in autism. Developmental Review, 30, 52–73. https://doi.org/10.1016/j.dr.2009.12.003.
+Ames, C. S., & Jarrold, C. (2007). The problem with using eye-gaze to infer desire: A deficit of cue inference in children with autism spectrum disorder? Journal of Autism and Developmental Disorders, 37, 1761–1775.
+Bartgis, J., Thomas, D., Lefler, E., & Hartung, C. (2008). The development of attention and response inhibition in early childhood. Infant and Child Development, 17, 491–502. https://doi.org/10.1002/icd.563.
+Bryson, S. E., Wainwright-Sharp, J. A., & Smith, I. M. (1990). Autism: A developmental spatial neglect syndrome? In J. T. Enns (Ed.), The development of attention: Research and theory (pp. 405–427). Amsterdam: Elsevier North Holland.
+Burack, J. A. (1994). Selective attention deficits in persons with autism: Preliminary evidence of an inefficient attentional lens. Journal of Abnormal Psychology, 103, 535–543.
+Casey, B. J., Gordon, C. T., Mannheim, G. B., & Rumsey, J. M. (1993). Dysfunctional attention in autistic savants. Journal of Clinical and Experimental Neuropsychology, 15, 933–946.
+Colombo, J. (2001). The development of visual attention in infancy. Annual Review of Psychology, 52, 337–367.
+Colombo, J. (2002). Infant attention grows up: The emergence of a developmental cognitive neuroscience perspective. Current Directions in Psychological Science, 11, 196–200.
+Corbetta, M., & Shulman, G. (2002). Control of goal-directed and stimulus driven attention in the brain. Neuroscience, 3, 201–215. https://doi.org/10.1038/nrn755.
+Courchesne, E., Townsend, J., Akshoomoff, N. A., Saitoh, O., Yeung-Courchesne, R., Lincoln, A. J., et al. (1994). Impairment in shifting attention inautistic and cerebellar patients. Behavioral Neuroscience, 108, 848–865.
+Courchesne, E., Townsend, J. P., Akshoomoff, N. A., Yeung-Courchesne, R., Press, G. A., Murakmi, J. W., et al. (1993). A new finding: Impairment in shifting of attention in autistic and cerebellar patients. In S. H. Broman & J. Grafman (Eds.), Atypical deficits in developmental disorders: Implications for brain function (pp. 101–137). Hillsdale: Erlbaum.
+Elsabbagh, M., Volein, A., Holmboe, K., Tucker, L., Csibra, G., Baron-Cohen, S., et al. (2009). Visual orienting in the early broader autism phenotype: Disengagement and facilitation. Journal of Child Psychology and Psychiatry, 50, 637–642.
+Frick, J., & Richards, J. (2001). Individual differences in infants’ recognition of briefly presented visual stimuli. Infancy, 2, 331–352.
+Goldstein, G., Johnson, C., & Minshew, N. (2001). Attentional processes in autism. Journal of Autism and Developmental Disorders, 31, 433–440.
+Hauer, B., & MacLeod, C. (2006). Endogenous versus exogenous attentional cueing effects on memory. Acta Psychologica, 122, 305–320. https://doi.org/10.1016/j.actpsy.2005.12.008.
+Hutt, C., Hutt, S. J., Lee, D., & Ounsted, C. (1964). Arousal and childhood autism. Nature, 204, 908–909.
+Kannass, K., & Colombo, J. (2007). The effects of continuous and intermittent distractors on cognitive performance and attention in preschoolers. Journal of Cognition and Development, 8, 63–77.
+Kannass, K., Colombo, J., & Wyss, N. (2010). Now, pay attention! The effects of instruction on children’s attention. Journal of Cognition and Development, 11, 509–532. https://doi.org/10.1080/15248372.2010.516418.
+Kannass, K., & Oakes, L. (2008). The development of attention and its relations to language in infancy and toddlerhood. Journal of Cognition and Development, 9, 222–246. https://doi.org/10.1080/152483708020 22696.
+Klin, A., Jones, W., Schultz, R., Volkmar, F., & Cohen, D. (2002). Visual fixation patterns during viewing of naturalistic social situations as predictors of social competence in individuals with autism. Archives of General Psychiatry, 59, 809–815.
+Leekam, S. R., Lopez, B., & Moore, C. (2000). Attention and joint attention in preschool children with autism. Developmental Psychology, 36, 261–273.
+Lovaas, I., Koegel, R., & Schreibman, L. (1979). Stimulus overselectivity in autism: A review of research. Psychological Bulletin, 86, 1236–1254.
+Mundy, P., & Newell, L. C. (2007). Attention, joint attention and social cognition. Current Directions in Psychological Science, 16, 269–274.
+Ornitz, E. M. (1988). Autism: A disorder of directed attention. Brain Dysfunction, 1, 309–322.
+Ornitz, E. M., & Ritvo, E. R. (1968). Perceptual inconsistency in early infantile autism. Archives of General Psychiatry, 18, 76–98.
+Pascualvaca, D., Fantie, B., Papageorgiou, M., & Mirsky, A. (1998). Attentional capacities in children with autism: Is there a general deficit in shifting focus? Journal of Autism and Developmental Disorders, 28, 467–478.
+Rincover, A., & Ducharme, J. M. (1987). Variables influencing stimulus over-selectivity and “tunnel-vision” in developmentally disabled children. American Journal of Mental Deficiency, 91, 422–430.
+Ruff, H., & Capozzoli, M. (2003). Development of attention and distractibility in the first 4 years of life. Developmental Psychology, 39, 877–890.
+Sasson, N. (2008). Children with autism demonstrate circumscribed attention during passive viewing of complex social and nonsocial picture arrays. Autism Research, 1, 31–42.
+Sillar, M., & Sigman, M. (2008). Modeling longitudinal change in the language abilities of children with autism: Parent behaviors and child characteristics as predictors of change. Developmental Psychology, 44, 1691–1704.
+Sodian, B., & Thoermer, C. (2008). Precursors to a theory of mind in infancy: Perspectives for research on autism. Quarterly Journal of Experimental Psychology, 61, 27–39. https://doi.org/10.1080/1747021070 1508681.
+Zubin, J. (1975). Problem of attention in schizophrenia. In M. L. Kietzman, S. Sutton, & J. Zubin (Eds.), Experimental approaches to psychopathology (pp. 139–166). New York: Academic Press.
+
+## Attention Deficit/Hyperactivity Disorder
+
+### Synonyms
+
+ADD; ADHD; Attention deficit disorder; Hyperkinetic disorders; Minimal brain damage; Minimal brain dysfunction; Syndrome of deficits in attention, motor control, and perception (DAMP)
+
+### Short Description or Definition
+
+Attention deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in children and adolescents. It is characterized by inattention, impulsivity, and hyperactivity. Its rate decreases with the increase of age. ADHD usually starts in childhood and continues through adolescence into adulthood. The burden and psychosocial functioning impairment of ADHD is farther than its inattention, impulsivity, and hyperactivity symptoms. There are many controversies and scientific debates about ADHD (Biederman and Faraone 2005; Furman 2008).
+
+### Categorization
+
+According to DSM-IV, there are three subtypes of ADHD called “predominantly inattentive,” “predominantly hyperactive-impulsive,” and “combined.” ICD-10 lacks this categorization.
+
+### Epidemiology
+
+The prevalence of ADHD in children is estimated to be about 8–12% (Biederman and Faraone 2005). The rate of ADHD in boys is three times more than girls, and this ratio in the clinical sample is six to nine times (Ghanizadeh et al. 2008).
+
+### Natural History, Prognostic Factors, and Outcomes
+
+From about two centuries ago, children with symptoms of inattention, impulsivity, and hyperactivity have been described (Crichton 2008; Lange et al. 2010). Heinrich Hoffmann described some symptoms of ADHD in the story of Fidgety Phil (Hoffmann (1948) cited by Lange et al. (2010)). Moral control defect was introduced by Sir George Frederic Still ((Still 1902) cited in Lange et al. (2010)). He reports that these children cannot internalize rules and limits. Then, the term of “postencephalitic behavior disorder” was introduced after the worldwide influenza epidemic (Rothenberger and Neumärker 2005) cited in Lange et al. (2010). The terms of “minimal brain damage” and “minimal brain dysfunction” were described (Hoffmann 1948). The name was changed to “hyperkinetic reaction of childhood” in the second edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-II) (American Psychiatric Association (APA) (1967). Diagnostic and statistical manual for mental disorders). Overactivity, restlessness, distractibility, and short attention span were the characteristics of this disorder (APA (1967). Diagnostic and statistical manual for mental disorders). In the third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III), the disorder was called “attention deficit disorder (ADD): with and without hyperactivity.” In this edition, the focus was on inattentiveness rather than hyperactivity (APA (1980). Diagnostic and statistical manual (DSM-III)). In addition, it was stressed that hyperactivity was no more a necessary criterion for diagnosis of this disorder. From 1987, revision of the third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R), this disorder was renamed “attention deficit/hyperactivity disorder” (ADHD) (APA (1987). Diagnostic and statistical manual (DSM-III, revised)). In the DSM-III-R, the subtype of “ADD without hyperactivity” was replaced with the category of “undifferentiated ADD” (Lange et al. 2010). From the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (APA (1994). Diagnostic and statistical manual (DSM-IV)), the three subtypes of ADHD including “predominantly inattentive type,” “predominantly hyperactive-impulsive type,” and “combined type with symptoms of both dimensions” were presented (Lahey et al. 1994). There was no change regarding ADHD in the text revision of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) (APA (2000). Diagnostic and statistical manual (DSM-IV, Text Rev.)). It is expected that DSM-V will be published in 2012.
+Multiple comorbid disorders and parent-reported ADHD severity are associated with the poorer psychosocial quality of life (Klassen et al. 2004). The type of comorbidity is also associated with the quality of life. Lower quality of life is associated with the comorbidity of oppositional defiant disorder, conduct disorder, and learning disorder (Klassen et al. 2004). There is a positive short-term effect of medication on quality of life in children, adolescents, and adults with ADHD (Coghill 2010). Comorbidity of ODD with ADHD is associated with more severe ADHD symptoms, peer problems, and family problems (Ghanizadeh and Jafari 2010). Children and adolescents with ADHD have poorer social and communication skills leading to more peer relationship problems. More than two-thirds of them have no close friends (Wehmeier et al. 2010). So, they are more frequently rejected by others. This makes them more prone to join to deviant peer groups, injuries, occupational problems, educational problems, cigarettes, and substance use disorders (Biederman and Faraone 2005). The symptoms of ADHD continue from childhood into adult. However, most of them will not meet the full diagnostic criteria in adult but they will meet the diagnosis of ADHD in partial remission (Fischer et al. 2002).
+
+### Clinical Expression and Pathophysiology
+
+While there are many controversies about ADHD, the improvement of some symptoms after pharmacotherapy supports that there are neurobiological causes for the heterogeneous nature of ADHD. There is a large gap in our knowledge and current literature regarding ADHD. However, it is clear that there is not any one specific brain area or genetic or neurochemical factor as the etiology of ADHD. The etiology of ADHD is complex (Steinhausen 2009). The heritability of ADHD is reported in twin and adoption studies. However, more molecular genetic studies are necessary to indicate the complex genetics and the interaction of gene by environment in ADHD (Biederman and Faraone 2005; Nigg et al. 2010).
+There is not enough evidence supporting that ADHD is caused by foods or food additives (Biederman and Faraone 2005), while lead is reported to be associated with ADHD (Ghanizadeh 2011). Exposure to toxins such as mercury, lead, manganese, and polychlorinated biphenyls (PCBs) and pregnancy and delivery complications (such as eclampsia, maternal age, prenatal alcohol exposure, maternal smoking, fetal postmaturity, duration of labor, fetal distress, low birth weight, and hemorrhage) are other risk factors associated with ADHD (Banerjee et al. 2007). Meanwhile, TV viewing is not a risk factor for ADHD (Banerjee et al. 2007). From the psychosocial factors, low family cohesion, exposure to parental psychopathology especially maternal psychopathology, low maternal education, low social class, and single parenthood are important risk factors for ADHD (Biederman and Faraone 2005). Brain structural studies do not report consistent findings for ADHD. However, most of imaging studies delineated overall decrease in total brain size, the caudate nucleus, prefrontal cortex white matter, corpus callosum and the cerebellar vermis (Tripp and Wickens 2009). Some of these areas have a high density of dopamine receptors. Neuropsychological studies show the impairment of vigilance attention, executive function, working memory response, and motivation in some children with AHD (Tripp and Wickens 2009). Brain maturation is delayed in ADHD (Curatolo et al. 2009). Finally, children with ADHD may have difficulties in social exchanges such as sharing and cooperation with peers. They are self-centered, impulsive, and commanding (Wehmeier et al. 2010).
+
+### Evaluation and Differential Diagnosis
+
+In many countries, ADHD diagnoses are generally made using Diagnostic and Statistical Manual, Fourth Edition, Text Revision (APA (2000). Diagnostic and statistical manual (DSM-IV, Text Rev.)). According to 4th Edition, Text Revision (DSM-IV-TR) criteria, there are two groups of symptoms including (a) attention deficit, (b) hyperactivity, or impulsivity. Six or more items from at least one of the groups are required for ADHD diagnosis. In addition, functional impairments in at least two different settings such as at home, school, and nursery are required. In other countries, especially in Europe, International Classification of Diseases-10 (ICD-10) is used (World Health Organization (WHO) 1992). Hyperkinetic disorder is the ICD-10 equivalent of ADHD diagnosis (WHO 1992). In ICD-10, several items from attention deficit, hyperactivity, and impulsivity are required to reach diagnosis. Therefore, it is expected that the rate of ADHD in countries using DSM-IV-TR criteria would be reported higher than that of those countries using ICD-10 criteria.
+ADHD diagnosis is subjective using the diagnostic systems criteria. There is not any objective diagnostic test or any biomedical laboratory test for it. However, the ADHD diagnosis is reliable when well-trained raters assess and agree the presence of its symptoms (Biederman and Faraone 2005). There is a weak correlation between different informants such as parents and teachers for the rating of ADHD symptoms. In other words, they usually do not agree on their assessment of symptoms in children with ADHD. The evaluation of children in different situations can be an explanation for this disagreement. Teachers evaluate children in school while the children are taking medication. Sometime, parents may report some symptoms that the symptoms are not reported by teachers. In clinical samples, ADHD is usually comorbid with other psychiatric disorders. The rate of at least one comorbid psychiatric disorder in children with ADHD is more than 80% (Ghanizadeh et al. 2008). Other disruptive behavior disorders (oppositional defiant disorder (ODD) or conduct disorder (CD)) and anxiety disorders are the most common comorbid disorders in children with ADHD. The rate for ODD and CD is about 59.3% and 13.6% (Ghanizadeh et al. 2008). Some of the other comorbid disorders are mood disorders, tic disorder, enuresis, and encopresis. It is interesting that the parent of children with ADHD usually suffer from psychiatric disorders. The lifetime prevalence of ADHD in fathers and mothers of children with ADHD are 45.8% and 17.7%, respectively. Major depressive disorder is very frequent in the parents. The rate in father and mothers are 48.1% and 43.0%, respectively (Ghanizadeh et al. 2008).
+
+### Co-occurrence of ADHD and Autism
+
+ADHD DSM-IV-derived items do not overlap with autism spectrum disorder (Ghanizadeh 2010), and the comorbidity of ADHD and autism is precluded in the DSM-IV-TR. Therefore, the symptoms of inattentiveness, hyperactivity, or impulsivity in individuals with autism originate from autism, not ADHD. Meanwhile, there are many individuals who meet diagnostic criteria for both ADHD and autism. In addition, many patients with Asperger’s syndrome are screened with concerns about ADHD (Murray 2010). The children with autism my severely attend to their interest and do not attend to other factors in their environment. It can be interpreted as inattentiveness. Also, sometimes, their stereotypic motor behavior can be interpreted as hyperactivity (Murray 2010). However, there are many published studies reported the co-occurrence of ADHD and autism. About 40–78% of individuals with autism meet diagnostic criteria for DSM-IV ADHD (Murray 2010). Eighty-seven percent of children with autism spectrum disorder have at least one of the three components of ADHD (Ames and White 2011). The rate of autistic traits in children with ADHD is from one-third to one-fifth (Grzadzinski et al. 2011).
+In addition, the subtype of ADHD is associated with the severity of difficulties in autism. For example, language and social problems are more common in those with both autism and ADHD-inattentive subtype. Moreover, less symptoms of autism are reported in those with ADHD-hyperactivity subtype. While internalizing behavior problems are usually seen in autism, externalizing behavior problems are more common in those with ADHD. A combination of externalizing and internalizing behavior problems are reported in those with both ADHD and autism (Murray 2010). Clinical profiles and outcomes of children with both ADHD and autism are different with that of those children with autism alone. They have severe social problems and poorer outcomes. Furthermore, executive function is more impaired in the individuals with both ADHD and autism than those with ADHD or autism alone. Motor coordination abnormalities are different between ADHD and autism. While motor response inhibition is more common in ADHD, motor planning impairment is more common in autism (Murray 2010). About two-thirds of children with the syndrome of deficits in attention, motor control, and perception (DAMP) meet diagnostic criteria for autism spectrum disorders. Comorbidity with developmental coordination problems is more likely to co-occur with autism symptoms than those with ADHD alone. Autism, ADHD, and dyslexia overlap genetically (Smalley et al. 2005). ADHD can be dissociated from autism spectrum disorders regarding executive dysfunction and response inhibition. Those with autism spectrum disorders are slow and accurate, while those with ADHD are impulsive (Johnston et al. 2011). It is expected that the comorbidity of ADHD and autism spectrum disorders will be allowed in DSM-V. Then, autism will not be an exclusive criterion for ADHD diagnosis.
+
+### Treatment
+
+The educating and counseling of parents (Ghanizadeh 2007), teachers (Ghanizadeh et al. 2006), and general physicians (Ghanizadeh and Zarei 2010) about ADHD is highly necessary and recommended. Many of parents, teachers, and medical service providers have not enough and updated knowledge towards ADHD symptoms and its management. Behavioral parent training is encouraged (van den Hoofdakker et al. 2007). Drug therapy with stimulant drugs (Cornforth et al. 2010) and atomoxetine (Vaughan et al. 2009) is better than no drug therapy. However, there is not enough evidence indicating any difference between these medications regarding their efficacy or side effects (King et al. 2006).
+The precise mechanism of stimulants in ADHD is not known. Noradrenaline and dopamine neurotransmitter systems are involved in ADHD. Methylphenidate and dextroamphetamine are stimulant medications which are effective in the management of ADHD. Atomoxetine is a nonstimulant catecholaminergic medication. They improve ADHD symptoms through increasing activation in cortical and subcortical regions involved in attention and executive functions (Curatolo et al. 2009). Meanwhile, there is a concern about the possible association of atomoxetine and increased suicidal behavior (Garnock-Jones and Keating 2009). There are concerns about the higher rate of side effects of stimulants in individuals with both autism and ADHD than those with ADHD alone. In addition, methylphenidate efficacy in autism is less than ADHD (Stigler et al. 2004). While the response rate is limited up to 25%, the rate of side effects reaches to 60% (Stigler et al. 2004). Dexamphetamine may worsen the symptoms (Handen et al. 2000). Clonidine and guanfacine are α-2 agonists with promising efficacy on hyperactivity, impulsivity, irritability, explosive behaviors, stereotypies, and social interaction (Scahill et al. 2006). Atomoxetine selectively inhibits the presynaptic norepinephrine transporter. There are contradictory reports about the efficacy of atomoxetine on ADHD symptoms in autism. While an open-label study supported its efficacy (Posey et al. 2006), others did not report a significant effect (Charnsil 2011). Donepezil as a anticholinesterase inhibitor may decrease some symptoms of ADHD in children with autism (Yoo et al. 2007). Further controlled trials are required to detect the significant gains of these medications on autism. There are open-label studies promising the efficacy of atypical antipsychotics, such as risperidone, quetiapine, and aripiprazole, on hyperactivity symptom in autism (Murray 2010).
+
+### See Also
+
+*   Affective Disorders (Includes Mood and Anxiety Disorders)
+*   Antipsychotics: Drugs
+*   Aripiprazole
+*   Asperger Syndrome
+*   Atomoxetine
+*   Attention
+*   Atypical Antipsychotics
+*   Autism
+*   Autistic Disorder
+*   Behavior
+*   Behavior Modification
+*   Behavior Rating Scale (BRS)
+*   Cerebral Cortex
+*   Clonidine
+*   Communication Disorder/Communication Impairment
+*   Comorbidity
+*   Conduct Disorder
+*   Developmental Milestones
+*   Dextroamphetamine
+*   DSM-III
+*   DSM-III-R
+*   DSM-IV
+*   Dyslexia
+*   Education
+*   Educational Therapy
+*   Encopresis
+*   Enuresis
+*   Epidemiology
+*   Executive Function (EF)
+*   Expressive Language Disorder
+*   Guanfacine
+*   ICD 10 Research Diagnostic Guidelines
+*   Methylphenidate
+*   Mood Disorders
+*   Motivation
+*   Motor Planning
+*   Neurotransmitter
+*   Norepinephrine
+*   Pervasive Developmental Disorder
+*   Repetitive Behavior
+*   Risperidone
+*   Stereotypic Behavior
+*   Stimulant Medications
+*   Tics
+*   Treatment Integrity
+
+### References and Reading
+
+American Psychiatric Association. (1967). Diagnostic and statistical manual for mental disorders. Washington, DC: APA Press.
+American Psychiatric Association. (1980). Diagnostic and statistical manual (DSM-III). Washington, DC: APA Press.
+American Psychiatric Association. (1987). Diagnostic and statistical manual (DSM-III, revised). Washington, DC: APA Press.
+American Psychiatric Association. (1994). Diagnostic and statistical manual (DSM-IV). Washington, DC: APA Press.
+American Psychiatric Association. (2000). Diagnostic and statistical manual (DSM-IV). Washington, DC: APA Press.
+Ames, C. S., & White, S. J. (2011). Brief report: Are ADHD traits dissociable from the autistic profile? Links between cognition and behaviour. Journal of Autism and Developmental Disorders, 41(3), 357–363.
+Banerjee, T. D., Middleton, F., & Faraone, S. V. (2007). Environmental risk factors for attention-deficit hyperactivity disorder. Acta Paediatrica, 96(9), 1269–1274.
+Biederman, J., & Faraone, S. V. (2005). Attention-deficit hyperactivity disorder. Lancet, 366(9481), 237–248.
+Charnsil, C. (2011). Efficacy of atomoxetine in children with severe autistic disorders and symptoms of ADHD: An open-label study. Journal of Attention Disorders, 15(8), 684–689.
+Coghill, D. (2010). The impact of medications on quality of life in attention-deficit hyperactivity disorder: A systematic review. CNS Drugs, 24(10), 843–866.
+Cornforth, C., Sonuga-Barke, E., & Coghill, D. (2010). Stimulant drug effects on attention deficit/hyperactivity disorder: A review of the effects of age and sex of patients. Current Pharmaceutical Design, 16(22), 2424–2433.
+Crichton, A. (2008). An inquiry into the nature and origin of mental derangement: On attention and its diseases. Journal of Attention Disorders, 12(3), 200–204. Discussion: 205–206.
+Curatolo, P., Paloscia, C., D’Agati, E., Moavero, R., & Pasini, A. (2009). The neurobiology of attention deficit/hyperactivity disorder. European Journal of Paediatric Neurology, 13(4), 299–304.
+Fischer, M., Barkley, R. A., Smallish, L., & Fletcher, K. (2002). Young adult follow-up of hyperactive children: Self-reported psychiatric disorders, comorbidity, and the role of childhood conduct problems and teen CD. Journal of Abnormal Child Psychology, 30(5), 463–475.
+Furman, L. M. (2008). Attention-deficit hyperactivity disorder (ADHD): Does new research support old concepts? Journal of Child Neurology, 23(7), 775–784.
+Garnock-Jones, K. P., & Keating, G. M. (2009). Atomoxetine: A review of its use in attention-deficit hyperactivity disorder in children and adolescents. Paediatric Drugs, 11(3), 203–226.
+Ghanizadeh, A. (2007). Educating and counseling of parents of children with attention-deficit hyperactivity disorder. Patient Education and Counseling, 68(1), 23–28.
+Ghanizadeh, A. (2010). Factor analysis on ADHD and autism spectrum disorder DSM-IV-derived items shows lack of overlap. European Child & Adolescent Psychiatry, 19(10), 797–798.
+Ghanizadeh, A. (2011). SNAP-25 may mediate the association of lead exposure and ADHD. European Journal of Paediatric Neurology, 15(3), 280–281.
+Ghanizadeh, A., & Jafari, P. (2010). Risk factors of abuse of parents by their ADHD children. European Child & Adolescent Psychiatry, 19(1), 75–81.
+Ghanizadeh, A., & Zarei, N. (2010). Are GPs adequately equipped with the knowledge for educating and counseling of families with ADHD children? BMC Family Practice, 11, 5.
+Ghanizadeh, A., Bahredar, M. J., & Moeini, S. R. (2006). Knowledge and attitudes towards attention deficit hyperactivity disorder among elementary school teachers. Patient Education and Counseling, 63(1–2), 84–88.
+Ghanizadeh, A., Mohammadi, M. R., & Moini, R. (2008). Comorbidity of psychiatric disorders and parental psychiatric disorders in a sample of Iranian children with ADHD. Journal of Attention Disorders, 12(2), 149–155.
+Grzadzinski, R., Di Martino, A., Brady, E., Mairena, M. A., O’Neale, M., Petkova, E., et al. (2011). Examining autistic traits in children with ADHD: Does the autism spectrum extend to ADHD? Journal of Autism and Developmental Disorders, 41(9), 1178–1191.
+Handen, B. L., Johnson, C. R., & Lubetsky, M. (2000). Efficacy of methylphenidate among children with autism and symptoms of attention-deficit hyperactivity disorder. Journal of Autism and Developmental Disorders, 30(3), 245–255.
+Hoffmann, H. (1948). Der Struwwelpeter. Oder lustige Geschichten und drollige Bilder für Kinder von 3 bis 6 Jahren. Loewes. Stuttgart: Frankfurter Originalausgabe.
+Johnston, K., Madden, A. K., Bramham, J., & Russell, A. J. (2011). Response inhibition in adults with autism spectrum disorder compared to attention deficit/hyperactivity disorder. Journal of Autism and Developmental Disorders, 41(7), 903–912.
+King, S., Griffin, S., Hodges, Z., Weatherly, H., Asseburg, C., Richardson, G., et al. (2006). A systematic review and economic model of the effectiveness and cost-effectiveness of methylphenidate, dexamfetamine and atomoxetine for the treatment of attention deficit hyperactivity disorder in children and adolescents. Health Technology Assessment, 10(23), iii–iv. xiii-146.
+Klassen, A. F., Miller, A., & Fine, S. (2004). Health-related quality of life in children and adolescents who have a diagnosis of attention-deficit/hyperactivity disorder. Pediatrics, 114(5), e541–e547.
+Lahey, B. B., Applegate, B., McBurnett, K., Biederman, J., Greenhill, L., Hynd, G. W., et al. (1994). DSM-IV field trials for attention deficit hyperactivity disorder in children and adolescents. The American Journal of Psychiatry, 151(11), 1673–1685.
+Lange, K. W., Reichl, S., Lange, K. M., Tucha, L., & Tucha, O. (2010). The history of attention deficit hyperactivity disorder. Attention Deficit Hyperactivity Disorder, 2(4), 241–255.
+Murray, M. J. (2010). Attention-deficit/hyperactivity disorder in the context of autism spectrum disorders. Current Psychiatry Reports, 12(5), 382–388.
+Nigg, J., Nikolas, M., & Burt, S. A. (2010). Measured gene-by-environment interaction in relation to attention-deficit/hyperactivity disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 49(9), 863–873.
+Posey, D. J., Wiegand, R. E., Wilkerson, J., Maynard, M., Stigler, K. A., & McDougle, C. J. (2006). Open-label atomoxetine for attention-deficit/hyperactivity disorder symptoms associated with high-functioning pervasive developmental disorders. Journal of Child and Adolescent Psychopharmacology, 16(5), 599–610.
+Rothenberger, A., & Neumärker, K. J. (2005). Wissenschaftsgeschichte der ADHS. Steinkopff, Darmstadt Kramer-Pollnow im Spiegel der Zeit.
+Scahill, L., Aman, M. G., McDougle, C. J., McCracken, J. T., Tierney, E., Dziura, J., et al. (2006). A prospective open trial of guanfacine in children with pervasive developmental disorders. Journal of Child and Adolescent Psychopharmacology, 16(5), 589–598.
+Smalley, S. L., Loo, S. K., Yang, M. H., & Cantor, R. M. (2005). Toward localizing genes underlying cerebral asymmetry and mental health. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics, 135B(1), 79–84.
+Steinhausen, H. C. (2009). The heterogeneity of causes and courses of attention-deficit/hyperactivity disorder. Acta Psychiatrica Scandinavica, 120(5), 392–399.
+Stigler, K. A., Desmond, L. A., Posey, D. J., Wiegand, R. E., & McDougle, C. J. (2004). A naturalistic retrospective analysis of psychostimulants in pervasive developmental disorders. Journal of Child and Adolescent Psychopharmacology, 14(1), 49–56.
+Still, G. F. (1902). Some abnormal psychical conditions in children: The Goulstonian lectures. Lancet, 1902, 1008–1012.
+Tripp, G., & Wickens, J. R. (2009). Neurobiology of ADHD. Neuropharmacology, 57(7–8), 579–589.
+van den Hoofdakker, B. J., van der Veen-Mulders, L., Sytema, S., Emmelkamp, P. M., Minderaa, R. B., & Nauta, M. H. (2007). Effectiveness of behavioral parent training for children with ADHD in routine clinical practice: A randomized controlled study. Journal of the American Academy of Child and Adolescent Psychiatry, 46(10), 1263–1271.
+Vaughan, B., Fegert, J., & Kratochvil, C. J. (2009). Update on atomoxetine in the treatment of attention-deficit/hyperactivity disorder. Expert Opinion on Pharmacotherapy, 10(4), 669–676.
+Wehmeier, P. M., Schacht, A., & Barkley, R. A. (2010). Social and emotional impairment in children and adolescents with ADHD and the impact on quality of life. The Journal of Adolescent Health, 46(3), 209–217.
+World Health Organization (WHO). (1992). The ICD-10 classification of mental and behavioural disorders. Clinical descriptions and diagnostic guidelines. Geneva: World Health Organization (WHO).
+Yoo, J. H., Valdovinos, M. G., & Williams, D. C. (2007). Relevance of donepezil in enhancing learning and memory in special populations: A review of the literature. Journal of Autism and Developmental Disorders, 37(10), 1883–1901.
+
+## Attention Network Tests in ASD
+
+### Definition
+
+Attention has been conceptualized as a multi-component system comprised of three isolable but interacting networks: alerting, orienting, and executive control (Posner and Petersen 1990). Alerting refers to the achievement and maintenance of a state of readiness to respond, orienting refers to the selection of an input pathway for further processing, and executive control refers to resolution of conflict between competing inputs and responses. The Attention Network Test (ANT), first described by Fan et al. (2002), was developed as a computerized tool for assessing the efficacy of each network.
+In the ANT, participants are asked to fixate on a central cross responding to target arrows, which appear either above or below fixation. Targets are sometimes preceded by asterisks appearing at the center of the screen (center cue), above and below fixation simultaneously (double cue), or at the location of a subsequent target (spatial cue). In other words, cues may predict the onset (alerting cues) and/or location (orienting cues) of the target arrow. Finally, target arrows are flanked by arrows pointing in the same direction, arrows pointing in the opposite direction, or neutral bars. Network scores are typically calculated as differences in mean reaction time (RT) in opposing conditions. The orienting effect is the RT difference between center cue and spatial cue conditions, the alerting effect is the RT difference between no-cue and double-cue conditions, and the executive control effect is the RT difference between congruent and flanker conditions.
+
+### Historical Background
+
+Since the ANT was first introduced by Fan et al. (2002), substantial evidence has emerged supporting the biological validity of the three-network model. Unique neural patterns associated with each network have been identified using both electroencephalography (Fan et al. 2007) and functional magnetic resonance imaging (Fan et al. 2005). Furthermore, genetic studies suggest that there are heritable factors for executive control, as measured by the ANT (Fan et al. 2001).
+Although the three attention networks are biologically and functionally distinct, and network scores are reliable across sessions (Ishigami and Klein 2010), frequently reported interaction effects between cue and flanker type suggest that these networks are not entirely independent (Fan et al. 2002; Ishigami and Klein 2010; Rueda et al. 2004). True independence is theoretically unlikely, assuming there is constant communication among functionally distinct brain regions and networks. Indeed, variations of the ANT have provided compelling evidence that the processes of orienting, alerting, and executive control do, in fact, modulate one another (e.g., Callejas et al. 2005; Fan et al. 2009; Fuentes and Campoy 2008)
+Variants of the ANT have been developed to suit a range of purposes. For example, the child-ANT (ANT-C) features colorful, fish-shaped stimuli, which are meant to be more engaging for younger participants (Rueda et al. 2004). A lateralized version of the ANT (Greene et al. 2008) has been used to effectively isolate attentional processes in the left and right hemispheres. To better detect network differences, a revised version of the original ANT (ANT-R; Fan et al. 2009) modified a number of parameters, such as visual angle, cue-to-target interval, target duration, and target placement. The ANT-R also included orienting cues presented at locations other than that of the target, known as “invalid” cues. In another version known as the ANT-interaction (ANT-I; Callejas et al. 2004), 50% of all spatial cues are invalid (i.e., they are “uninformative”). This version of the task additionally introduced auditory alerting tones to facilitate exploring the interaction between alerting and orienting networks. Recently, the ANT has been adapted into a game-like format in an effort to improve engagement relative to previous versions of the test. In the AttentionTrip (Klein et al. 2017), the participant uses a wheel to steer a spaceship through a wormhole while “shooting” target stimuli as they appear on the screen. This version of the task has been used with high-functioning adults on the autism spectrum (Mash et al. 2018) and may also demonstrate utility in research settings with young or lower-functioning individuals.
+
+### Current Knowledge
+
+To date, there is a relatively small but growing body of literature reporting attention network scores in individuals with ASD. These studies have inconsistently reported significant differences between ASD and typically developing (TD) groups in all three major networks. Furthermore, these experiments vary considerably with respect to method (i.e., version of the ANT used), outcome variables reported (accuracy, reaction time), sample size, and age of the sample. In several studies, the sample sizes are quite small (e.g., N ¼ 12) and therefore have limited power to detect negative results. However, several general themes have emerged from the extant literature that may guide future research.
+
+#### Orienting
+
+Problems with attention orienting and disengagement have been well-documented in individuals with ASD across the life span (Sacrey et al. 2014). Reduced orienting efficiency has been corroborated by several studies using versions of the ANT. In a sample of children and adolescents with and without ASD (ages 8–19), Keehn et al. (2010) found smaller orienting network scores on the original ANT in the ASD group, likely reflecting reduced benefit of an orienting cue compared to the TD group. Less efficient orienting was similarly reported by Mutreja et al. (2016) in younger children with ASD (5–11 years) using the ANT-C. In a very small sample of older adolescents (six ASD and six TD, ages 16–17), Hames et al. (2016) did not find any significant group differences on the ANT-C with respect to orienting reaction time. However, they reported that the ASD group was more error-prone on orienting trials and that they tended to over-recruit brain regions typically associated with executive control during the orienting task. Although the above studies appear to implicate atypical orienting in younger individuals with ASD, other work has found relatively typical orienting on the ANT in both children (Ip et al. 2017; Samyn et al. 2017) and young adults (Fan et al. 2012; Mash et al. 2018) on the autism spectrum. Considering the critical role of attention orienting in early social development (Keehn et al. 2013), this is an important area of clarification for future research.
+
+#### Alerting
+
+Alerting network scores may reflect changes in both tonic and phasic alertness. Tonic alertness refers to intrinsic arousal, whereas phasic alertness is associated with rapid changes induced by a stimulus. Atypically large network scores may suggest reduced tonic alertness, resulting in slower reaction times in the absence of an alerting cue. Very small network scores, on the other hand, may be interpreted as reduced phasic alertness, resulting in only marginal improvements in reaction time in the presence of an alerting cue. In a study comparing typically developing children to those with ASD and attention-deficit/hyperactivity disorder (ADHD), alerting network scores on the ANT-I were significantly larger in the ADHD group, but were comparable in the ASD and TD groups (Samyn et al. 2017). A study using the original ANT reported no significant group differences in alerting between ASD and TD children and adolescents, but alerting network score size was associated with symptom severity in the ASD group. In contrast, Mash et al. (2018) reported reduced alerting network scores in young adults using the original ANT, but not the AttentionTrip. In another sample of young adults tested on the ANT-R, Fan et al. (2012) reported that the ASD group made more errors in the absence of a cue, suggesting potentially poorer tonic alertness. Furthermore, using fMRI, they found that alerting errors were associated with reduced brain activity in the medial frontal gyri and caudate. As with orienting network scores, some research reported no significant group differences in alerting networks in ASD (Ip et al. 2017; Mutreja et al. 2016; Ridderinkhof et al. 2018; Samyn et al. 2017).
+
+#### Executive Control
+
+In general, studies of both children and adults measuring reaction time differences between congruent and incongruent flanker conditions on various versions of the ANT have found similar executive control networks in typical development and ASD (Fan et al. 2012; Hames et al. 2016; Ip et al. 2017; Keehn et al. 2010; Mash et al. 2018; Mutreja et al. 2016; Ridderinkhof et al. 2018; Samyn et al. 2017). One of these studies described an inverse relationship between IQ and the size of the executive control network in children and adolescents with ASD (Keehn et al. 2010), suggesting that inefficient executive processes (i.e., slower reaction time on incongruent trials) may be directly related to general cognitive ability. Supporting this possibility, they did not find any relationship between executive control and ASD symptoms. This study additionally reported that the alerting and executive control networks demonstrated unusually high interdependence in ASD individuals. The authors speculated that this might reflect compensatory executive strategies to control alertness in individuals with poorer intrinsic regulation of arousal. Although reaction times tend to be similar in ASD and TD individuals, there is some evidence that ASD individuals show significantly reduced accuracy on incongruent trials relative to congruent trials, resulting in larger accuracy difference scores. Mutreja et al. (2016) reported this effect in children (ages 5–11) using the ANT-C; a similar finding that did not reach statistical significance was reported in a larger sample of slightly older group of individuals aged 8–23 (Ridderinkhof et al. 2018). Using the ANT-R, Fan et al. (2012) demonstrated poorer executive control accuracy in adults with ASD; further, they found that less accurate performance on the flanker component of the task was associated with reduced activation in the anterior cingulate cortex and more severe language and communication symptoms in the ASD group. Therefore, although individuals with ASD do not appear to respond more slowly to incongruent flankers, error analysis suggests that they may trade speed for accuracy on this task. Furthermore, it appears that accuracy, but not reaction time, may relate to behavioral and brain markers of ASD.
+
+### Future Directions
+
+Studies examining attention using ANT-like tasks have provided some insight into attention network function in individuals with ASD. For example, participants on the autism spectrum generally tend to demonstrate reduced orienting efficiency, as well as poorer task accuracy when resolving conflict. However, even these relatively well-established findings have not been consistent across studies. Although ANT tasks are increasingly used and reported in ASD research, this body of literature remains fairly small and heterogeneous. There is great deal of variability with respect to participant age, sample size, ANT version, and outcome measures reported, which complicates direct comparison of findings. However, further study with adequate sample sizes may help to clarify the details of some of the emerging themes in this field.
+A main disadvantage of the ANT is its length and repetitive nature. This may pose a challenge for populations that may have difficulty with sustained attention. Often, such individuals are of greatest interest to researchers studying attention. However, insufficient or variable effort throughout the entire task may preclude accurate interpretation of the resulting data. A recently developed, game-like version of the ANT (the AttentionTrip; Klein et al. 2017) may help to mitigate problems with engagement in younger or cognitively impaired groups. The AttentionTrip has been used successfully in high-functioning adults on the autism spectrum (Mash et al. 2018), but future work may establish whether it can improve engagement in children or lower-functioning participants with ASD.
+
+### See Also
+
+*   Arousal
+*   Attention
+*   Cognitive Skills
+*   Executive Function (EF)
+*   Orienting Response
+
+### References and Reading
+
+Callejas, A., Lupiáñez, J., & Tudela, P. o. (2004). The three attentional networks: On their independence and interactions. Brain and Cognition, 54(3), 225–227. https://doi.org/10.1016/j.bandc.2004.02.012.
+Callejas, A., Lupiàñez, J., Funes, M. J., & Tudela, P. (2005). Modulations among the alerting, orienting and executive control networks. Experimental Brain Research, 167(1), 27–37. https://doi.org/10.1007/s00221-005-2365-z.
+Fan, J., Wu, Y., Fossella, J. A., & Posner, M. I. (2001). Assessing the heritability of attentional networks. BMC Neuroscience, 2, 14. https://doi.org/10.1186/1471-2202-2-14.
+Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14(3), 340–347. https://doi.org/10.1162/089892902317361886.
+Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., & Posner, M. I. (2005). The activation of attentional networks. NeuroImage, 26(2), 471–479. https://doi.org/10.1016/j.neuroimage.2005.02.004.
+Fan, J., Byrne, J., Worden, M. S., Guise, K. G., McCandliss, B. D., Fossella, J., & Posner, M. I. (2007). The relation of brain oscillations to attentional networks. Journal of Neuroscience, 27(23), 6197–6206. https://doi.org/10.1523/JNEUROSCI.1833-07.2007.
+Fan, J., Gu, X., Guise, K. G., Liu, X., Fossella, J., Wang, H., & Posner, M. I. (2009). Testing the behavioral interaction and integration of attentional networks. Brain and Cognition, 70(2), 209–220. https://doi.org/10.1016/j.bandc.2009.02.002.
+Fan, J., Bernardi, S., Van Dam, N. T., Anagnostou, E., Gu, X., Martin, L., . .. Hof, P. R. (2012). Functional deficits of the attentional networks in autism. Brain and Behavior, 2(5), 647–660. https://doi.org/10.1002/brb3.90.
+Fuentes, L. J., & Campoy, G. (2008). The time course of alerting effect over orienting in the attention network test. Experimental Brain Research, 185(4), 667–672. https://doi.org/10.1007/s00221-007-1193-8.
+Greene, D. J., Barnea, A., Herzberg, K., Rassis, A., Neta, M., Raz, A., & Zaidel, E. (2008). Measuring attention in the hemispheres: The lateralized attention network test (LANT). Brain and Cognition, 66(1), 21–31. https://doi.org/10.1016/j.bandc.2007.05.003.
+Hames, E. C., Rajmohan, R., Fang, D., Anderson, R., Baker, M., Richman, D. M., & O’Boyle, M. (2016). Attentional networks in adolescents with high-functioning autism: An fMRI investigation. The Open Neuroimaging Journal, 10, 102–110. https://doi.org/10.2174/1874440001610010102.
+Ip, H. H. S., Lai, C. H.-Y., Wong, S. W. L., Tsui, J. K. Y., Li, R. C., Lau, K. S.-Y., & Chan, D. F. Y. (2017). Visuospatial attention in children with Autism Spectrum Disorder: A comparison between 2-D and 3-D environments. Cogent Education, 4(1), 1307709. https://doi.org/10.1080/2331186X.2017.1307709.
+Ishigami, Y., & Klein, R. M. (2010). Repeated measurement of the components of attention using two versions of the Attention Network Test (ANT): Stability, isolability, robustness, and reliability. Journal of Neuroscience Methods, 190(1), 117–128. https://doi.org/10.1016/j.jneumeth.2010.04.019.
+Keehn, B., Lincoln, A. J., Müller, R.-A., & Townsend, J. (2010). Attentional networks in children and adolescents with autism spectrum disorder. Journal of Child Psychology and Psychiatry, 51(11), 1251–1259. https://doi.org/10.1111/j.1469-7610.2010.02257.x.
+Keehn, B., Müller, R.-A., & Townsend, J. (2013). Atypical attentional networks and the emergence of autism. Neuroscience and Biobehavioral Reviews, 37(2), 164–183. https://doi.org/10.1016/j.neubiorev.2012.11.014.
+Klein, R. M., Hassan, T., Wilson, G., Ishigami, Y., & Mulle, J. (2017). The AttentionTrip: A game-like tool for measuring the networks of attention. Journal of Neuroscience Methods, 289, 99–109. https://doi.org/10.1016/j.jneumeth.2017.07.008.
+Mash, L. E., Klein, R. M., & Townsend, J. (2018). Brief report: A gaming approach to the assessment of attention networks in autism spectrum disorder and typical development. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-018-3635-5.
+Mutreja, R., Craig, C., & O’Boyle, M. W. (2016). Attentional network deficits in children with autism spectrum disorder. Developmental Neurorehabilitation, 19(6), 389–397. https://doi.org/10.3109/17518423.2015.1017663.
+Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13, 25–42. https://doi.org/10.1146/annurev.ne.13.030190.000325.
+Ridderinkhof, A., de Bruin, E. I., van den Driesschen, S., & Bogels, S. M. (2018). Attention in children with autism spectrum disorder and the effects of a mindfulness-based program. Journal of Attention Disorders. https://doi.org/10.1177/1087054718797428.
+Rueda, M. R., Fan, J., McCandliss, B. D., Halparin, J. D., Gruber, D. B., Lercari, L. P., & Posner, M. I. (2004). Development of attentional networks in childhood. Neuropsychologia, 42(8), 1029–1040. https://doi.org/10.1016/j.neuropsychologia.2003.12.012.
+Sacrey, L. A., Armstrong, V. L., Bryson, S. E., & Zwaigenbaum, L. (2014). Impairments to visual disengagement in autism spectrum disorder: A review of experimental studies from infancy to adulthood. Neuroscience and Biobehavioral Reviews, 47, 559–577. https://doi.org/10.1016/j.neubiorev.2014.10.011.
+Samyn, V., Roeyers, H., Bijttebier, P., & Wiersema, J. R. (2017). Attentional networks in boys with ADHD or autism spectrum disorder and the relationship with effortful control. Journal of Attention Disorders, 21(3), 228–239. https://doi.org/10.1177/10870547 12473183.
+
+## Attention Process Training (APT) Program
+
+### Definition
+
+The Attention Process Training (APT and APT-II) program is a cognitive rehabilitation intervention that targets focused, sustained, selective, alternating, and divided attention (Sohlberg and Mateer 1987; Sohlberg et al. 2001). APT developers define focused attention as the ability to respond to specific stimuli. Sustained attention refers to the ability to consistently respond during a continuous or repetitive activity. Selective attention is the ability to activate and inhibit responses based on discrimination of stimuli. Alternating attention refers to aptitude for mental flexibility, and divided attention has been defined as the ability to engage in multiple tasks simultaneously.
+In general, process training involves implementing a structured treatment program to improve attention skills in a variety of areas (Sohlberg et al. 2001). The APT materials consist of tasks that are hierarchically organized to target sustained, selective, alternating, and divided attention (Sohlberg et al. 2001). The hierarchical structure is intended to allow for basic skills to be constantly utilized while developing and practicing more complex skills (Palmese and Raskin 2000). Auditory attention tapes and visual activities are used for some of the tasks. APT also includes exercises to facilitate generalization of skills to daily life (Palmese & Raskin). The APT approach has been referred to as process-specific cognitive rehabilitation because it is intended to improve particular types of attention skills and does not lead to improvements in overall cognitive functioning (Sohlberg and Mateer 1987).
+
+### Historical Background
+
+APT was developed by Sohlberg and Mateer (1987) based on experimental attention literature, clinical observation, and patients’ subjective reports of symptoms. It frames attention as a multidimensional cognitive capacity (Sohlberg & Mateer). The APT-II is an extension of the original APT and is designed to target more complex attention impairments (Murray et al. 2006).
+
+### Rationale or Underlying Theory
+
+APT follows a process-specific approach to cognitive rehabilitation in that it is intended to improve functioning in distinct cognitive areas (Sohlberg and Mateer 1987). The rationale underlying APT is that learning specific skills may help improve some of the cognitive problems that result from acquired brain damage (Park et al. 1999). A process-specific approach can be contrasted with the functional adaptation and the general stimulation perspectives. The functional adaptation approach utilizes task analysis and changes in the environment to assist with the challenges associated with cognitive impairments. The general stimulation approach utilizes tasks that facilitate any type of cognitive processing. These prior approaches to cognitive rehabilitation have been criticized as leading to poor generalizability and lacking a theoretical orientation, respectively (Sohlberg and Mateer 1987; Sohlberg et al. 2001).
+
+### Goals and Objectives
+
+The objectives of APTare to improve individuals’ focused attention, sustained attention, selective attention, alternating attention, and divided attention skills following an acquired brain injury, although the program has also been used with other populations. Individualized treatment goals are created based on the needs of the client in each of these areas of attention.
+
+### Treatment Participants
+
+Although APT was designed for use with individuals who have acquired brain injury and most published research on the APT has been based on this population, some researchers have examined the efficacy of APT for individuals with schizophrenia and aphasia. Little is known about the efficacy of the program with other populations. Some have suggested that APT could be beneficial for individuals with autism spectrum disorders (Ozonoff et al. 2005), although published efficacy research to date has not been conducted with this population.
+
+### Treatment Procedures
+
+The APT program is comprised of a set of activities that have a common structure and that range in complexity and processing speed requirements (Sohlberg and Mateer 1987). Treatment goals are individualized based on the client’s impairments in each of the attention areas targeted (i.e., sustained, selective, alternating, and divided). Each task is designed to offer practice in one or more levels of attention. The tasks are either client-paced or therapist-paced depending on the nature of the exercise (Park et al. 1999).
+The APT-II includes general exercises, each requiring approximately 5 min to complete, for each of the specific areas of attention emphasized in the program (Palmese and Raskin 2000). Four types of activities are incorporated into APT: visual cancelation, auditory cancelation, mental control, and daily life attentional activities (López-Luengo and Vázquez 2003). Within each exercise, there are tasks that increase in speed and difficulty. When the client completes the final activity for a particular sequence, he or she can advance to the next level. Each exercise is repeated until it is completed successfully according to specified criteria. Some researchers have noted that the linguistic demands of APT tasks need to be taken into account for treatment planning with patients who have language impairments (Murray et al. 2006). In the area of sustained attention, examples of visual activities include cancelation tasks (e.g., crossing out all the Ps and Cs in a long series of letters) where the client is scored on completion time, omissions, and errors. Audio activities include tasks such as having the client press a button when he or she hears a target stimulus among a set of distracters (e.g., identifying items that are round from a list of words) and is scored for accuracy (Pero et al. 2006). For selective attention, tasks from sustained attention are included but with more irrelevant and distracting stimuli added (e.g., auditory stimuli recorded over a noisy background). Similar tasks are also incorporated into the alternating attention activities but with instructions to change the target stimuli every 15 seconds. The divided attention activities include completing the visual and auditory cancelation tasks simultaneously, as well as card sorting and Stroop tasks (Pero et al.). Solving math problems and identifying main ideas from paragraphs are also examples of APT tasks (Palmese and Raskin 2000). The program does not specify a particular number of sessions but recommends that response time should be decreased by 35% before moving on to the next task and that the client achieve 85% accuracy on each task (Pero et al. 2006). Researchers examining the efficacy of the APT program have generally implemented the intervention for a range of 4–10 weeks at a frequency of one to nine sessions per week (e.g., Coelho 2005; Palmese and Raskin 2000; Sohlberg and Mateer 1987; Sohlberg et al. 2000).
+
+### Efficacy Information
+
+There is some evidence that APT may lead to improvements in specific attentional skills but not in general cognitive functioning. Most of the efficacy research for APT has been based on single-case designs with small sample sizes (e.g., Coelho 2005; Murray et al. 2006; Palmese and Raskin 2000; Pero et al. 2006; Sohlberg and Mateer 1987), although a few studies have incorporated between-group designs with random assignment (e.g., López-Luengo and Vázquez 2003; Sohlberg et al. 2000). In general, researchers have found some support for improvement on sustained, selective, and divided attention tasks, as well as reading comprehension, in certain situations (Boman et al. 2004; Coelho 2005; Kurtz et al. 2001; Murray et al. 2006; Palmese and Raskin 2000; Pero et al. 2006; Sohlberg et al. 2000; Sohlberg and Mateer 1987). However, studies have not consistently found evidence of improvement in attention skills resulting from APT (e.g., López-Luengo and Vázquez 2003; Silverstein et al. 2005).
+For example, individuals with brain injury who have completed the APT program have shown improvement on the paced auditory serial addition task (PASAT; Gronwall 1977), a measure of sustained attention and information processing speed (Park et al. 1999). However, control subjects who did not receive APT also showed improvement on this task over time (Park et al.). Compared to individuals receiving brain injury education, those who received APT in another study made greater gains on the PASAT (Sohlberg et al. 2000). Another task on which individuals with brain injury who have completed APT have shown improvement is the consonant trigrams activity (Park et al. 1999), which involves recalling three consonants heard after counting backward by threes. It is intended to measure memory under conditions of distraction.
+
+### Outcome Measurement
+
+Avariety of outcome measures including attention tasks, questionnaires, and participant interviews have been used in APT efficacy research. However the most commonly used outcome measures appear to be the paced auditory serial addition task (PASAT; Gronwall 1977), consonant trigrams (Peterson and Peterson 1959), Trails B, and variations of the Stroop task (Stroop 1935).
+
+#### Paced Auditory Serial Addition Task
+
+The PASAT measures rate of information processing and was designed to assess the rate and degree of progress for clients recovering from concussion (Gronwall 1977). It is comprised of a randomized presentation of an auditory digit sequence, and the participant is expected to add each new digit to the preceding one (Sohlberg et al. 2000). Subsequent trials are presented at increasingly faster rates. Scores can be calculated as the correct number of responses at each trial pace or average time per correct response (Gronwall 1977). The PASAT is considered to require two types of attention: sustained attention and the ability to identify and correct errors during the activity (Park et al. 1999). Some have questioned whether improvement on this task following APT is due to the intervention or is an effect of repeated testing (Pero et al. 2006).
+
+#### Consonant Trigrams/Brown-Peterson Task
+
+This task measures memory skills under conditions of distraction (Park et al. 1999). Individuals participating in this task hear three consonants followed by a number. They are then asked to count backward by threes for a predetermined number of seconds (e.g., 3, 9, 18). After the set time has elapsed, the participant is expected to recall the three consonants heard at the beginning of the trial. Delays of varying lengths between the end of the counting backward and the instruction to recall the consonants are also incorporated into the assessment (Park et al.).
+
+#### Trails B
+
+Trails B was originally part of the Army Individual Test Battery and is a task that measures visual scanning, mental flexibility, planning abilities, and working memory (Corrigan and Hinkeldey 1987; Sohlberg et al. 2000). Participants are asked to draw lines connecting consecutively numbered and lettered circles and alternate between the two (e.g., in the order 1-A-2-B-3-C-4-D. . .). Trails B can be scored as number of seconds required to complete the task (Corrigan and Hinkeldey 1987).
+
+#### The Stroop Task
+
+The Stroop task measures the interference effects of conflicting stimuli (Stroop 1935). Participants are shown a list of color words and asked to name the colors in which the words are printed (e.g., red, yellow) and ignore the words themselves (e.g., naming “yellow” for the word “red” printed in yellow ink). The task can also be completed by having participants read the list of color words while ignoring the ink color in which they are printed. Many variations of this original task have been developed that utilize different types of conflicting stimuli (MacLeod 1991).
+
+### Qualifications of Treatment Providers
+
+Psychologists, speech-language pathologists, occupational therapists, special education staff, and related professionals with appropriate training in cognitive rehabilitation would generally be considered qualified to implement APT.
+
+### See Also
+
+*   Attention
+*   Auditory Discrimination
+*   Auditory Processing
+*   Executive Function (EF)
+*   Information Processing Speed
+*   Memory
+*   Reaction Time
+*   Short-Term Memory
+*   Visual Processing
+*   Visual Scanning
+
+### References and Reading
+
+Boman, I.-L., Lindstedt, M., Hemmingsson, H., & Bartfai, A. (2004). Cognitive training in home environment. Brain Injury, 18, 985–995.
+Coelho, C. A. (2005). Direct attention training as a treatment for reading impairment in mild aphasia. Aphasiology, 19, 275–283.
+Corrigan, J. D., & Hinkeldey, N. S. (1987). Relationships between parts A and B of the trail making test. Journal of Clinical Psychology, 43, 402–409.
+Gronwall, D. M. A. (1977). Paced auditory serial-addition task: A measure of recovery from concussion. Perceptual and Motor Skills, 44, 367–373.
+Kurtz, M. M., Moberg, P. J., Mozley, L. H., Swanson, C. L., Gur, R. C., & Gur, R. E. (2001). Effectiveness of an attention- and memory-training program on neuropsychological deficits in schizophrenia. Neurorehabilitation and Neural Repair, 15, 75–80.
+López-Luengo, B., & Vázquez, C. (2003). Effects of attention process training on cognitive functioning of schizophrenic patients. Psychiatry Research, 119, 41–53.
+MacLeod, C. M. (1991). Half a century of research on the Stroop effect: An integrative review. Psychological Bulletin, 109, 163–203.
+Mohlman, J. (2008). More power to the executive? A preliminary test of CBT plus executive training for treatment of late-life GAD. Cognitive and Behavioral Practice, 15, 306–316.
+Murray, L. L., Keeton, R. J., & Karcher, L. (2006). Treating attention in mild aphasia: Evaluation of attention process training-II. Journal of Communication Disorders, 39, 37–61.
+Ozonoff, S., South, M., & Provencal, S. (2005). Executive functions. In F. R. Volkmar, R. Paul, A. Kiln, & D. Cohen (Eds.), Handbook of autism and pervasive developmental disorders: Vol. 1, diagnosis, development, neurobiology, and behavior (pp. 606–627). Hoboken: Wiley.
+Palmese, C. A., & Raskin, S. A. (2000). The rehabilitation of attention in individuals with mild traumatic brain injury, using the APT-II programme. Brain Injury, 14, 535–548.
+Park, N. W., Proulx, G.-B., & Towers, W. M. (1999). Evaluation of the attention process training programme. Neuropsychological Rehabilitation, 9, 135–154.
+Pero, S., Incoccia, C., Caracciolo, B., Zoccolotti, P., & Formisano, R. (2006). Rehabilitation of attention in two patients with traumatic brain injury by means of ‘attention process training’. Brain Injury, 20, 1207–1219.
+Peterson, L. R., & Peterson, M. J. (1959). Short-term retention of individual verbal items. Journal of Experimental Psychology, 58, 193–198.
+Silverstein, S. M., Hatashita-Wong, M., Solak, B. A., Uhlhaas, P., Landa, Y., Wilkniss, S. M., et al. (2005). Effectiveness of a two-phase cognitive rehabilitation intervention for severely impaired schizophrenia patients. Psychological Medicine, 35, 829–837.
+Sohlberg, M. M., & Mateer, C. A. (1987). Effectiveness of an attention-training program. Journal of Clinical and Experimental Neuropsychology, 9, 117–130.
+Sohlberg, M. M., McLaughlin, K. A., Pavese, A., Hedrich, A., & Posner, M. I. (2000). Evaluation of attention process training and brain injury education in persons with acquired brain injury. Journal of Clinical and Experimental Neuropsychology, 22, 656–676.
+Sohlberg, M. M., Johnson, L., Paule, L., Raskin, S. A., & Mateer, C. A. (2001). Attention process training-II: A program to address attentional deficits for persons with mild cognitive dysfunction (2nd ed.). Wake Forest: Lash & Associates.
+Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643–662.
+
+## Attentional Disengagement
+
+### Definition
+
+The first of the three subfunctions necessary for visual-spatial orienting (disengage, shift, and engage); the removal of attention from and/or ocular engagement with a stimulus that enables a shift of attention from one location to another.
+
+### Historical Background
+
+Attention and autism spectrum disorder. Although autism spectrum disorder (ASD) is diagnosed on the basis of impairments in social interaction and communication as well as the presence of repetitive and stereotyped interests and behaviors (APA 2013), differences in attention have been noted as secondary or associated features since the disorder was first described (Asperger 1944; Kanner 1943). For example, in his original account, Asperger (1944) observed that:
+We regularly find a disturbance of active attention in autistic children. Here we are not [. . .] talking about the common-or-garden problems of concentration. These are problems that we find in many [children with other developmental disabilities] who are constantly distracted from work by external stimuli [. . .]. Autistic children on the other hand are, from the start, not interested in directing their attention to outside stimuli [. . .]. They follow their own ideas, which are mostly far removed from ordinary concerns, and do not like to be distracted from their thoughts.
+Likewise, for one of his original 11 cases, Kanner (1943) remarked that, “to get his attention almost requires one to break down a mental barrier between his inner consciousness and the outside world” (p. 218). However, it was not until the 1960s and 1970s that research focused on the attentional differences in individuals with ASD began in earnest with the work of Hutt et al. (1964), Hermelin and O’Connor (1964), as well as Lovaas et al. (1971). Later, pioneering research led by Michael Posner (1980) investigating visual-spatial orienting in neurotypical individuals as well as those with cortical and subcortical lesions (Posner et al. 1982) illuminated this basic cognitive process and its associated brain network. Based on this work, Posner et al. (1984) later outlined the subcomponents of visual-spatial orienting: disengaging, shifting, and reengaging attention. Attentional disengagement thus reflects the initial step of the orienting process and is a prerequisite for shifting and then engaging a new object, person, or location within one’s environment. Subsequent research using Posner’s cuing paradigm in ASD provided the first evidence of impaired nonsocial visual-spatial orienting and in particular showed deficits in disengaging attention (Casey et al. 1993; Townsend et al. 1996; Wainwright-Sharp and Bryson 1993).
+
+### Current Knowledge
+
+How do we measure disengagement? In addition to the Posner cuing paradigm, attentional disengagement in ASD has primarily been measured using gap-overlap tasks, which examine differences in the latency of eye movements to peripheral targets appearing with, and without, a central stimulus (Saslow 1967). The time required to execute saccadic eye movements (also referred to as saccadic reaction time; SRT) is reduced when a fixated central stimulus is removed prior to (i.e., gap condition) or simultaneously with (i.e., baseline or step condition) the onset of a peripheral target compared to when the central stimulus remains on screen when the peripheral target appears (i.e., overlap condition). Attentional disengagement, as measured by the gap effect (i.e., overlap SRT – gap SRT), is associated with both attentional and oculomotor components, and arises from two distinct sources: (1) a generalized alerting effect as a consequence of the fixation offset, which cues participants about the impending peripheral target and (2) the release of ocular inhibition due to (a) removal of the foveal stimulus and (b) top-down preparation of a saccade (e.g., Kingstone and Klein 1993). Disengagement abilities have been measured using modified gap-overlap paradigms across the lifespan from infants at risk for ASD (because they have an older sibling diagnosed with the disorder) to adults diagnosed with ASD (see Sacrey et al. 2014, for review).
+Attentional disengagement in ASD. Results of studies employing gap-overlap paradigms in ASD are mixed with evidence of equivalent (e.g., Fischer et al. 2016; Schmitt et al. 2014; Zalla et al. 2018), slower (Elison et al. 2013; Elsabbagh et al. 2013; Kawakubo et al. 2007; Kleberg et al. 2017; Landry and Bryson 2004; Sabatos-DeVito et al. 2016), and faster (van der Geest et al. 2001) disengagement. Evidence of impaired disengagement in ASD has received the most support from studies of high-risk infant siblings of children with ASD and has now been replicated by three separate research groups using unique cohorts of infants (Bryson et al. 2018; Elison et al. 2013; Elsabbagh et al. 2013). This deficit in attentional disengagement emerges around the end of the first year of life and has been shown to persist in children (Kleberg et al. 2017; Landry and Bryson 2004; Sabatos-DeVito et al. 2016) and adults (Kawakubo et al. 2007). Further, while these studies examining attentional disengagement in ASD have almost exclusively used visual stimuli, Keehn et al. (2019) recently showed reduced disengagement efficiency in children with ASD in the auditory domain, suggesting that disengagement impairments in ASD are not specific to the visual modality. Interestingly, this impairment in attentional disengagement is essentially in accord with the early anecdotal accounts by Kanner (1943) and Asperger (1944). That is, difficulties disengaging attention may manifest themselves in becoming “stuck” and subsequently failing to “direct their attention to outside stimuli.” However, as referenced above, not all investigations have reported impairments in attentional disengagement in ASD. Inconsistent findings may arise from a variety of sources including the heterogeneous nature of ASD, the ages investigated, and differences in task design. Regarding the latter point, Keehn et al. (2019) noted two methodological factors that may contribute to the presence or absence of disengagement differences in ASD: (1) the type of fixation stimulus (e.g., dynamic or static images) and (2) predictability in the sequence of stimuli. For example, disengagement impairments are more commonly reported in studies of infants and young children, which primarily employ dynamic stimuli to maintain engagement of these younger participants, whereas studies of older children, adolescents, and adults with ASD tend to use more basic stimuli (e.g., fixation cross, LEDs). Second, at least two key aspects of gap-overlap tasks can be varied to decrease/increase the predictability of the target onset: (1) whether the central stimulus has a fixed or a variable duration and (2) whether trial types are blocked or randomized. In both cases, studies with more predicable stimulus sequences – central stimulus present for fixed duration and blocked trial type (e.g., all overlap trials presented together) – commonly report no group differences in disengagement, whereas evidence of impaired disengagement is more consistently found with unpredictable tasks. Furthermore, gap trials provide a predictable sequence of events: (1) fixation cross appears, (2) fixation cross is removed (fixed duration; e.g., 200 ms), and (3) peripheral target onset. Thus, disappearance of the central fixation in gap trials, regardless of study paradigm, always provides a fixed cue associated with the appearance of the target. Group differences in SRT are almost never present in the gap condition; rather, significantly larger gap effect scores in ASD (which are indicative of slower, less efficient disengagement) are the result of longer latencies to shift in overlap trials.
+
+Neural substrates of attentional disengagement. The network of brain regions responsible for orienting attention include the superior parietal lobes, intraparietal sulci, temporal-parietal junction (TPJ), and the frontal eye fields (FEF), as well as the thalamus and superior colliculus (SC) (Corbetta et al. 2008; Petersen and Posner 2012). In particular, the right TPJ may be a critical hub connecting both cortical (i.e., FEF) and subcortical (i.e., SC) brain regions (Bogadhi et al. 2019) and is thought to play a key role in disengaging and reorienting attention. Bryson et al. (1990) previously hypothesized that ASD could be characterized as a developmental spatial neglect syndrome (with acquired spatial neglect in adults generally associated with posterior right hemisphere brain lesions). More recently, these authors have shown asymmetrical disengagement deficits in high-risk infants. That is, consistent with their prediction of neglect-like patterns of behavior, infants later diagnosed with ASD showed atypically slowed left-directed SRT when the fixation stimulus remained on screen (i.e., overlap trials). This theory and associated empirical results are consistent with electrophysiological (e.g., Orekhova et al. 2009) and neuroimaging findings (e.g., Keehn et al. 2016) of atypical right hemisphere activation in individuals with ASD. However, the particular neural mechanism(s) underlying disengagement deficits in ASD remains unknown.
+
+Clinical significance. Early adaptive allocation of attention to one’s environment requires efficient attentional disengagement and shifting. Failure to respond to a caregiver’s name call or touch or the appearance of a novel object may result in fewer learning opportunities and affect the development of higher-level cognitive and social communication abilities. High-risk infants later diagnosed with ASD exhibit impairments in attentional disengagement compared both high- and low-risk infants that do not develop ASD. The presence of these early deficits in attentional disengagement has led some authors to hypothesize that they may be one of many factors that contribute to the emergence of the heterogeneous ASD phenotype (Keehn et al. 2013). Findings from prior research has demonstrated that disengagement efficiency in ASD is associated joint attention abilities (Schietecatte et al. 2011), recognition of spoken words (Venker 2017), and emotional distress (Bryson et al. 2018). For example, if infants and toddlers are unable to disengage and shift their attention during early dyadic interactions, then they may not follow a caregiver’s point (i.e., respond to joint attention bid) or direct their caregiver’s attention to a new item in their environment (i.e., to initiate joint attention). Thus, basic nonsocial attentional processes, such as attentional disengagement, may play a role in the development of core sociocommunicative impairments in ASD. These subsequent impairments (e.g., with joint attention) may have downstream consequences with word learning and language development and thus may alter developmental trajectories across a variety of domains.
+
+### Future Directions
+
+Identifying underlying mechanisms of impaired disengagement. Although strong evidence now exists for slower attentional disengagement in ASD, the mechanisms underlying these differences remain unclear. Elucidating the neurofunctional underpinnings associated with early disengagement impairments in ASD is a necessary next step to understand why this deficit emerges, how it may be used to accurately identify infants at risk, and how to more effectively target this skill in early intervention.
+Leveraging attentional disengagement for early diagnosis and intervention. If disengagement impairments are present early (within first year of life) and play a critical role in the development of ASD, then (1) disengagement deficits may be used as an early biobehavioral marker to identify infants at risk for ASD and (2) the development of attention-targeted early interventions may augment early disengagement skills and improve outcomes in children with ASD. Eye-tracking biomarkers for ASD risk that focus on preference for social compared to nonsocial stimuli have shown excellent specificity but poor sensitivity (Pierce et al. 2016). Similar research examining the utility of nonsocial attentional disengagement metrics for classifying ASD risk has not yet been published. Such research – especially in community-based high-risk samples – will assist the field in identifying whether attentional disengagement may be used a biobehavioral marker for ASD risk. Further, research examining the role of atypical attentional disengagement on the development of ASD symptoms will advance our understanding regarding the utility of early attention-targeted interventions. For example, if early disengagement difficulties result in delayed or impaired joint attention in ASD, then targeting these early attention skills may facilitate the acquisition of this pivotal skill (Forssman and Wass 2018) and potentially result in improved outcomes for children with ASD.
+
+### See Also
+
+*   Attention
+*   Joint Attention
+*   Selective Attention
+*   Orienting Response
+
+### References and Reading
+
+APA. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: American Psychological Association.
+Asperger, H. (1944). Die “Autistischen Psychopathen” im Kindesalter. Archiv für Psychiatrie und Nervenkrankheiten, 117(1), 76–136.
+Bogadhi, A. R., Bollimunta, A., Leopold, D. A., & Krauzlis, R. J. (2019). Spatial attention deficits are causally linked to an area in macaque temporal cortex. Current Biology, 29(5), 726–736 e724.
+Bryson, S. E., Wainwright-Sharp, J. A., & Smith, I. M. (1990). Autism: A developmental spatial neglect syndrome? In J. T. Enns (Ed.), The development of attention: Research and theory (pp. 405–427). Amsterdam: Elsevier North-Holland.
+Bryson, S. E., Garon, N., McMullen, T., Brian, J., Zwaigenbaum, L., Armstrong, V., . . . & Szatmari, P. (2018). Impaired disengagement of attention and its relationship to emotional distress in infants at high-risk for autism spectrum disorder. J Clin Exp Neuropsychol, 40(5), 487–501.
+Casey, B. J., Gordon, C. T., Mannheim, G. B., & Rumsey, J. M. (1993). Dysfunctional attention in autistic savants. Journal of Clinical and Experimental Neuropsychology, 15(6), 933–946.
+Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system of the human brain: From environment to theory of mind. Neuron, 58(3), 306–324.
+Elison, J. T., Paterson, S. J., Wolff, J. J., Reznick, J. S., Sasson, N. J., Gu, H., . . . Network, I. (2013). White matter microstructure and atypical visual orienting in 7-month-olds at risk for autism. Am J Psychiatry, 170(8), 899–908.
+Elsabbagh, M., Fernandes, J., Jane Webb, S., Dawson, G., Charman, T., & Johnson, M. H. (2013). Disengagement of visual attention in infancy is associated with emerging autism in toddlerhood. Biological Psychiatry, 74, 189–194.
+Fischer, J., Smith, H., Martinez-Pedraza, F., Carter, A. S., Kanwisher, N., & Kaldy, Z. (2016). Unimpaired attentional disengagement in toddlers with autism spectrum disorder. Developmental Science, 19(6), 1095–1103.
+Forssman, L., & Wass, S. V. (2018). Training basic visual attention leads to changes in responsiveness to social-communicative cues in 9-month-olds. Child Development, 89(3), e199–e213.
+Hermelin, B., & O’Connor, N. (1964). Effects of sensory input and sensory dominance on severely disturbed, autistic children and on subnormal controls. British Journal of Psychology, 55, 201–206.
+Hutt, C., Hutt, S. J., Lee, D., & Ounsted, C. (1964). Arousal and childhood autism. Nature, 204, 908–909.
+Kanner, L. (1943). Autistic disturbances of affective contact. The Nervous Child, 2, 217–250.
+Kawakubo, Y., Kasai, K., Okazaki, S., Hosokawa-Kakurai, M., Watanabe, K., Kuwabara, H., . . . & Maekawa, H. (2007). Electrophysiological abnormalities of spatial attention in adults with autism during the gap overlap task. Clinical Neurophysiology, 118(7), 1464–1471.
+Keehn, B., Muller, R. A., & Townsend, J. (2013). Atypical attentional networks and the emergence of autism. Neuroscience and Biobehavioral Reviews, 37(2), 164–183.
+Keehn, B., Nair, A., Lincoln, A. J., Townsend, J., & Muller, R. A. (2016). Under-reactive but easily distracted: An fMRI investigation of attentional capture in autism spectrum disorder. Developmental Cognitive Neuroscience, 17, 46–56.
+Keehn, B., Kadlaskar, G., McNally Keehn, R., & Francis, A. L. (2019). Auditory attentional disengagement in children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 49, 3999–4008.
+Kingstone, A., & Klein, R. M. (1993). Visual offsets facilitate saccadic latency: Does predisengagement of visuospatial attention mediate this gap effect? Journal of Experimental Psychology: Human Perception and Performance, 19(6), 1251–1265.
+Kleberg, J. L., Thorup, E., & Falck-Ytter, T. (2017). Reduced visual disengagement but intact phasic alerting in young children with autism. Autism Research, 10(3), 539–545.
+Landry, R., & Bryson, S. E. (2004). Impaired disengagement of attention in young children with autism. Journal of Child Psychology and Psychiatry, 45(6), 1115–1122.
+Lovaas, O. I., Schreibman, L., Koegel, R., & Rehm, R. (1971). Selective responding by autistic children to multiple sensory input. Journal of Abnormal Psychology, 77(3), 211–222.
+Orekhova, E. V., Stroganova, T. A., Prokofiev, A. O., Nygren, G., Gillberg, C., & Elam, M. (2009). The right hemisphere fails to respond to temporal novelty in autism: Evidence from an ERP study. Clinical Neurophysiology, 120(3), 520–529.
+Petersen, S. E., & Posner, M. I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89.
+Pierce, K., Marinero, S., Hazin, R., McKenna, B., Barnes, C. C., & Malige, A. (2016). Eye tracking reveals abnormal visual preference for geometric images as an early biomarker of an autism spectrum disorder subtype associated with increased symptom severity. Biological Psychiatry, 79(8), 657–666.
+Posner, M. I. (1980). Orienting of attention. The Quarterly Journal of Experimental Psychology, 32(1), 3–25.
+Posner, M. I., Cohen, Y., & Rafal, R. D. (1982). Neural systems control of spatial orienting. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 298(1089), 187–198.
+Posner, M. I., Walker, J. A., Friedrich, F. J., & Rafal, R. D. (1984). Effects of parietal injury on covert orienting of attention. Journal of Neuroscience, 4(7), 1863–1874.
+Sabatos-DeVito, M., Schipul, S. E., Bulluck, J. C., Belger, A., & Baranek, G. T. (2016). Eye tracking reveals impaired attentional disengagement associated with sensory response patterns in children with autism. Journal of Autism and Developmental Disorders, 46(4), 1319–1333.
+Sacrey, L. A., Armstrong, V. L., Bryson, S. E., & Zwaigenbaum, L. (2014). Impairments to visual disengagement in autism spectrum disorder: A review of experimental studies from infancy to adulthood. Neuroscience and Biobehavioral Reviews, 47, 559–577.
+Saslow, M. G. (1967). Effects of components of displacement-step stimuli upon latency for saccadic eye movement. Journal of the Optical Society of America, 57(8), 1024–1029.
+Schietecatte, I., Roeyers, H., & Warreyn, P. (2011). Exploring the nature of joint attention impairments in young children with autism spectrum disorder: Associated social and cognitive skills. Journal of Autism and Developmental Disorders, 42(1), 1–12.
+Schmitt, L. M., Cook, E. H., Sweeney, J. A., & Mosconi, M. W. (2014). Saccadic eye movement abnormalities in autism spectrum disorder indicate dysfunctions in cerebellum and brainstem. Molecular Autism, 5(1), 47.
+Townsend, J., Harris, N. S., & Courchesne, E. (1996). Visual attention abnormalities in autism: Delayed orienting to location. Journal of the International Neuropsychological Society, 2(6), 541–550.
+van der Geest, J. N., Kemner, C., Camfferman, G., Verbaten, M. N., & van Engeland, H. (2001). Eye movements, visual attention, and autism: A saccadic reaction time study using the gap and overlap paradigm. Biological Psychiatry, 50(8), 614–619.
+Venker, C. E. (2017). Spoken word recognition in children with autism spectrum disorder: The role of visual disengagement. Autism, 21(7), 821–829.
+Wainwright-Sharp, J. A., & Bryson, S. E. (1993). Visual orienting deficits in high-functioning people with autism. Journal of Autism and Developmental Disorders, 23(1), 1–13.
+Zalla, T., Seassau, M., Cazalis, F., Gras, D., & Leboyer, M. (2018). Saccadic eye movements in adults with high-functioning autism spectrum disorder. Autism, 22(2), 195–204.
+
+## Attributions (First Order/Second Order)
+
+### Synonyms
+
+Attribution of mental states
+
+### Definition
+
+Attribution is a concept in psychology referring to people’s tendency to attribute traits and causes to help explain what they observe. First- and second-order attributions refer more specifically to the attribution of mental states to self or others to explain and predict observable behavior (see ▶“Theory of Mind”). Attribution of mental states, such as beliefs and desires, has been widely studied in false belief paradigms (Frith and Frith 2010). First-order mental state attribution tasks require the participant to represent another person’s thoughts about the world, e.g., Sally thinks the ball is in the basket. Second-order tasks require representation of one person’s belief about another person’s mental state, e.g., Sally thinks Ann knows the ball is in the box. An everyday life example of attribution of mental states would be when we understand whether someone is telling a joke or telling a lie: we attribute to the liar, but not to the joker, the intension to make us believe what he or she says. Several tests exist for assessing the ability to attribute mental states (e.g., Happé 1994; White et al. 2009).
+A large body of research has demonstrated that most children and many adults with ASD find it difficult to make mental state attributions, especially attributing to another person a state of knowledge that is different from their own or from reality (Baron-Cohen et al. 2000). This may underlie a range of social and communicative symptoms in ASD, such as overliteral language use/understanding, difficulty adapting conversation to listeners’ interests/knowledge, and difficulty understanding deception. An interesting question in recent research (e.g., Williams and Happé 2009) is whether some people with ASD may have difficulty attributing mental states to self, with implications for self-awareness and the ability to reflect upon one’s own thoughts and feelings. Attribution of mental states has become a key task for use during functional neuroimaging investigations of brain differences in ASD. A range of different tasks suggest key regions including the medial prefrontal cortex are less activated in people with ASD compared to controls when attributing thoughts (in response to, e.g., animated shapes, story vignettes; Frith and Frith 2010).
+
+### See Also
+
+*   Theory of Mind
+
+### References and Reading
+
+Baron-Cohen, S., Tager-Flusberg, H., & Cohen, D. J. (Eds.). (2000). Understanding other minds. Oxford: Oxford University Press.
+Frith, U., & Frith, C. (2010). The social brain: Allowing humans to boldly go where no other species has been. Philosophical Transactions of the Royal Society B, 365, 165–176.
+Happé, F. G. E. (1994). An advanced test of theory of mind: Understanding of story characters’ thoughts and feelings by able autistic, mentally handicapped and normal children and adults. Journal of Autism and Developmental Disorders, 24, 129–154.
+White, S. J., Hill, E., Happé, F., & Frith, U. (2009). Revisiting the Strange Stories: revealing mentalising impairments in autism. Child Development, 80, 1097–1117.
+White, S. J., Coniston, D., Rogers, R., & Frith, U. (2011). Developing the Frith-Happé animations: A quick and objective test of theory of mind for adults with autism. Autism Research, 4, 149–154.
+Williams, D., & Happé, F. (2009). What did I say? Versus what did I think? Attributing false beliefs to self amongst children with and without autism. Journal of Autism and Developmental Disorders, 39(6), 865–873.
+
+## Atypical Antipsychotics
+
+### Synonyms
+
+Novel antipsychotics; Second-generation antipsychotics (SGAs)
+
+### Indications
+
+#### Aripiprazole (Abilify)
+
+Schizophrenia in adults and pediatric patients (age 13–17 years); Acute manic or mixed episodes of bipolar I disorder in adults and pediatric patients (age 10–17 years), alone or as an adjunct to lithium or valproate; Major depressive disorder in adults (adjunctive treatment); Agitation associated with schizophrenia or manic or mixed episodes of bipolar I disorder (adults).
+
+#### Clozapine (Clozaril)
+
+Acute schizophrenia; Acute schizoaffective disorder; Treatment-refractory schizophrenia; Maintenance therapy in schizophrenia; Manic episodes of bipolar disorder; Depression with psychotic features.
+
+#### Olanzapine (Zyprexa)
+
+Schizophrenia in adults and pediatric patients (age 13–17 years); Acute manic or mixed episodes of bipolar I disorder in adults and pediatric patients (age 13–17 years), alone or as an adjunct to lithium or valproate; Acute agitation in schizophrenia and mania in bipolar I disorder; in combination with fluoxetine for depressive episodes associated with bipolar I disorder in adults; in combination with fluoxetine for treatment-resistant depression (adults).
+
+#### Olanzapine and Fluoxetine Hydrochloride (Symbyax)
+
+Acute depressive episodes of bipolar I disorder in adults; Treatment-resistant depression in adults.
+
+#### Paliperidone (Invega)
+
+Schizophrenia; Acute treatment of schizoaffective disorder, alone or as an adjunct to mood stabilizers and/or antidepressants.
+
+#### Quetiapine (Seroquel)
+
+Schizophrenia, including global symptoms, positive symptoms, negative symptoms, cognition, and aggression; Bipolar disorder (adults); Major depressive disorder in adults (adjunctive treatment).
+
+#### Risperidone (Risperdal)
+
+Schizophrenia in adults and pediatric patients (age 13–17 years); Acute manic or mixed episodes of bipolar I disorder in adults, alone or as an adjunct to lithium or valproate; Acute manic or mixed episodes of bipolar I disorder in pediatric patients (age 10–17 years); Irritability associated with autistic disorder in pediatric patients (age 5–16 years).
+
+#### Ziprasidone Hydrochloride (Geodon) and Ziprasidone Mesylate (Geodon)
+
+Schizophrenia in adults; Acute manic or mixed episodes of bipolar I disorder in adults, alone or as an adjunct to lithium or valproate; Acute agitation of schizophrenia in adults
+
+### Mechanisms of Action
+
+When considering mechanisms of action of antipsychotics, it is important to note that the pathophysiologies of psychiatric conditions treated by these drugs (i.e., schizophrenia, bipolar disorder, and autism) are unknown; therefore, the precise mechanisms of action of the atypical antipsychotics are unknown.
+
+#### Aripiprazole
+
+Aripiprazole is a dopamine type 2 (D2) receptor partial agonist, not a full antagonist like the other atypical antipsychotics. This drug acts as a D2 receptor antagonist when coadministered with a dopamine (DA) agonist but acts as a D2 receptor agonist when administered without another DA agonist. Aripiprazole acts as an antagonist in overactive DA pathways and an agonist in underactive DA pathways. This drug’s antagonist activity at serotonin type 2A (5-HT2A) receptors may cause reductions in extrapyramidal symptoms (EPS) and improve the negative symptoms of schizophrenia, and its partial agonist activity at serotonin type 1A (5-HT1A) may cause improvement in the negative and cognitive symptoms of schizophrenia, depression, and anxiety.
+
+#### Clozapine
+
+Clozapine exhibits low affinity for and quick dissociation from dopamine type 2 (D2) receptors and high affinity for the serotonin type 2A (5-HT2A) and serotonin type 1C (5-HT1C) receptors, adrenergic receptors, cholinergic receptors, and dopamine type 4 (D4) receptors, mainly in the extrastriatal cortex as compared to the striatal cortex. This drug also increases the release of dopamine (DA) in the prefrontal cortex. This effect of the drug may alleviate the negative symptoms and cognitive deficits of schizophrenia since these two aspects of the disorder may result from dopaminergic hypoactivity in the prefrontal cortex.
+
+#### Olanzapine
+
+Olanzapine has high relative serotonin type 2A (5-HT2A) receptor blocking activity compared to that of dopaminergic (DA) receptors. This drug increases expression of c-fos in the caudate nucleus and increases serum glutamate levels. Also, olanzapine increases brain glutamate levels in patients who exhibit improvement in the negative symptoms of schizophrenia.
+
+#### Paliperidone
+
+Paliperidone is a dopamine type 2 (D2), serotonin type 2A (5-HT2A), α1- and α2-adrenergic, and histaminergic 1 (H1) receptor antagonist. This drug is expected to have a mechanism very similar to that of risperidone since it is the major active metabolite of that drug, although patients have been reported to have responded positively to paliperidone after failing to respond to an adequate trial of risperidone.
+
+#### Quetiapine
+
+Quetiapine exhibits a high relative blockade of serotonin type 2A (5-HT2A), serotonin type 2B (5-HT2B), and serotonin type 2C (5-HT2C) receptors compared to that of dopamine (DA) receptors. This drug exhibits a greater degree of binding in the extrastriatal cortex than in the striatal cortex. Quetiapine has partial agonist activity at 5-HT2A which causes an increased DA level in the mesocortical DA pathway in individuals in which this pathway is hypoactive, thereby causing improvement in the negative and cognitive symptoms of schizophrenia. Also, this compound exhibits brief, high occupancy of dopamine type 2 (D2) receptors for 2–3 h after dose administration in patients who exhibit improvement in psychosis, extrapyramidal symptoms (EPS), and prolactin. Imaging studies show that this drug has means of 74% 5-HT2A receptor binding and 30% D2 receptor binding for 450 mg/day dosing and means of 76% 5-HT2A receptor binding and 41% D2 receptor binding for 750 mg/day dosing.
+
+#### Risperidone
+
+Risperidone acts as an antagonist at the serotonin type 2A (5-HT2A), dopamine type 2 (D2), α1- and α2-adrenergic, and histaminergic 1 (H1) receptors. Selective 5-HT2A antagonists block amphetamine- and phencyclidine-induced locomotor activity and thereby may improve symptoms of psychosis. Also, the dizocilpine-induced disruption of prepulse inhibition of 5-HT2A antagonists may improve sensory gating deficits in schizophrenia which may be caused by glutamatergic dysregulation. The α-adrenergic antagonist activity may cause an increase in dopamine (DA) levels in the medial prefrontal cortex which may improve negative symptoms and cognition in schizophrenia. Dopaminergic hypoactivity in the prefrontal cortex is a potential cause of negative symptoms and cognitive deficits in schizophrenia. The α-adrenergic antagonist activity of this drug also may reduce the risk for the development of extrapyramidal symptoms (EPS) and improve cognition in individuals with frontal dementias. When taken with haloperidol, the selective serotonin type 2 (5-HT2) antagonism reduces neuroleptic-induced parkinsonism and akathisia by increasing DA metabolism in the striatum and preventing an increase in D2 receptor density which causes a decrease in the effects of D2 receptor blockade and DA supersensitivity.
+
+#### Ziprasidone
+
+The antipsychotic effects of ziprasidone may be due to the affinity of this drug for dopamine type 2 (D2) receptors in the striatum and its strong antagonism for serotonin type 2A (5-HT2A) receptors. The 5-HT2A receptor antagonism of this drug and its strong serotonin type 1A (5-HT1A) receptor agonism may improve the negative and cognitive symptoms of schizophrenia by facilitating the release of dopamine (DA) in the prefrontal cortex.
+
+### Specific Compounds and Properties
+
+The specific compounds currently marketed in the United States that act as atypical antipsychotics are aripiprazole, clozapine, olanzapine, paliperidone, risperidone, ziprasidone, and quetiapine. The unique chemical structure of each atypical antipsychotic accounts for its binding activity as detailed in the “Mechanisms of Action” section of this entry. The chemical structures of these compounds are pictured in Figs. 1, 2, 3, 4, 5, 6, and 7 (Note: image figures are not provided in the input, so they cannot be reproduced).
+
+### Clinical Use (Including Side Effects)
+
+#### Aripiprazole
+
+Aripiprazole is used in autistic disorder to improve symptoms of aggression, irritability, and self-injurious behavior. Doses used in studies range from 2.5 to 15 milligrams per day (mg/day). Side effects of aripiprazole include nausea, weight gain, akathisia, headache, insomnia, agitation, anxiety, and mild transient somnolence.
+
+#### Clozapine
+
+Clozapine is used in autism spectrum disorders (ASDs) to improve symptoms of aggression. Doses of 276 mg/day in an adolescent and 283.33 mg/day in children have been used to treat ASDs. Side effects of clozapine include a very high risk of sedation; a high risk of anticholinergic effects, sialorrhea, orthostasis, and weight gain; a moderate risk of seizures and hematologic effects; a low risk of increased liver enzyme levels; and a very low risk of extrapyramidal symptoms (EPS) and neuroleptic malignant syndrome (NMS).
+
+#### Olanzapine
+
+Olanzapine is used in autism spectrum disorders for global improvement of severe behavioral symptoms, overall symptoms of autism, motor restlessness/hyperactivity, social relatedness, affectual relations, sensory responses, language use, self-injurious behaviors, aggression, irritability, anxiety, and depression. The dose for this drug may be between 5 and 20 mg/day and is used in children, adolescents, and adults. Side effects of olanzapine include sedation and weight gain. Also, this drug has a moderate risk of orthostasis and anticholinergic effects; a low, dose-dependent risk of EPS; a low risk of increased liver enzyme levels; and a very low risk of TD, seizures, and hematologic effects.
+
+#### Paliperidone
+
+Paliperidone has been used in autism spectrum disorders to improve symptoms of irritability, including aggression, self-injurious behaviors, and tantrums. Doses of 6–12 mg/day have been used in adolescents with autism. Side effects of paliperidone include orthostatic hypotension, weight gain, weight loss, and sedation.
+
+#### Quetiapine
+
+Quetiapine is used in autism spectrums disorders (ASDs) to improve symptoms of aggression, hyperactivity, and inattention. Doses used in studies of quetiapine for use in the treatment of ASDs include means of 225 mg/day and 477 mg/day in children and adolescents; a mean of 292 mg/day in adolescents; and a mean of 249 mg/day in a group of children, adolescents, and adults. Side effects of quetiapine include agitation, sedation, weight gain, aggression, and sialorrhea. Also, this drug has a low risk of anticholinergic effects, orthostasis, and increased liver enzyme levels and a very low risk of EPS, NMS, seizures, and hematologic effects.
+
+#### Risperidone
+
+Risperidone is used in autistic disorder to improve symptoms of aggression, irritability, repetitive behavior and language, hyperactivity, social withdrawal, nonverbal communication, and social responsiveness. An effective dose for children with pervasive developmental disorder (PDD) may range from 1 to 1.2 mg/day, whereas an effective dose for children with autism may be 1.8 mg/day. An effective dose for adults with autism may be 2.9 mg/day. Side effects of risperidone include sedation, increased prolactin, weight gain, and hypersalivation. Also, this drug has a high risk for orthostasis; a moderate, dose-dependent risk of EPS; and a very low risk of tardive dyskinesia (TD), NMS, anticholinergic effects, seizures, hematologic effects, and elevated liver enzyme levels.
+
+#### Ziprasidone
+
+Ziprasidone is used in autism spectrum disorders to improve symptoms of aggression, irritability, and agitation. A dose used in studies of ziprasidone for use in the treatment of ASDs includes a mean of 59 mg/day in children and adolescents. Side effects of ziprasidone include sedation and mild weight gain. Also, this drug has a low risk of orthostasis and increased liver enzyme levels and a very low risk of EPS, anticholinergic effects, seizures, and hematologic effects.
+
+### References and Reading
+
+Barnard, L., Young, A. H., Pearson, J., Geddes, J., & O’Brien, G. (2002). A systematic review of the use of atypical antipsychotics in autism. Journal of Psychopharmacology, 16, 93–101.
+Biederman, J., Spencer, R., & Wilens, T. (2004). Psychopharmacology. In J. M. Wiener & M. K. Dulcan (Eds.), The American psychiatric publishing textbook of child and adolescent psychiatry (3rd ed., pp. 931–973). Washington, DC: American Psychiatric Publishing.
+Brown, C. S., Markowitz, J. S., Moore, T. R., & Parker, N. G. (1999). Atypical antipsychotics: Part II: Adverse effects, drug interactions, and costs. The Annals of Pharmacotherapy, 33, 210–217.
+Chen, N. C., Bedair, H. S., McKay, B., Bowers, M. B., Jr., & Mazure, C. (2001). Clozapine in the treatment of aggression in an adolescent with autistic disorder. The Journal of Clinical Psychiatry, 62, 479–480.
+Citrome, L. (2010). Paliperidone palmitate – Review of the efficacy, safety and cost of a new second-generation depot antipsychotic medication. International Journal of Clinical Practice, 64, 216–239.
+Daniel, D. G., Copeland, L. F., & Tamminga, C. (2006). Ziprasidone. In A. F. Schatzberg & C. B. Nemeroff (Eds.), Essentials of clinical psychopharmacology (2nd ed., pp. 297–305). Washington, DC: American Psychiatric Publishing.
+Goff, D. C. (2006). Risperidone. In A. F. Schatzberg & C. B. Nemeroff (Eds.), Essentials of clinical psychopharmacology (2nd ed., pp. 285–295). Washington, DC: American Psychiatric Publishing.
+Marder, S. R., & Wirshing, D. A. (2006). Clozapine. In A. F. Schatzberg & C. B. Nemeroff (Eds.), Essentials of clinical psychopharmacology (2nd ed., pp. 229–243). Washington, DC: American Psychiatric Publishing.
+Martinez, M., Marangell, L. B., & Martinez, J. M. (2011). Psychopharmacology. In R. E. Hales, S. C. Yudofsky, & G. O. Gabbard (Eds.), Essentials of psychiatry (3rd ed., pp. 455–524). Washington, DC: American Psychiatric Publishing, Inc..
+Miyamoto, S., Duncan, G. E., Marx, C. E., & Lieberman, J. A. (2005). Treatments for schizophrenia: A critical review of pharmacology and mechanisms of action of antipsychotic drugs. Molecular Psychiatry, 10, 79–104.
+Posey, D. J., Stigler, K. A., Erickson, C. A., & McDougle, C. J. (2008). Antipsychotics in the treatment of autism. Science in Medicine, 118, 6–14.
+Printz, D. J., & Lieberman, J. A. (2006a). Aripiprazole. In A. F. Schatzberg & C. B. Nemeroff (Eds.), Essentials of clinical psychopharmacology (2nd ed., pp. 277–283). Washington, DC: American Psychiatric Publishing.
+Printz, D. J., & Lieberman, J. A. (2006b). Quetiapine. In A. F. Schatzberg & C. B. Nemeroff (Eds.), Essentials of clinical psychopharmacology (2nd ed., pp. 263–275). Washington, DC: American Psychiatric Publishing.
+Schatzberg, A. F., Cole, J. O., & DeBattista, C. (2003). Antipsychotic drugs. In Manual of clinical psychopharmacology (4th ed., pp. 159–243). Washington, DC: American Psychiatric Publishing.
+Schultz, S. C., Olson, S., & Kotlyar, M. (2006). Olanzapine. In A. F. Schatzberg & C. B. Nemeroff (Eds.), Essentials of clinical psychopharmacology (2nd ed., pp. 245–275). Washington, DC: American Psychiatric Publishing.
+Stigler, K. A., Erickson, C. A., Mullet, J. E., Posey, D. J., & McDougle, C. J. (2010). Paliperidone for irritability in autistic disorder. Journal of Child and Adolescent Psychopharmacology, 20, 75–78.
+Tsai, L. Y. (2004). Autistic disorder. In J. M. Wiener & M. K. Dulcan (Eds.), The American psychiatric publishing textbook of child and adolescent psychiatry (3rd ed., pp. 261–260). Washington, DC: American Psychiatric Publishing.
+U.S. Food and Drug Administration. (2010a). Atypical antipsychotics drug information. Retrieved from http://www.fda.gov/Drugs/DrugSafety/Post marketDrugSafetyInformationforPatientsand Providers/ucm094303.htm
+U.S. Food and Drug Administration. (2010b). Drugs@FDA. Retrieved from http://www.accessdata. fda.gov/scripts/cder/drugsatfda/index.cfm
+
+## Atypical Autism
+
+### Short Description or Definition
+
+Atypical autism is often described as a subthreshold diagnosis, presenting with some symptoms of autism but insufficient to meet criteria for a diagnosis of childhood autism (or autistic disorder). Alternatively, atypical autism can be diagnosed when there is a late onset of symptomatology. Atypical autism (as defined by ICD-10) is seen as being equivalent to the DSM-IV-TR diagnostic category of pervasive developmental disorder not otherwise specified (PDD NOS). DSM-5 does not have a separate diagnostic category for PDD NOS.
+Like PDD NOS, atypical autism is poorly defined, resulting in a research literature that can be difficult to interpret and conclusions difficult to reach. Atypical autism, as defined by the ICD, lacks operationalized diagnostic criteria, resulting in inconsistencies and variability in the way in which the diagnosis is applied. Although it now appears to be more common than autistic disorder, in general it remains poorly understood. This is likely due, in no small part, to the lack of a clear definition. Although it is often assumed that findings relating to autism apply to atypical autism, the lack of operationalized diagnostic criteria has undoubtedly hampered specific research into this diagnostic category and contributed to inconsistent findings across studies. Studies often fail to describe how they operationalized or defined their samples of atypical autism or PDD NOS. The ICD-10 provides specifiers to further define the diagnosis of atypical autism (see section “Categorization”); however, studies generally do not use these specifiers. Difficulties therefore remain in interpreting and comparing findings across studies. The broadening of the PDD NOS category in DSM-IV (Volkmar et al. 2000) has also contributed to difficulties in interpretability of results across studies, although with DSM-IV-TR (American Psychiatric Association 2000) this was remedied. Further definition of atypical autism or PDD NOS in research (see, e.g., Mandy et al. (2011)) would assist with furthering knowledge in this area. This entry will focus on research studies involving individuals with atypical autism. Where necessary, this is supplemented with research findings from samples with PDD NOS.
+
+### Categorization
+
+The category of pervasive developmental disorder (PDD) was introduced in DSM-III (American Psychiatric Association 1980) and included the subthreshold diagnosis of atypical PDD, which subsequently became pervasive developmental not otherwise specified (PDD NOS) in DSM-III-R (American Psychiatric Association 1987). Reflecting thinking at the time, ICD-9 categorized autism (299.0 Infantile Autism) under the category of childhood psychoses and included a code for other specified early childhood psychoses, including atypical childhood psychosis (299.8) (World Health Organisation 1978). With the revision of these classification systems to the DSM-IV (American Psychiatric Association 2000) and ICD-10 (World Health Organisation 1992), the systems shared a common approach to coding and were seen as conceptually the same (Volkmar 1998).
+The ICD-10 (World Health Organisation 1992) provides diagnostic criteria for atypical autism (F84.1) under the category of pervasive developmental disorders. The diagnosis is for cases where age of onset is after the age of three (criteria the same for childhood autism except for age of onset), or all three sets of criteria for childhood autism are not met (subthreshold). Criteria in the domains of abnormalities in reciprocal social interaction, or communication, or restricted, repetitive, and stereotyped patterns of behavior, interests, and activities are the same as for childhood autism except that it is not necessary to meet the criteria for number of areas of abnormality. Specifiers can then be used to indicate atypicality in age of onset (F84.10), atypicality in symptomatology (F84.11), or atypicality in both age of onset and symptomatology (F84.12). The DSM-IV (American Psychiatric Association 2000) defines PDD NOS as including atypical autism. The ICD-10 also has two additional diagnoses, namely, other pervasive developmental disorder (F84.8, with no diagnostic criteria specified) and pervasive developmental disorder, unspecified (F84.9). The latter disorder is defined as a residual category for cases where there is a lack of information or contradictory findings, but where symptomatology fits the general description for a pervasive developmental disorder. The ICD-10 diagnoses of atypical autism, other pervasive developmental disorder, and pervasive developmental disorder, unspecified are considered to be broadly equivalent to the DSM-IV-TR (American Psychiatric Association 2000) diagnosis of PDD NOS.
+In the current DSM (DSM-5; American Psychiatric Association 2013), the category of PDD NOS has been subsumed under autistic spectrum disorder, with the instruction to give the DSM-5 diagnosis of autism spectrum disorder to those with a well-established diagnosis of PDD NOS. Concerns have been raised regarding whether children and adolescents with DSM-IV diagnoses of PDD NOS or ICD-10 diagnoses of atypical autism would meet the DSM-5 diagnostic criteria for autism spectrum disorder. Using draft criteria, a number of studies reported concerningly low rates (3–28.3%) of cases of PDD NOS/atypical autism meeting the DSM-5 criteria for autism spectrum disorder (Barton et al. 2013; Mandy et al. 2011; Mayes et al. 2013; McPartland et al. 2012). Kim et al. (2014) reported a higher rate (63%) and Huerta and colleagues found that the DSM-5 diagnostic criteria resulted in improved specificity compared to the DSM-IV criteria for PDD NOS (Huerta et al. 2012). It has been speculated that children without repetitive, restricted, or stereotyped behaviors previously diagnosed with PDD NOS may meet the diagnostic criteria for the new DSM-5 Social Communication Disorder category (Ozonoff 2012; Skuse 2012). Prospective research studies using the DSM-5 diagnostic criteria are needed to explore these issues. Draft guidelines for ICD-11 (due for release in 2018), mirror the DSM-5, subsuming atypical autism into the single diagnostic category of autism spectrum disorder (WHO, GCP Network 2017).
+
+### Epidemiology
+
+Atypical autism is rarely the focus of prevalence studies, and differing labels and combining of groups other than autistic disorder can make the extraction and interpretation of prevalence figures difficult. A number of population and birth cohort studies have included figures on the prevalence of atypical autism. The UK-based studies in children have reported differing prevalence figures of 10.5/10,000 (Lingam et al. 2003), 10.9/10,000 (Williams et al. 2008), and 27/10,000 (Baird et al. 2000), while a birth cohort study (6-year-olds) in Stockholm reported a prevalence of 22/10,000 (Fernell and Gillberg 2010). A study in the Faroe Islands (considered a genetic isolate) reported a population prevalence of atypical autism of 0.12%, while acknowledging that this is possibly an underestimate particularly in terms of higher functioning children (Ellefsen et al. 2007). A Danish population study reported separate prevalence rates for atypical autism (3.3/10,000) and PDD NOS (14.6/10,000), which when taken together are similar to those rates reported by Fernell and Gillberg (2010) and Baird et al. (2000). A South Korean study provided a prevalence estimate of 1% for PDD NOS (Kim et al. 2011). Using data from the national Danish register, reported rates of Gender ratios have been reported by a very small number of studies, with a higher proportion of males with autistic disorder compared to atypical autism, 6.5:1 compared to 3.8:1 in Stockholm (Fernell and Gillberg 2010), and no reported gender differences between PDD NOS (85.3% male) and autistic disorder (85.9% male) in a birth cohort of 4–6-year-olds in Stafford in the UK (Chakrabarti and Fombonne 2005).
+A series of review studies by Fombonne, most recently in 2009, reviewed 43 prevalence surveys, 17 of which provided separate estimates of the prevalence of atypical autistic syndromes (PDD NOS and atypical autism) (Fombonne 2009). Fourteen of these studies reported a higher prevalence of atypical autism syndromes compared to autistic disorder, 37.1/10,000 and 20.6/10,000 respectively. Like the prevalence of autism, the reported prevalence of atypical autism has increased over time. Similarly, this increase is typically discussed in relation to changes in diagnostic criteria, increased awareness, diagnostic substitution, changes in special education policies, and increases in the availability of services. What is, however, clear from these studies is that there is a significantly large population of children with atypical autism who have treatment needs similar to those of children with autism.
+
+### Natural History, Prognostic Factors, and Outcomes
+
+A small number of studies have investigated the early signs and symptoms in children later diagnosed with atypical autism, with mixed results. One study looked at first symptoms and diagnosis in children with atypical autism, comparing the parent-reported onset of symptomatology to that of children diagnosed with childhood autism (Oslejskova et al. 2007). Significant group differences were found in age of first symptoms, with parents of children with atypical autism reporting first symptoms at an average of 36.7 months (compared to 23.5 months for children with childhood autism). There were however no significant group differences in age at diagnosis. In contrast, Walker et al. reported no difference between autism and PDD NOS in terms of age at which abnormalities were first identified by parents (2004). Two epidemiological studies found that atypical autism was diagnosed later than childhood autism, with atypical autism generally diagnosed at 5–6 years of age and childhood autism at 3–4 years (Fernell and Gillberg 2010; Lingam et al. 2003).
+Research has demonstrated that outcome in autism and other pervasive developmental disorders is associated with the acquisition of expressive language skills by the age of 5–6 years, cognitive ability, and early social-communicative skills (Gillberg and Steffenburg 1987; Kobayashi et al. 1992; Mundy et al. 1990; Nordin and Gillberg 1998; Sigman and Ruskin 1999). Longitudinal studies have reported that initial diagnosis (i.e., atypical autism or PDD NOS compared to autistic disorder) is not related to outcomes (Baghdadli et al. 2007; Turner et al. 2006) and therefore has limited use in predicting developmental outcomes. However, Moulton et al. (2016) reported that a diagnosis of PDD NOS at age 2 was associated with better outcomes at age 4 relative to those children with a diagnosis of autistic disorder, likely due to lower rates of autism symptomatology, particularly restricted and repetitive behaviors.
+
+### Clinical Expression and Pathophysiology
+
+The reliability and stability of the diagnoses of atypical autism and PDD NOS has been questioned. In a study of subtypes of pervasive developmental disorders in children, Mahoney et al. (1998) reported interrater agreement for diagnoses of Asperger’s disorder, autism, and atypical autism across three raters. Kappa values revealed good agreement for the diagnosis of autism (0.55), Asperger’s disorder (0.56), and non-PDD (0.67), but poor agreement in the case of atypical autism (0.18). Consistent with the results of studies in children with atypical autism, research in toddlers with autism and PDD NOS has reported good agreement between clinicians on the diagnosis of autism, but low rates of agreement for PDD NOS (Chawarska et al. 2007; Stone et al. 1999).
+In relation to diagnostic stability, research has focused on individuals with PDD NOS. While diagnoses of autistic disorder have been shown to be relatively stable in toddlers, the same is not true of PDD NOS (Chawarska et al. 2007; Stone et al. 1999; Turner et al. 2006; van Daalen et al. 2009). A meta-analysis of the diagnostic stability of PDD NOS reviewed eight studies, reporting higher rates of stability for a diagnosis of autistic disorder compared to PDD NOS (Rondeau et al. 2010). It was concluded that a diagnosis of PDD NOS prior to 36 months was unstable (35% stability) over time, highlighting the need for reassessment. It has been suggested that low diagnostic stability may be attributable to the later emergence of stereotyped and repetitive behaviors in young children (Kleinman et al. 2008; Sutera et al. 2007).
+The lack of operationalized diagnostic criteria for atypical autism and the variability in which the diagnosis is applied have possibly resulted in a significant amount of heterogeneity in the presentation of individuals; as such, there is as yet no consensus regarding the symptom profile for atypical autism or PDD NOS (Mandy et al. 2011). Two studies have examined symptom profiles in children with atypical autism, focusing on high-functioning children with atypical autism, Asperger’s disorder, and childhood autism (Kanai et al. 2004; Kurita 1997). In a comparison of children with high-functioning atypical autism and childhood autism, symptom patterns were examined using the Childhood Autism Rating Scale (CARS) (Kurita et al. 1989), rated by clinicians blind to the child’s diagnosis. The children with atypical autism scored significantly lower on the CARS total score. There were no significant group differences on 11 of the 15 CARS items. After controlling for IQ and total CARS score, the children with atypical autism were found to be significantly less impaired on two items of the CARS (relationships with people and general impressions) and were more impaired in anxiety reaction compared to the children with childhood autism. In a comparison of high- functioning atypical autism and Asperger’s disorder, the Asperger’s disorder group was significantly less impaired than the atypical autism group on total CARS score, imitation, visual responsiveness, auditory responsiveness, and nonverbal communication (Kurita 1997). Overall, these findings are consistent with the idea of atypical autism being a subthreshold diagnosis for children with a significant degree of impairment, but not to the degree that criteria for childhood autism are met.
+Further information on symptom presentation comes from studies with children with a diagnosis of PDD NOS. Consistent with the results of the studies with children with atypical autism, a number have reported generally finding children with PDD NOS to have significantly less impairment in the social, communication, and restricted and repetitive symptom domains compared to children with autistic disorder (Fodstad et al. 2009; Walker et al. 2004). de Bruin et al. (2006) reported that children with PDD NOS have similar cognitive profiles as children with autism, although in contrast Walker et al. (2004) found that children with PDD NOS scored better than children with autism on measures of adaptive behavior and nonverbal reasoning and problem-solving skills. An investigation of communication impairments using the Children’s Communication Checklist (Bishop 1998) with children with high-functioning autism, Asperger’s disorder, and PDD NOS found that while all groups demonstrated significantly more impairment than the typically developing control group, there was little difference across the autism subtypes. In a comprehensive study, Mandy et al. (2011) operationalized the definition of PDD NOS and compared the symptom profiles of children with autistic disorder, Asperger’s disorder, and PDD NOS on independent measures of symptomatology. They found that the overwhelming majority (97%) of children with PDD NOS presented with a symptom profile characterized by significant impairment in social interaction and communication skills without repetitive stereotyped behavior. The remaining children presented with a symptom pattern of significant social impairment and repetitive stereotyped behavior without communication impairment. These results are inconsistent with the view of PDD NOS being a condition with marked heterogeneity. The children with PDD NOS demonstrated significantly less routinized and repetitive behaviors, sensory difficulties, feeding, and visuospatial problems compared to the children with autistic disorder and Asperger’s disorder. With PDD NOS now subsumed under the DSM-5 diagnostic category of autism spectrum disorder (ASD), it may be that individuals presenting with marked impairments in social interaction and communication, without repetitive stereotyped behavior, will not meet the DSM-5 diagnostic criteria for ASD.
+High rates of comorbid mental health problems have been reported in atypical autism and PDD NOS.ADanishstudycomparedasampleof89individuals diagnosed as children with atypical autism to a matched control sample from the general population (Mouridsen et al. 2008). Using the Danish Psychiatric Register, they demonstrated that over a 36-year follow-up period, elevated rates of co-occurring psychiatric diagnoses were found in those with atypical autism. The most prevalent of these was schizophrenia spectrum disorder. High levels of depression, anxiety, and disruptive behavior disorder have been reported in children with PDD NOS (de Bruin et al. 2007; Pearson et al. 2006), highlighting the importance of considering comorbid mental health problems when conducting diagnostic assessments for atypical autism. It has been reported that while comorbid medical conditions in autism are associated with degree of intellectual disability, they may be more frequent in individuals with atypical autism, although results are mixed across studies (Gillberg and Coleman 1996; Juul-Dam et al. 2001; Rutter et al. 1994). A study by Hara (2007) found no differences between individuals with autism and atypical autism in terms of epilepsy. Biological research on atypical autism and PDD NOS, including neuroimaging and genetic studies, has overall found no evidence for differences between these conditions and autistic disorder (Towbin 2005).
+
+### Evaluation and Differential Diagnosis
+
+The assessment process for atypical autism is the same as that recommended for autism and other pervasive developmental disorders. In making a differential diagnosis, whether the criteria are met for a diagnosis of autism or Asperger’s disorder needs to be considered, and degree of intellectual disability needs to be taken into account. Differentiating atypical autism from language disorder is also important. It has been demonstrated that children with PDD NOS can be differentiated from children with language disorders on the basis of more severe social impairment and a greater need for routines and order (Mayes et al. 1993). Research with children with a significant degree of disruptive behavior has also highlighted the need to consider a diagnosis of atypical autism. In a cohort of primary school-aged children, significant impairments in social and communication domains were identified in children with significant disruptive behavior, with 28% meeting criteria for a diagnosis of atypical autism (Donno et al. 2010).
+Differentiating ADHD and atypical autism in young children can be problematic, with children often first diagnosed with ADHD (Jensen et al. 1997). In a retrospective study, parents of children with PDD NOS or ADHD reported on the symptoms of their children in their first 4 years (Roeyers et al. 1998). Early differences were infrequent, although children with ADHD showed more hyperactive behaviors during the 7–12-month period; this difference was not maintained as the PDD NOS children became active with age. As children aged, the difference became more apparent, with children with PDD NOS demonstrating more pronounced social difficulties, withdrawal, anxiety, stereotyped motor behaviors, unusual behaviors, and better scores on cognitive assessments compared to children with ADHD (Jensen et al. 1997; Luteijn et al. 2000; Roeyers et al. 1998; Scheirs and Timmers 2009).
+
+### Treatment
+
+As for autism, treatment for individuals with atypical autism needs to include a range of services and approaches. Behavioral, educational, and developmental approaches to the treatment of communication deficits, social difficulties, and behavior problems have been demonstrated to result in improvements for individuals with autism and are likely to be helpful for individuals with atypical autism. Although there are no drugs that specifically treat autism, medication and medication in combination with parent training approaches have been shown to reduce severe behavior problems such as aggression, self-injurious behavior, severe tantrums, and irritability (King 2000; Research Units on Pediatric Psychopharmacology (RUPP) Autism Network 2005a, b, 2009).
+Early intervention has been highlighted as a specific area of importance in the treatment of children with autism. Treatment gains have been demonstrated in adaptive functioning, developmental skills, symptom severity, and behavior problems (Dawson et al. 1998; Howlin et al. 2009; Rogers and Vismara 2008). Training parents to implement early intervention programs has also demonstrated gains in communicative behavior, knowledge of autism, parent communication style, parent-child interaction, child behavior problems, and a reduction in parent stress and mental health problems (McConachie and Diggle 2005; Tonge et al. 2006; Whittingham et al. 2009). Improvements can also be made in teaching joint attention, symbolic play, and imitation skills to very young children (Drew et al. 2002; Kasari et al. 2001, 2006). Although important gains have been made in the development of evidence-based early interventions, less is known about the role played by mediating or moderating variables in treatment outcomes. Importantly, the impact that early childhood intervention may or may not have on adult outcomes remains unknown. Research on treatment approaches specifically for individuals with atypical autism is lacking; it is assumed that treatment needs and approaches are similar to those for individuals with autism. Whether existing evidence-based treatments produce greater effects in individuals with atypical autism remains an area for further research. As is the case for autism, it has been concluded that no single treatment approach or method has been shown to be effective for PDD NOS (Towbin 2005), with treatment approaches needing to take into account the specific strengths, impairments, and needs of each individual.
+
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+
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+Rogers, S. J., & Vismara, L. A. (2008). Evidence-based comprehensive treatments for early autism. Journal of Clinical Child & Adolescent Psychology, 37(1), 8–38.
+Rondeau, E., Klein, L. S., Masse, A., Bodeau, N., Cohen, D., & Guile, J. M. (2010). Is pervasive developmental disorder not otherwise specified less stable than autistic disorder? A meta-analysis. Journal of Autism & Developmental Disorders, 41(9), 1267–1276.
+Rutter, M., Bailey, A., Bolton, P., & Le Couteur, A. (1994). Autism and known medical conditions: Myth and substance. Journal of Child Psychology & Psychiatry & Allied Disciplines, 35(2), 311–322.
+Scheirs, J. G. M., & Timmers, E. A. (2009). Differentiating among children with PDD-NOS, ADHD, and those with a combined diagnosis on the basis of WISC-III profiles. Journal of Autism and Developmental Disorders, 39(4), 549–556.
+Sigman, M., & Ruskin, E. (1999). Continuity and change in the social competence of children with autism, down syndrome, and developmental delays. Monographs of the Society for Research in Child Development, 64(1), v-114.
+Skuse, D. H. (2012). DSM-5’s conceptualization of autistic disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 51, 344–346.
+Stone, W. L., Lee, E. B., Ashford, L., Brissie, J., Hepburn, S. L., Coonrod, E. E., et al. (1999). Can autism be diagnosed accurately in children under 3 years? Journal of Child Psychology and Psychiatry, 40(2), 219–226.
+Sutera, S., Pandey, J., Esser, E. L., Rosenthal, M. A., Wilson, L. B., Barton, M., et al. (2007). Predictors of optimal outcome in toddlers diagnosed with autism spectrum disorders. Journal of Autism and Development-mental Disorders, 37(1), 98–107.
+Tonge, B., Brereton, A. V., Kiomall, M., Mackinnon, A., King, N. M., & Rinehart, N. (2006). Effects on parental mental health of an education and skills training program for parents of young children with autism: A randomized controlled trial. Journal of the American Academy of Child and Adolescent Psychiatry, 45(5), 561–569.
+Towbin, K. E. (2005). Pervasive developmental disorder not otherwise specified. In F. R. Volkmar, R. Paul, A. Klin, & D. Cohen (Eds.), Handbook of autism and pervasive developmental disorders (Vol. 1, 3rd ed., pp. 165–200). Hoboken: Wiley.
+Turner, L. M., Stone, W. L., Pozdol, S. L., & Coonrod, E. E. (2006). Follow-up of children with autism spectrum disorders from age 2 to age 9. Autism, 10(3), 243–265.
+van Daalen, E., Kemner, C., Dietz, C., Swinkels, S. H. N., Buitelaar, J. K., & van Engeland, H. (2009). Inter-rater reliability and stability of diagnoses of autism spectrum disorder in children identified through screening at a very young age. European Child & Adolescent Psychiatry, 18(11), 663–674.
+Volkmar, F. R. (1998). Categorical approaches to the diagnosis of autism: An overview of DSM-IV and ICD-10. Autism: The International Journal of Research and Practice, 2(1), 45–60.
+Volkmar, F. R., Shaffer, D., & First, M. (2000). PDDNOS in DSM-IV. Journal of Autism and Developmental Disorders, 30(1), 74–75.
+Walker, D. R., Thompson, A., Zwaigenbaum, L., Goldberg, J., Bryson, S. E., Mahoney, W. J., et al. (2004). Specifying PDD-NOS: A comparison of PDD-NOS, Asperger syndrome, and autism. Journal of the American Academy of Child & Adolescent Psychiatry, 43(2), 172–180.
+Whittingham, K., Sofronoff, K., Sheffield, J., & Sanders, M. R. (2009). Stepping stones triple P: An RCT of a parenting program with parents of a child diagnosed with an autism spectrum disorder. Journal of Abnormal Child Psychology, 37(37), 469–480.
+Williams, E., Thomas, K., Sidebotham, H., & Emond, A. (2008). Prevalence and characteristics of autistic spectrum disorders in the ALSPAC cohort. Developmental Medicine & Child Neurology, 50(9), 672–677.
+World Health Organisation. (1978). International classification of diseases: Mental disorders: Glossary and guide to their classification (9th ed.). Geneva: World Health Organisation.
+World Health Organisation. (1992). The ICD-10 classification of mental and behavioural disorders: Diagnostic criteria for research. Geneva: World Health Organisation.
+World Health Organisation, GCP Network (2017). ICD-11 draft guidelines. Available at https://gcp.network/en/ private/icd-11-guidelines/grouping. Accessed 22 Dec 2017.
+
+## Audiovisual Media Content Preferences of Children with Autism Spectrum Disorders
+
+### Definition
+
+Children with autism spectrum disorder (ASD) spend more time with screen media than any other leisure activity (Shane and Albert 2008). Evidence indicates that children with ASD spend most of their screen time with nonsocial media (i.e., television, video games) and less time with social media. Compared with other disability groups, among ASD youth, rates of nonsocial media use are higher, and that of social media use are lower (Mazurek 2013b). Similarly, children with ASD report more time with television and video games and less time with social media as compared to neurotypical siblings (Mazurek 2013a). Given that children with ASD report difficulty in developing and maintaining friendships compared to typically developing children (i.e., Rowley et al. 2012), the finding that ASD youth spend more time with nonsocial media is not surprising.
+Although existing research demonstrates that children with ASD engage in selective exposure to screen media, less attention has been paid to content preferences among this population. There are only a handful of studies that offer some insight into media content preferences of children with ASD. Regarding television, some studies report that children with ASD tend to prefer animated content (e.g., Martins et al. 2019; Shane and Albert 2008) and that this content is typically created for younger audiences (Martins et al. 2019). Martins et al. (2019) argued that children with ASD select programs with content features made to appeal to developmentally similar children; hence programs for the preschool audience are commonly reported as favorites. These programs are slower-paced and more attuned to specific, individual sensory preferences which may aid in comprehension. Considering that parents identify comprehensibility of content as a key factor in program selection by their children (Martins et al. 2019), then we would expect that these programs are what children with ASD like the most. Comprehensibility is also a key factor in video game content preferences. In their review, Stiller and Mößle (2018) reported that children with ASD prefer role-playing and simulation games. Martins et al. (2019) argued that games like Minecraft are popular among this population because children understand the basic functionality for paying and pausing and have full control over the content they view. As mentioned above, research demonstrates that children with ASD spend little to no time on social media platforms (Martins et al. 2019; Mazurek 2013a, b). There are at least three reasons why children with ASD spend less time with nonsocial media. First, children with ASD are socially isolated (Rowley et al. 2012) and may not have a network of friends to connect with online. Second, some apps like Snapchat or Facebook are not developmentally appropriate, and ASD youth may not understand how such apps work. Finally, parental concerns over the safety of social networks may prevent ASD youth from experimenting with the technology. Parents are worried that their ASD child is incapable of recognizing deceit and therefore might be targets of child predators. Other parents were worried that their child could be made fun or bullied for the content they post (see Martins et al. 2019).
+
+Future research should continue to examine content preferences and how such preferences can be used to teach children both academic and socioemotional skills. For example, future work should test whether education skill could be taught using repeated exposure to preferred components of media (i.e., favorite media characters). Such work is particularly important given that parents report that “autism apps” marketed to the ASD community are either unaffordable or not proven to work (see Martins et al. 2019). Future research should also examine whether restricting access to online communities or social networking apps does more harm than good as ASD children transition into adolescence.
+
+### See Also
+
+*   Visual Supports
+
+### References and Reading
+
+Martins, N., King, A. J., & Beights, R. (2019). Audiovisual media content preferences of children with autism spectrum disorders: Insights from parental interviews. Journal of Autism and Developmental Disorders, 1–9. https://doi.org/10.1007/s10803-019-03987-1.
+Mazurek, M. O., & Engelhardt, C. R. (2013a). Video game use in boys with autism spectrum disorder, ADHD, or typical development. Pediatrics, 132, 260–266. https://doi.org/10.1542/peds.2012-3956.
+Mazurek, M. O., & Wenstrup, C. (2013b). Television, video game and social media use among children with ASD and typically developing siblings. Journal of Autism and Developmental Disorders, 43, 1258–1271. https://doi.org/10.1007/s10803-012-1659-9.
+Rowley, E., Chandler, S., Baird, G., Simonoff, E., Pickles, A., Loucas, T., et al. (2012). The experiences of friendship, victimization and bullying in children with an autism spectrum disorder: Associations with child characteristics and school placement. Research in Autism Spectrum Disorders, 6, 1126–1134.
+Shane, H. C., & Albert, P. D. (2008). Electronic screen media for persons with autism spectrum disorder: Results of a survey. Journal of Autism and Developmental Disorders, 38, 1499–1508. https://doi.org/10.1 007/s10803-007-0527-5.
+Stiller, A., & Mößle, T. (2018). Media use among children and adolescents with autism spectrum disorder: A systematic review. Review Journal of Autism and Developmental Disorders, 5, 227–246. https://doi.org/10.1007/s40489-018-0135-7.
+
+## Auditory Acuity
+
+### Synonyms
+
+Hearing sensitivity; Hearing threshold
+
+### Definition
+
+Auditory acuity describes how sensitive the auditory system is to sound. Auditory acuity is assessed by determining the intensity at which a tone is just audible. Frequencies important for speech perception are typically tested (octave frequencies from 250 to 8,000 Hz). Normal hearing sensitivity is defined as hearing thresholds from –10 to 15 dB HL. Hearing sensitivity between 16 and 25 dB HL is considered minimal or borderline; between 26 and 40 dB HL is considered mild hearing loss; between 41 and 55 dB HL is considered moderate hearing loss; between 56 and 70 dB HL is considered moderately severe hearing loss; between 71 and 90 dB HL is considered severe hearing loss; and greater than 91 dB HL is considered profound hearing loss. Hearing sensitivity would be evaluated in an individual with autism spectrum disorders if questions regarding hearing abilities existed, but more systematic research needs to be completed regarding auditory acuity in the population of individuals with autism.
+
+### See Also
+
+*   Hearing Sensitivity
+*   Hearing Threshold
+
+### References and Reading
+
+Hall, J. (1992). Handbook of auditory evoked responses. Needham Heights: Allyn & Bacon.
+Justice, L. (2006). Communication sciences and disorders: An introduction. Columbus: Pearson.
+Rosenhall, U., Nordin, V., Sandstrom, M., Ahlsen, G., & Gillberg, C. (1999). Autism and hearing loss. Journal of Autism and Developmental Disorders, 29(5), 349–357.
+
+## Auditory Brainstem Response (ABR)
+
+### Synonyms
+
+Brainstem auditory evoked response (BAER)
+
+### Definition
+
+Auditory brainstem response (ABR), sometimes called brainstem auditory evoked response (BAER), is an electrophysiologic test that assesses the auditory system through the low brainstem. This test can assess hearing sensitivity in individuals who cannot respond to traditional testing; thus, it is often used in newborn hearing screenings and on populations that are nonverbal. The ABR is completed by placing electrodes on the individual’s head and ears and placing earphones in their ears. Responses are elicited using click and tonal stimuli which are delivered through the earphones. Five waveforms are typically present in the ABR (waves I, II, III, IV, and V); however, wave V is the waveform used for threshold testing. Individuals with autism spectrum disorders might not be able to consistently respond to traditional tests of hearing sensitivity; therefore, ABR may be useful in establishing hearing sensitivity for these individuals.
+
+### See Also
+
+*   Auditory Acuity
+*   Brainstem Audiometry
+*   Hearing
+
+### References and Reading
+
+Hall, J. (1992). Handbook of auditory evoked responses. Needham Heights: Allyn & Bacon.
+Rosenblum, S. M., Arick, J. R., Krug, D. A., Stubbs, E. G., Young, N. B., & Pelson, R. O. (1980). Auditory brainstem evoked responses in autistic children. Journal of Autism and Developmental Disorders, 10, 215–225.
+Rosenhall, U., Nordin, V., Sandstrom, M., Ahlsen, G., & Gillberg, C. (1999). Autism and hearing loss. Journal of Autism and Developmental Disorders, 29(5), 349–357.
+Skoff, B. F., Mirsky, A. F., & Turner, D. (1980). Prolonged brainstem transmission time in autism. Psychiatry Research, 2, 157–166.
+Skoff, B. F., Fein, D., McNally, B., Lucci, D., Humes-Bartlo, M., & Waterhouse, L. (1986). Brainstem auditory evoked potentials in autism. Psychophysiology, 23, 462.
+
+## Auditory Cortex
+
+### Synonyms
+
+Auditory brain area
+
+### Definition
+
+The human auditory cortex occupies a large portion of the superior temporal gyrus located along the sylvian fissure dorsally and the superior temporal sulcus ventrally (Brodmann area 41, 42, and 22). The dorsal surface of the superior temporal gyrus is located within the sylvian fissure and is divided into Heschl’s gyrus, the planum temporale, and the planum polare. Studies have suggested that the primary auditory cortex in humans is mainly confined to the anterior-medial wall of Heschl’s gyrus. This brain region is vital in decoding and processing spoken language and sounds. The planum temporale, also vital in auditory processing, is located posterior to Heschl’s gyrus and lies on the superior surface of the posterior superior temporal sulcus. While high-frequency sounds activate a small lateral region anterior to the intersection of Heschl’s gyrus and the superior temporal gyrus and a more extensive medial region posterior to the tip of Heschl’s gyrus, low-frequency sounds activate lateral regions centered on mid-Heschl’s gyrus and extending posteriorly along the superior temporal gyrus.
+Neuroimaging research has identified anatomical and functional abnormalities in the planum temporale in individuals with autism spectrum disorder. While anatomical abnormalities include abnormal asymmetry, altered minicolumn organization, and altered cell type and count, the functional abnormalities include abnormal feature extraction and sensitivity to sounds.
+
+### See Also
+
+*   Auditory Acuity
+*   Auditory Processing
+*   Cortical Language Areas
+*   Primary Sensory Areas
+*   Wernicke’s Aphasia
+
+### References and Reading
+
+Binder, J. R., Rao, S. M., Hammeke, T. A., Yetkin, F. Z., Jesmanowicz, A., Bandettini, P. A., et al. (1994). Functional magnetic resonance imaging of human auditory cortex. Annals of Neurology, 35, 662–672.
+Boddaert, N., Chabane, N., Belin, P., Bourgeois, M., Royer, V., Barthelemy, C., et al. (2004). Perception of complex sounds in autism: Abnormal auditory cortical processing in children. American Journal of Psychiatry, 161, 2117–2120.
+Celesia, G. G. (1976). Organization of auditory cortical areas in man. Brain, 99, 403–414.
+Palmen, S., van Engeland, H., Hof, P., & Schmitz, C. (2004). Neuropathological finding in autism. Brain, 127, 2572–2583.
+Zatorre, R. J., Belin, P., & Penhune, V. (2002). Structure and function of auditory cortex: Music and speech. Trends in Cognitive Sciences, 6, 37–46.
+
+## Auditory Discrimination
+
+### Definition
+
+While enhanced discrimination and memory for musical pitch have been widely described in the literature on musical savants with autism, it is only in more recent times that such abilities have been observed in autistic individuals without savant skills (see Heaton 2003). Bonnel et al. (2010) studied auditory perception in individuals with high-functioning autism and Asperger’s syndrome and showed that enhanced pitch discrimination was more prevalent in those with late speech onset and was not associated with atypical discrimination of stimuli that were spectrally and/or temporally complex. Research identifying enhanced discrimination of pitch change in linguistic stimuli (Jarvinen-Pasley and Heaton 2007) has shown that atypical pitch processing is not limited to music but generalizes across auditory domains. This suggests that difficulties in understanding pitch-mediated linguistic cues or prosody, demonstrated in a number of studies (for review McCann and Peppe 2003), are not perceptual in origin but result from abnormalities in higher-order cognitive operations. Building on the enhanced perceptual functioning model, the neural complexity hypothesis (see Samson et al. 2010) is able to account for enhanced pitch discrimination as well as abnormalities in processing acoustically complex stimuli. According to this model, autism is characterized by a bias toward the perceptual features of auditory information. At the behavioral level, this can be associated with enhanced processing of low-level stimuli and atypical processing of higher-order information, such as greater focus toward the perceptual aspects of speech stimuli.
+
+### See Also
+
+*   Autistic Savants
+*   Enhanced Perceptual Functioning
+
+### References and Reading
+
+Bonnel, A., McAdams, S., Smith, B., Berthiaume, C., Bertone, A., Ciocca, V., et al. (2010). Enhanced pure-tone pitch discrimination among persons with autism but not Asperger syndrome. Neuropsychologia, 48(9), 2465–2475.
+Heaton, P. (2003). Pitch memory, labeling and disembedding in autism. Journal of Child Psychology and Psychiatry, 44(4), 543–551.
+Jarvinen-Pasley, A., & Heaton, P. (2007). Evidence for reduced domain-specificity in auditory processing in autism. Developmental Science, 10(6), 786–793.
+McCann, J., & Peppe, S. (2003). Prosody in autism spectrum disorders: A critical review. International Journal of Language & Communication Disorders, 38(4), 325–350.
+Samson, F., Hyde, K. L., Bertone, A., Soulieres, I., Mendrek, A., Ahad, P., et al. (2010). Atypical processing of auditory temporal complexity in autistics. Neuropsychologia, 49, 546–555.
+
+## Auditory Integration Therapy
+
+### Definition
+
+Auditory integration training (AIT) is an intervention technique which is currently considered experimental. It was created to attempt to improve the way individuals with autism spectrum disorders (ASD) recognize and respond to sound and to reduce other behaviors associated with ASD. AIT has also been referred to as auditory enhancement training (AET) and audio-psycho-phonology (APP).
+
+### Historical Background
+
+Auditory integration training (AIT) was first written about in 1982 in a book by the otolaryngologist Guy Berard, which was translated in 1993 from French to the English title Hearing Equals Behavior. In his writing, Berard suggests that various disorders (“autism,” hyperactivity, depression, learning difficulties) are associated with atypical sensitivity to sound.
+The AIT technique became widely popular after the 1991 publication of Annabel Stehli’s The Sound of a Miracle: A Child’s Triumph over Autism. In this book, Stehli described the full recovery of her daughter, who was diagnosed with autism and schizophrenia, after 10 h of AIT at Berard’s clinic. In 1994, the American Speech-Language-Hearing Association (ASHA) published a review of the existing data on AIT in response to such accounts linking AIT to increased eye contact, social awareness, verbalizations, auditory comprehension, and articulation and reduced tantrums and hyperacusis (i.e., oversensitivity to certain frequency ranges of sound) in children with autism spectrum disorders, learning difficulties, attention deficit disorder, and dyslexia. Currently, several professional organizations (including the American Speech-Language-Hearing Association, the American Academy of Audiology, the Educational Audiology Association, and the American Academy of Pediatrics) indicate that AIT should be considered an experimental rather than an evidence-based treatment due to the lack of scientific data supporting its benefits. While in the United States the majority of AIT practitioners use the original Berard or a modified methodology, there are other methods of AIT in existence (including the Tomatis and Clark methods).
+
+### Rationale or Underlying Theory
+
+Dr. Guy Berard, an ear, nose, and throat (ENT) physician, first introduced auditory integration training (AIT) suggesting that many learning and behavioral disorders, “including autism,” are associated with hypersensitivity to sound at particular frequencies possibly resulting in disturbances in learning and discomfort. He suggested that although many children with autism spectrum disorders (ASD) can hear sound, the way in which they process sounds is different and can result in reduced emotional responsiveness and repetitive behaviors even if hypersensitivity to sound does not exist.
+
+### Goals and Objectives
+
+In 1982, Dr. Berard suggested that auditory integration training (AIT) would involve a “reeducation” of the hearing process for individuals with autism spectrum disorders (ASD) targeting the atypical sound perception theorized to be present in a variety of behavioral and learning disorders. Specifically, he suggests the training of the middle ear muscles, and the auditory nervous system is targeted through listening exercises.
+
+### Treatment Participants
+
+Auditory integration training (AIT) has been promoted by Dr. Berard as a useful intervention for a variety of disorders (e.g., learning disabilities, behavior disorders, autism, pervasive developmental disorder, attention deficit disorder, attention deficit hyperactivity disorder, tinnitus, progressive deafness, hyperacusis, allergic disorders, depression, suicidal tendencies, poor organizational skills) and has also been recommended for reducing foreign accents and writer’s block.
+
+### Treatment Procedures
+
+Auditory integration training (AIT) begins with an audiogram (i.e., a graph showing the results of a pure-tone hearing test) to determine whether auditory “abnormalities” exist. The treatment involves ten consecutive days of therapy centered upon listening to music (that has been modified to dampen certain sound frequencies and intensities to correspond to those found abnormal on the audiogram) for 30 min twice a day. It is recommended that sessions occurring on the same day be separated by at least 3 h, while a 2-day interruption of therapy on weekends is allowed. Audiograms are also used to determine if filter settings need to be adjusted mid-intervention and to monitor response to treatment post-intervention. Berard asserts that following AIT, audiograms show that auditory distortions are eliminated, as they become “flattened.” He explains that the “peaks and valleys” in the original audiograms reflect areas of hyper- and hypo-sensitivity, but there is debate as to whether these patterns truly indicate auditory “abnormalities.”
+Following the recommended 20 auditory integration therapy (AIT) sessions in Dr. Berard’s method, an audiogram is obtained and reviewed, while changes in behavior patterns are examined to measure outcome. In efficacy studies of AIT, outcome measures have included post-intervention assessments in the following areas: cognitive ability, core features of autism (i.e., social interaction, communication, and behavioral problems), hyperacusis, auditory processing, behavioral problems, attention and concentration, activity level, quality of life in school and at home, and adverse events. The US Food and Drug Administration (FDA) banned the import of the Berard’s original equipment (Audiokinetron or Ears Education and Retraining System) used for AIT as a medical device based on finding that there was no sufficient evidence to support that it benefited individuals medically. The FDA regards the Audiokinetron as an educational aid but not appropriate for the treatment or curing of any medical conditions, such as autism spectrum disorders. The Digital Auditory Aerobics (DAA) device was introduced as a result of this limited access to the Audiokinetron in the United States. The 20 compact disks (CDs) (each containing 30 min of modulated music) available with this device are believed to match the output of the Audiokinetron device. Other AIT programs are available (e.g., Samonas Sound Therapy, The Listening Program) which provide music on CDs and promise similar results to Berard’s AIT programs.
+
+### Efficacy Information
+
+The efficacy of auditory integration training (AIT) continues to be debated. A review of the available existing research indicates that three studies suggest improvements with AIT at 3 months post-intervention based on reported improved performance scores on the Aberrant Behavior Checklist. It should be noted that investigators in these studies were associated with organizations that promote or directly provide AIT. Similar results have not yet been replicated by any independent studies. The review highlights the fact that the studies examining AIT were not randomized controlled trials (used to minimize bias), did not contain control or alternative treatment group, and involved single or very few participants or used surveys or animals.
+The American Speech-Language-Hearing Association (ASHA) issued a report on AIT, in which it states that further research in AIT is discouraged given the lack of evidence that it is an effective treatment for individuals with autism spectrum disorder (ASD) but indicates that a “high level of evidence” of its efficacy should be provided if future AIT trials are conducted. ASHA also cautioned parents to take precautions to avoid hearing loss while also being aware of the costs involved in receiving AIT. In studies where children or adults with ASD (ages 3–39 years) were selected and randomly assigned to study treatment groups, though no adverse effects were reported, no noteworthy changes were found in the participants’ ability to process sound, their quality of life, or their core and associated features of ASD following AIT. ASHA expressed concerns that clear criteria (based on evidence-based research) are not available, indicating which individuals will be most appropriate for AIT, and families could find both their financial resources and hope strained or depleted by investing in interventions that lack empirical support. In addition, the professional organization had reservations regarding the variability in AIT treatment protocols and the possible noise-induced hearing loss that might be associated with AIT devices, as sufficient data on the risk to participants regarding intensity of sound and length of presentation is not currently available for the devices. In more recent studies (2013–2016), electrophysiological changes and behavioral changes via caregiver report were observed in children with ASD following a series of AITsessions. Authors of these studies suggested further research to explain the neural mechanisms of how AIT may affect such changes. Still, studies during this same time period suggested the lack of efficacy of AIT, some suggesting increased occurrence of stereotypy post-AIT. Considering that ASD behaviors can often resemble auditory processing disorders (APD), ASHA has also ruled out the diagnosis of APD, for which AIT is often suggested, in children with ASD unless reliable testing reveals deficits on multiple assessments. In the case that a child with ASD does meet this guideline, the benefit of receiving intervention involving listening tasks with limited social interaction can also be questioned.
+
+### Qualifications of Treatment Providers
+
+The majority of auditory integration training (AIT) practitioners are speech-language pathologists or audiologists but have also included psychologists, physicians, social workers, and teachers. No training is required to operate the Digital Auditory Aerobics (DAA) device that is currently used within the United States to provide AIT based on Berard’s method. Other AIT programs do provide trainings to practitioners (e.g., The Listening Program [2½ days], Samonas Sound Therapy [offers a credentialing process following pre-workshop training, initial and advanced workshop training, and a year of practice]). The American Speech-Language-Hearing Association, the American Academy of Audiology, the Educational Audiology Association, and the American Academy of Pediatrics nonetheless all state that AIT should be considered an experimental rather than an evidence-based treatment due to the limited amount of scientific research studies supporting its benefits.
+
+### See Also
+
+*   Aberrant Behavior Checklist
+*   American Speech-Language-Hearing Association Functional Assessment of Communication Skills
+*   Auditory Processing Disorder
+
+### References and Reading
+
+Al-Ayadhi, L. Y., Al-Drees, A. M., & Al-Arfaj, A. M. (2013). Effectiveness of auditory integration therapy in autism spectrum disorders–prospective study. Autism Insights, 5, 13.
+American Academy of Audiology. (1993). Position statement: Auditory integration training. Audiology Today, 5(4), 21.
+American Academy of Pediatrics. (1998). Auditory integration training and facilitated communication for autism. Pediatrics, 102(2), 431–433.
+American Speech-Language-Hearing Association Working Group on Auditory Integration Training. (2003). Auditory integration training. (Technical Report). Rockville: Author.. Retrieved from www.asha.org/ docs/html/TR2004-00260.html
+Berard, G. (1993). Hearing equals behaviour. New Canaan: Keats Publishing. (Original work published 1982).
+Berard, G. (1995). Concerning length, frequency, number, and follow-up AIT sessions. The Sound Connection Newsletter, 2(3), 5–6. Available from The Society for Auditory Intervention Techniques.
+Bettison, S. (1996). The long-term effects of auditory training on children with autism. Journal of Autism and Developmental Disorders, 26(3), 361–373.
+Brockett, S. S., Lawton-Shirley, N. K., & Kimball, J. G. (2014). Berard auditory integration training: Behavior changes related to sensory modulation. Autism Insights, 6, 1.
+Committee on Children With Disabilities. (1998). Auditory integration training and facilitated communication for autism. Pediatrics, 102(2), 431–433.
+Edelson, S., Arin, D., Bauman, M., Lukas, S., Rudy, J., Sholar, M., et al. (1999). Auditory integration training: A double-blind study of behavioural and electrophysiological effects in people with autism. Focus on Autism and Other Developmental Disabilities, 14(2), 73–81.
+Educational Audiology Association. (1997). Auditory integration training: Educational Audiology Association position statement. Educational Audiology Newsletter, 14(3), 16.
+Feigin, J. A., Kapun, J. G., Stelmachowicz, P. G., & Gorga, M. P. (1989). Probe-tube microphone measures of ear canal sound pressure levels in infants and children. Ear and Hearing, 10(4), 254–258.
+Gillberg, C., & Coleman, M. (2000). The biology of autistic syndromes (3rd ed.). London: MacKeith Press.
+Gilmore, T., Madaule, P., & Thompson, B. (1989). About the Tomatis method. Toronto: Listening Center Press.
+Gringras, P. (2000). Practical paediatric psychopharmacological prescribing in autism: The potential and the pitfalls. Autism, 4(3), 229–247.
+LaFrance, D. L., Miguel, C. F., Donahue, J. N., & Fechter, T. R. (2015). A case study on the use of auditory integration training as a treatment for stereotypy. Behavioral Interventions, 30(3), 286–293.
+Mudford, O. C., Cross, B. A., Breen, S., Cullen, C., Reeves, D., Gould, J., & Douglas, J. (2000). Auditory integration training for children with autism: no behavioral benefits detected. American Journal on Mental Retardation, 105(2), 118–129.
+Mudford, O. C., & Cullen, C. (2005). Auditory integration training: A critical review. In J. W. Jacobson, R. M. Foxx, & J. A. Mulick (Eds.), Controversial therapies for developmental disabilities: Fad, fashion, and science in professional practice (pp. 351–362). Mahwah: Lawrence Erlbaum Associates.
+Rimland, B., & Edelson, S. M. (1994). The effects of auditory integration training on autism. American Journal of Speech-Language Pathology, 3(2), 16–24.
+Rimland, B., & Edelson, S. (1995). Brief report: A pilot study of auditory integration training in autism. Journal of Autism and Developmental Disorders, 25(1), 61–70.
+Sinha, Y., Silove, N., Wheeler, D. M., & Williams, K. J. (2009). Auditory integration training and other sound therapies for autism spectrum disorders (Review). Hoboken: Wiley.
+Sokhadze, E. M., Casanova, M. F., Tasman, A., & Brockett, S. (2016). Electrophysiological and behavioral outcomes of berard auditory integration training (AIT) in children with autism spectrum disorder. Applied psychophysiology and biofeedback, 41(4), 405–420.
+Stehli, A. (1991). The sound of a miracle. A child's triumph over autism. New York: Doubleday.
+Tharpe, A. M. (1998). Treatment fads versus evidence-based practice. In F. H. Bess (Ed.), Children with hearing impairment: Contemporary trends (pp. 179–188). Nashville: Vanderbilt Bill Wilkerson Center Press.
+Tochel, C. (2003). Sensory or auditory integration therapy for children with autistic spectrum disorders. London: Bazian Ltd (Eds.), Wessex Institute for Health Research and Development, University of Southampton.
+Veale, T. (1993). Effectiveness of AIT Using the BCG Device (Clark Method): A Controlled Study. Paper Presented at the World of Options International Autism Conference. Toronto.
+Zollweg, W., Palm, D., & Vance, V. (1997). The efficacy of auditory integration training: A double blind study. American Journal of Audiology, 6(3), 39–47.
+
+## Auditory Potentials
+
+### Synonyms
+
+Auditory evoked potential (AEP)
+
+### Definition
+
+An auditory potential is an electroencephalographic (EEG) response, less than a millivolt, time-locked to an auditory sound such as a click, tone, or speech sound. It is recorded from scalp electrodes and consists of averaged responses to a series of sounds. Averaging removes background EEG activity, usually considered to be unrelated to the auditory potential.
+A brief sound such as a click triggers at least 15 waveform peaks that unfold over the first second (Picton et al. 1974). These alternating positive and negative peaks reflect the flow of auditory information from the brainstem to the cortex. The short-latency peaks appearing during the first tenth of a second (10 ms) originate from the primary auditory pathway of the brainstem. Central Auditory Processing Disorders (CAPDs) were described in early 1940s and have recently become of interest to ASD researchers (see Ocak et al. 2018). Auditory middle latency responses are promising auditory tests that allow the identification of functional deficits of the central auditory pathways, and the cerebral hemispheres in school children with reading and writing learning disorders. The recording of these potentials ensure visualization of the electrical activity of the primary auditory cortex and the auditory thalamus-cortical pathways, from the observation of a sequence of waves, negative (N) and positive (P). Na, Pa, Nb, Pb occur in 10–80 ms intervals after stimuli (McPherson et al. 2008).
+The later auditory potentials, a subset of event-related potentials (ERPs), represent the sum of neural activity originating from spatially distinct sources. They are usually studied with multiple scalp electrodes that enable determination of waveform scalp topography. Mid-latency auditory peaks, which appear during the 10–50-ms interval, have few well-established clinical findings. Attention effects are seen under some conditions during the later part of this interval. Long-latency peaks appearing between 50 and 1,000 ms have received the most study. The specific timing of these peaks depends on both the auditory stimulus characteristics and the task demands. They are named starting with the initial positive peak (P1) at 50 ms usually maximal at the frontocentral electrodes. Next is the negative peak (N1) at around 100 ms, maximal at the vertex. P2 peaks at 150–200 ms. The negative peak (N2) is typically maximal at 200–300 ms at central sites. The P3 peak at 300–400 ms is attention dependent. Amplitude is inversely related to stimulus probability, and latency is positively related to task difficulty. Developmentally, the scalp location of the maximum depends on task conditions. These waveform peaks each reflect several underlying components. The waveform peaks should be distinguished from the components, which refer to potential neural sources. Unless the component is large such as P3b, it usually needs to be isolated with difference waves or by experimental design (Luck 2005). The component peaks are often identified by the number of milliseconds to peak, e.g., N75 and P100. Auditory ERPs are also used to study language processing. An N400 component, maximal over central and parietal sites, is seen when there is a semantic deviation from expectations, e.g., the last word in a sentence is out of context. P3a, P3b, and N400 components do not appear before ages 3 or 4 years. A central, frontal negative component, at 400–500 ms, reflecting attention has been identified in early infants and labeled “Nc.” A recent review concluded that persons with autism show differences in many of the long-latency components (Jeste and Nelson 2009).
+
+### See Also
+
+*   Brainstem Auditory Evoked Potentials
+*   Electroencephalogram (EEG)
+*   Event-Related Potential (ERP)
+*   Evoked Potentials
+
+### References and Reading
+
+Andreassi, J. L. (2007). Psychophysiology: Human behavior and physiological response (5th ed.). Mahwah: Lawrence Erlbaum Associates.
+Chermak, G. D., & Musiek, F. E. (1992). Managing central auditory processing disorders in children and youth. American Journal of Audiology, 1, 61–65.
+Handy, T. C. (Ed.). (2005). Event-related potentials: A methods handbook. Cambridge: MIT Press.
+Jeste, S. S., & Nelson, C. A. (2009). Event related potentials in the understanding of autism spectrum disorders: An analytical review. Journal of Autism and Developmental Disorders, 39, 495–510.
+Luck, S. J. (2005). An introduction to the event-related potential technique. Cambridge: MIT Press.
+McPherson, D. L., Ballachanda, B. B., & Kaf, W. (2008). Middle and longa latency evoked potentials. In R. J. Roeser, M. Valente, & H. H. Dunn (Eds.), Audiology: Diagnosis (pp. 443–477). New York: Thieme.
+Ocak, E., Eshraghi, R. S., Danesh, A., Mittal, R., & Eshraghi, A. A. (2018). Central auditory processing disorders in individuals with autism spectrum disorders. Balkan Medical Journal, 35(5), 367–372. https://doi.org/10.4274/balkanmedj.2018.0853.
+Picton, T. W., Hillyard, S. A., Krausz, H. I., & Galambos, R. (1974). Human auditory evoked potentials. I: Evaluation of components. Electroencephalography and Clinical Neurophysiology, 36, 179–190.
+
+## Auditory Processing
+
+### Synonyms
+
+Central Auditory Processing Disorder (CAPD)
+
+### Short Description or Definition
+
+Central auditory processing disorder (CAPD) may be considered when a child is having difficulties producing or understanding verbal language. Lack of appropriate response to what others say may cause people to think the child may be deaf; however, audiological examination of children with CAPD is entirely normal. These children can hear and detect sounds, but their ability to process these sounds meaningfully is not developing as expected. These children may have difficulty recognizing sounds or discriminating between different sounds. CAPD is a controversial diagnosis that is not currently part of conventional diagnostic systems but is increasingly identified in the USA and
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