  The process of integration of inputs from several sensory modalities in the
human brain is referred to as multisensory integration. Age-related cognitive
decline leads to a loss in the ability of the brain to conceive multisensory
inputs. There has been considerable work done in the study of such cognitive
changes for the old age groups. However, in the case of middle age groups, such
analysis is limited. Motivated by this, in the current work, EEG-based
functional connectivity during audiovisual temporal asynchrony integration task
for middle-aged groups is explored. Investigation has been carried out during
different tasks such as: unimodal audio, unimodal visual, and variations of
audio-visual stimulus. A correlation-based functional connectivity analysis is
done, and the changes among different age groups including: young (18-25
years), transition from young to middle age (25-33 years), and medium (33-41
years), are observed. Furthermore, features extracted from the connectivity
graphs have been used to classify among the different age groups.
Classification accuracies of $89.4\%$ and $88.4\%$ are obtained for the Audio
and Audio-50-Visual stimuli cases with a Random Forest based classifier,
thereby validating the efficacy of the proposed method.
