  Across the scientific literature, information measurement in the nervous
system is posed as a problem of information processing internal to the brain by
constructs such as neuronal populations, sensory surprise, or cognitive models.
Application of information theory in the nervous system has focused on
measuring phenomena such as capacity and integration. Yet the ecological
perspective suggests that information is a product of active perception and
interactions with the environment. Here, we propose Gibsonian Information (GI),
relevant to both the study of cognitive agents and single cell systems that
exhibit cognitive behaviors. We propose a formal model of GI that characterizes
how agents extract environmental information in a dynamic fashion. GI
demonstrates how sensory information guides information processing within
individual nervous system representations of motion and continuous multisensory
integration, as well as representations that guide collective behaviors. GI is
useful for understanding first-order sensory inputs in terms of agent
interactions with naturalistic contexts and simple internal representations and
can be extended to cybernetic or symbolic representations. Statistical
affordances, or clustered information that is spatiotemporally dependent
perceptual input, facilitate extraction of GI from the environment. As a
quantitative accounting of perceptual information, GI provides a means to
measure a generalized indicator of nervous system input and can be
characterized by three scenarios: disjoint distributions, contingent action,
and coherent movement. By applying this framework to a variety of specific
contexts, including a four-channel model of multisensory embodiment, we
demonstrate how GI is essential to understanding the full scope of cognitive
information processing.
