Increase in Mutual Information During Interaction with the Environment Contributes to Perception

Perception and motor interaction with physical surroundings can be analyzed by the changes in probability laws governing two possible outcomes of neuronal activity, namely the presence or absence of spikes (binary states). Perception and motor interaction with the physical environment are partly acc...

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Bibliographic Details
Published in:Entropy (Basel, Switzerland) Switzerland), 2019-04, Vol.21 (4), p.365
Main Authors: Gupta, Daya, Bahmer, Andreas
Format: Article
Language:English
Subjects:
affordance
Animal cognition
Circuits
Coding theory
Coupling
Dynamical systems
embedded cognitive theory
Entropy
Feedback
Nervous system
Perception
Principles
Random variables
Reduction
Shannon information
sparse coding
Stimuli
surprisal
temporal coupling
temporal processing
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Summary:Perception and motor interaction with physical surroundings can be analyzed by the changes in probability laws governing two possible outcomes of neuronal activity, namely the presence or absence of spikes (binary states). Perception and motor interaction with the physical environment are partly accounted for by a reduction in entropy within the probability distributions of binary states of neurons in distributed neural circuits, given the knowledge about the characteristics of stimuli in physical surroundings. This reduction in the total entropy of multiple pairs of circuits in networks, by an amount equal to the increase of mutual information, occurs as sensory information is processed successively from lower to higher cortical areas or between different areas at the same hierarchical level, but belonging to different networks. The increase in mutual information is partly accounted for by temporal coupling as well as synaptic connections as proposed by Bahmer and Gupta (Front. Neurosci. 2018). We propose that robust increases in mutual information, measuring the association between the characteristics of sensory inputs’ and neural circuits’ connectivity patterns, are partly responsible for perception and successful motor interactions with physical surroundings. The increase in mutual information, given the knowledge about environmental sensory stimuli and the type of motor response produced, is responsible for the coupling between action and perception. In addition, the processing of sensory inputs within neural circuits, with no prior knowledge of the occurrence of a sensory stimulus, increases Shannon information. Consequently, the increase in surprise serves to increase the evidence of the sensory model of physical surroundings
ISSN:1099-4300
1099-4300
DOI:10.3390/e21040365