Author: Khalid Sayood1
Affiliation: <sup>1</sup> Department of Electrical and Computer Engineering, University of Nebraska, Lincoln, NE 68588-0511, USA.
Conference/Journal: Entropy (Basel)
Date published: 2018 Sep 14
Other:
Volume ID: 20 , Issue ID: 9 , Pages: 706 , Special Notes: doi: 10.3390/e20090706. , Word Count: 225
We examine how information theory has been used to study cognition over the last seven decades. After an initial burst of activity in the 1950s, the backlash that followed stopped most work in this area. The last couple of decades has seen both a revival of interest, and a more firmly grounded, experimentally justified use of information theory. We can view cognition as the process of transforming perceptions into information-where we use information in the colloquial sense of the word. This last clarification is one of the problems we run into when trying to use information theoretic principles to understand or analyze cognition. Information theory is mathematical, while cognition is a subjective phenomenon. It is relatively easy to discern a subjective connection between cognition and information; it is a different matter altogether to apply the rigor of information theory to the process of cognition. In this paper, we will look at the many ways in which people have tried to alleviate this problem. These approaches range from narrowing the focus to only quantifiable aspects of cognition or borrowing conceptual machinery from information theory to address issues of cognition. We describe applications of information theory across a range of cognition research, from neural coding to cognitive control and predictive coding.
Keywords: average mutual information; cognition; information theory; neuronal codes; predictive coding.
PMID: 33265795 PMCID: PMC7513233 DOI: 10.3390/e20090706