DOI: 10.14704/nq.2011.9.3.449

Information and Learning in Neural Systems

Subhash Kak

Abstract


This paper presents a brief account of my research on applying information to neural systems. Although information in physical systems is measured in terms of entropy, it also has a subjective meaning that plays a role in cognition and creativity. To cover the broader meaning of information, I developed learning mechanisms that can recall given a fragment of the memory and a model for instantaneous learning in a neural network. Further, I introduced the notion of quantum neural computing and investigated new aspects of quantum entropy. I have also investigated questions of learning from the perspective of the three languages of the brain: associative, re-organizational, and quantum.

Keywords


cognition, information, learning models, neuroscience, paradox, quantum theory

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