Abstract
In this paper a novel architecture for cortical computation has been proposed. This architecture is composed of computing paths consisting of neurons and synapses. These paths have been decomposed into lateral, longitudinal and vertical components. Cortical computation has then been decomposed into lateral computation (LaC), longitudinal computation (LoC) and vertical computation (VeC). It has been shown that various loop structures in the cortical circuit play important roles in cortical computation as well as in memory storage and retrieval, keeping in conformity with the molecular basis of short and long term memory. A new learning scheme for the brain has also been proposed and how it is implemented within the proposed architecture has been explained. A few mathematical results about the architecture have been proposed, some of which are without proof.
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Acknowledgements
The author likes to acknowledge Chitta Ranjan Das for drawing the figures. Critical comments by two anonymous reviewers have greatly helped to improve the paper. A postdoctoral fellowship from the Institute of Mathematical Sciences (funded by the Department of Atomic Energy of the Government of India) under which the current research has been carried out is being acknowledged.
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Majumdar, K. Outline of a novel architecture for cortical computation. Cogn Neurodyn 2, 65–77 (2008). https://doi.org/10.1007/s11571-007-9034-9
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DOI: https://doi.org/10.1007/s11571-007-9034-9