Outline of a novel architecture for cortical computation

TL;DR

This paper introduces a new cortical computation architecture based on neuron-synapse paths, decomposing cortical functions into lateral, longitudinal, and vertical components, with a novel learning scheme and supporting mathematical insights.

Contribution

It presents a novel neural architecture with specific path-based components and a new learning scheme, advancing understanding of cortical computation and memory mechanisms.

Findings

Identification of loop structures' roles in memory and computation

Proposal of a new brain learning scheme

Mathematical results supporting the architecture

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 only. 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 number of mathematical results about the architecture have been proposed, many of which without proof.