Institute of Mathematical Sciences, Chennai, 600113, India,
Cogn Neurodyn. 2008 Mar;2(1):65-77. doi: 10.1007/s11571-007-9034-9. Epub 2007 Nov 27.
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.
本文提出了一种新的皮质计算架构。该架构由包含神经元和突触的计算路径组成。这些路径被分解为横向、纵向和垂直成分。皮质计算随后被分解为横向计算（LaC）、纵向计算（LoC）和垂直计算（VeC）。已经表明，皮质电路中的各种环路结构在皮质计算以及记忆存储和检索中起着重要作用，这与短期和长期记忆的分子基础相一致。还提出了一种新的大脑学习方案，并解释了如何在提出的架构中实现它。提出了一些关于该架构的数学结果，其中一些没有证明。
