A Novel Computing Architecture for Cognitive Systems based on the Laminar Microcircuitry of the Neocortex
University of Plymouth, The University of Manchester, University College London, University of Edinburgh, University of Oxford
The neocortex of the brain subserves sensory perception, attention, memory and a spectrum of other perceptual and cognitive functions, which combine to provide the biological system with its outstanding powers. It is clear that the brain carries out information processing in a fundamentally different way to today's conventional computers. The computational architecture of the brain clearly involves the use of highly parallel, asynchronous, nonlinear and adaptive dynamical systems, namely the laminar neural circuits of the neocortex. The fundamental aim of this project is to create a new "brain-inspired" computing architecture which possesses the basic properties of self-organisation, adaptation and plasticity manifest in the neural circuitry of the neocortex. The objective is a modular architecture based on a representation of a "stereotypical" cortical microcircuit. The project focuses on the laminar microcircuits of the primary visual cortex in order to build on the wealth of neurobiological knowledge concerning the behaviour and interconnectivity of neurons in this area of neocortex. However the wider objective is to use the laminar microcircuitry of primary visual cortex as an exemplar for a stereotypical neocortically-inspired architecture. This will allow the architecture to be deployed in a wide range of perceptual tasks, and potentially also in cognitive functions such as learning and attention, with minimal changes to the basic circuitry. The aim is not simply to build a detailed, biologically-precise model of primary visual cortex, but rather the challenge is to identify and capture the key fundamental principles and mechanisms that underlie the remarkable and ubiquitous information processing power of the neocortex.
At Manchester, we are investigating the feasibility of implementing the VLSI chips based on the cortical microcircuitry. We have proposed a new silicon neuron circuit, which produces biologically plausible action potentials and is capable of mimicking spiking and bursting firing patterns observed in cortical neurons, such as regular spiking, fast spiking, intrinsically bursting, chattering, etc. The prototype SpikeNeuron chip, implemented in 0.35um CMOS technology serves as a proof-of-concept, and illustrates how analogue circuitry can be used to implement complex functionality with minimum power consumption. Our neuron circuit consumes about 8pJ per spike - several orders of magnitute less than what is possible using digital technology to emulate the spiking behaviour!
J.H.B.Wijekoon and P.Dudek, "Compact silicon neuron circuit with spiking and bursting behaviour", Neural Networks, Vol 21, Number 2-3, pp 524-534, March/April 2008
J.H.B.Wijekoon and P.Dudek, “Spiking and Bursting Firing Patterns of a Compact VLSI Cortical Neuron Circuit”, International Joint Conference on Neural Networks, IJCNN 2007, Orlando, Florida, August 2007
J.H.B.Wijekoon and P.Dudek, “A simple analogue VLSI circuit of a cortical neuron”, IEEE International Conference on Electronics, Circuits and Systems, ICECS 2006, pp.1344-1347, December 2006
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Dr Piotr Dudek, School of Electrical and Electronic Engineering, The University of Manchester, PO Box 88, Manchester M60 1QD, UK, Email: firstname.lastname@example.org