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Dimension Reduction and Dynamics of a Spiking Neural Network Model for Decision Making under Neuromodulation

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Eckhoff, Philip, Wong-Lin, KongFatt and Holmes, Philip (2011) Dimension Reduction and Dynamics of a Spiking Neural Network Model for Decision Making under Neuromodulation. SIAM Journal on Applied Dynamical Systems, 10 (1). pp. 148-188. [Journal article]

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URL: http://epubs.siam.org/siads/resource/1/sjaday/v10/i1/p148_s1?isAuthorized=no

DOI: 10.1137/090770096

Abstract

Previous models of neuromodulation in cortical circuits have used either physiologically based networks of spiking neurons or simplified gain adjustments in low-dimensional connectionist models. Here we reduce a high-dimensional spiking neuronal network model, first to a four-population mean-field model and then to a two-population model. This provides a realistic implementation of neuromodulation in low-dimensional decision-making models, speeds up simulations by three orders of magnitude, and allows bifurcation and phase-plane analyses of the reduced models that illuminate neuromodulatory mechanisms. As modulation of excitation-inhibition varies, the network can move from unaroused states, through optimal performance to impulsive states, and eventually lose inhibition-driven winner-take-all behavior: all are clear outcomes of the bifurcation structure. We illustrate the value of reduced models by a study of the speed-accuracy tradeoff in decision making. The ability of such models to recreate neuromodulatory dynamics of the spiking network will accelerate the pace of future experiments linking behavioral data to cellular neurophysiology.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:21344
Deposited By:Dr Kongfatt Wong-Lin
Deposited On:09 Mar 2012 15:00
Last Modified:26 Nov 2012 11:58

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