Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/6192

Dynamics of neural networks with continuous attractors

Authors Fung, C.C.A.
Wong, K.Y.M.
Wu, S.
Issue Date 2008
Source Europhysics letters , v. 84, (1), 2008, Oct, article number 18002
Summary We investigate the dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of their neuronal interactions, CANNs can hold a continuous family of stationary states. We systematically explore how their neutral stability facilitates the tracking performance of a CANN, which is believed to have wide applications in brain functions. We develop a perturbative approach that utilizes the dominant movement of the network stationary states in the state space. We quantify the distortions of the bump shape during tracking, and study their effects on the tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable, and the reaction time to catch up an abrupt change in stimulus. Copyright © 2008 EPLA.
Subjects
ISSN 0295-5075
Rights Europhysics letters © copyright (2008) IOP Publishing Ltd. The Journal's web site is located at http://www.iop.org/EJ/journal/EPL
Language English
Format Article
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