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Real time computation: zooming in on population codes

Rochel, O. and Cohen, N. (2007) Real time computation: zooming in on population codes. BioSystems, 87 (2). pp. 260-266. ISSN 0303-2647

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Abstract

Information processing in nervous systems intricately combines computation at the neuronal and network levels. Many computations may be envisioned as sequences of signal processing steps along some pathway. How can information encoded by single cells be mapped onto network population codes, and how do different modules or layers in the computation synchronize their communication and computation? These fundamental questions are particularly severe when dealing with real time streams of inputs. Here we study this problem within the context of a minimal signal perception task. In particular, we encode neuronal information by externally applying a space- and time-localized stimulus to individual neurons within a network. We show that a pulse-coupled recurrent neural network can successfully handle this task in real time, and obeys three key requirements: (i) stimulus dependence, (ii) initial-conditions independence, and (iii) accessibility by a readout mechanism. In particular, we suggest that the network’s overall level of activity can be used as a temporal cue for a robust readout mechanism. Within this framework, the network can rapidly map a local stimulus onto a population code that can then be reliably read out during some narrow but well defined window of time. © 2006 Elsevier Ireland Ltd. All rights reserved.

Item Type: Article
Copyright, Publisher and Additional Information: Papers presented at the Sixth International Workshop on Information Processing in Cells and Tissues, York, UK, 2005 - IPCAT 2005, Information Processing in Cells and Tissues.
Keywords: Pulsed neural networks; Recurrent networks; Active memory; Signal perception; Computer simulations
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)
Depositing User: Miss Jamie Grant
Date Deposited: 12 Mar 2009 17:08
Last Modified: 24 Jun 2014 09:34
Published Version: http://dx.doi.org/10.1016/j.biosystems.2006.09.021
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.biosystems.2006.09.021
URI: http://eprints.whiterose.ac.uk/id/eprint/7953

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