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Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

Bush, D; Philippides, A; Husbands, P; O'Shea, M; (2010) Dual coding with STDP in a spiking recurrent neural network model of the hippocampus. PLoS Comput Biol , 6 (7) , Article e1000839. 10.1371/journal.pcbi.1000839. Green open access

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Abstract

The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain.

Type: Article
Title: Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pcbi.1000839
Publisher version: http://dx.doi.org/10.1371/journal.pcbi.1000839
Language: English
Additional information: © 2010 Bush et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: DB was initially supported by the BBSRC, then partly by Wellcome VIP funding and the EU-FP7 project E-Flux. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Keywords: Axons, CA3 Region, Hippocampal, Computer Simulation, Learning, Memory, Models, Neurological, Nerve Net, Neuronal Plasticity, Statistics, Nonparametric, Synapses, Theta Rhythm
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Experimental Epilepsy
URI: https://discovery.ucl.ac.uk/id/eprint/1335080
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