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Hebbian cross-correlation learning emerges as spike timing dependent plasticity

Hebbian cross-correlation learning emerges as spike timing dependent plasticity olde Scheper et al. BMC Neuroscience 2011, 12(Suppl 1):P355 http://www.biomedcentral.com/1471-2202/12/S1/P355 POSTER PRESENTATION Open Access Hebbian cross-correlation learning emerges as spike timing dependent plasticity 1,2* 1 1 1 1 Tjeerd olde Scheper , Rhiannon Meredith , Huibert Mansvelder , Jaap van Pelt , Arjen van Ooyen From Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011 In Donald O. Hebb’s oft quoted thesis on synaptic plas- Plasticity learning emerges. Due to the dynamic nature ticity, the change in efficacy in proportion to the degree of the autonomous learning rule, it responds in a simple of correlation between pre- and post-synaptic activity is feed-forward manner to the synaptic input in combina- expressed explicitly. The Hebbian learning rule has been tion to the localised post-synaptic activity. This pre- demonstrated in simulations to be reliable and effective cludes the need to perform spike matching and post- and appears to have a solid foundation in biology on the processing of the simulation and is more biologically basis of experimental results. However, beyond binary relevant. simulation models of the Spike Timing Dependent Plas- The relation between the local dynamics of a single ticity (STDP) rule, it has not been demonstrated that synapse and the localised dynamics due to post-synaptic the causal correlation property of synaptic plasticity is activity becomes apparent by different emerging learning as valid and as effective as always has been assumed. rules. The presence of action potentials and synaptic To clarify the exact nature of learning by means of inhibition can change the shape of the STDP learning spike timing dependent plasticity, a dynamic model has rule even to the extent that a Hebbian learning rule may been developed based on the cross-correlation between become anti-Hebbian and vice versa. The synapse can pre- and post-synaptic activity as expressed by a respond to external input as well as compete with other dynamic activity measure. The components that form synapses and tune itself to the local dendritic activity the model are centered around the following guiding and the global neuronal activity. principles. Firstly, the cross-correlation between local Synaptic adaptation due to the presence of nearby synaptic pre- and post-synaptic activity, as induced by synapses and global activity has previously not been the synapse itself in the post-synaptic cell, determines extensively studied. This work shows that synapses are the strength of the potential for synaptic depression. not mere slaves to the input but perform more complex Even though this may appear to be counter-intuitive, it computations by combining the input with the local reflects the depression due to pre-synaptic activity if lit- post-synaptic activity as well as the global dynamics due tle or no subsequent post-synaptic activity is present. to other synapses and action potentials. The second component is the post-synaptic activity induced by the synapse locally. This represents the local Author details response to synaptic input. The third component is the Department of Integrative Neurophysiology, Center for Neurogenomics and cross-correlation of the post-synaptic activity induced by Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands. Department of Computing, Oxford the synapse with other post-synaptic activity contribut- Brookes University, Wheatley Campus, Oxford, OX33 1HX, UK. ing factors such as an action potential and other synapses. These three components form the autono- Published: 18 July 2011 mous learning rule from which Spike Timing Dependent doi:10.1186/1471-2202-12-S1-P355 * Correspondence: tjeerd.olde.scheper@cncr.vu.nl Cite this article as: olde Scheper et al.: Hebbian cross-correlation Department of Integrative Neurophysiology, Center for Neurogenomics and learning emerges as spike timing dependent plasticity. BMC Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Neuroscience 2011 12(Suppl 1):P355. 1081 HV, Amsterdam, The Netherlands Full list of author information is available at the end of the article © 2011 olde Scheper et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Neuroscience Springer Journals

Hebbian cross-correlation learning emerges as spike timing dependent plasticity

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Springer Journals
Copyright
Copyright © 2011 by olde Scheper et al; licensee BioMed Central Ltd.
Subject
Biomedicine; Neurosciences; Neurobiology; Animal Models
eISSN
1471-2202
DOI
10.1186/1471-2202-12-S1-P355
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Abstract

olde Scheper et al. BMC Neuroscience 2011, 12(Suppl 1):P355 http://www.biomedcentral.com/1471-2202/12/S1/P355 POSTER PRESENTATION Open Access Hebbian cross-correlation learning emerges as spike timing dependent plasticity 1,2* 1 1 1 1 Tjeerd olde Scheper , Rhiannon Meredith , Huibert Mansvelder , Jaap van Pelt , Arjen van Ooyen From Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011 In Donald O. Hebb’s oft quoted thesis on synaptic plas- Plasticity learning emerges. Due to the dynamic nature ticity, the change in efficacy in proportion to the degree of the autonomous learning rule, it responds in a simple of correlation between pre- and post-synaptic activity is feed-forward manner to the synaptic input in combina- expressed explicitly. The Hebbian learning rule has been tion to the localised post-synaptic activity. This pre- demonstrated in simulations to be reliable and effective cludes the need to perform spike matching and post- and appears to have a solid foundation in biology on the processing of the simulation and is more biologically basis of experimental results. However, beyond binary relevant. simulation models of the Spike Timing Dependent Plas- The relation between the local dynamics of a single ticity (STDP) rule, it has not been demonstrated that synapse and the localised dynamics due to post-synaptic the causal correlation property of synaptic plasticity is activity becomes apparent by different emerging learning as valid and as effective as always has been assumed. rules. The presence of action potentials and synaptic To clarify the exact nature of learning by means of inhibition can change the shape of the STDP learning spike timing dependent plasticity, a dynamic model has rule even to the extent that a Hebbian learning rule may been developed based on the cross-correlation between become anti-Hebbian and vice versa. The synapse can pre- and post-synaptic activity as expressed by a respond to external input as well as compete with other dynamic activity measure. The components that form synapses and tune itself to the local dendritic activity the model are centered around the following guiding and the global neuronal activity. principles. Firstly, the cross-correlation between local Synaptic adaptation due to the presence of nearby synaptic pre- and post-synaptic activity, as induced by synapses and global activity has previously not been the synapse itself in the post-synaptic cell, determines extensively studied. This work shows that synapses are the strength of the potential for synaptic depression. not mere slaves to the input but perform more complex Even though this may appear to be counter-intuitive, it computations by combining the input with the local reflects the depression due to pre-synaptic activity if lit- post-synaptic activity as well as the global dynamics due tle or no subsequent post-synaptic activity is present. to other synapses and action potentials. The second component is the post-synaptic activity induced by the synapse locally. This represents the local Author details response to synaptic input. The third component is the Department of Integrative Neurophysiology, Center for Neurogenomics and cross-correlation of the post-synaptic activity induced by Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands. Department of Computing, Oxford the synapse with other post-synaptic activity contribut- Brookes University, Wheatley Campus, Oxford, OX33 1HX, UK. ing factors such as an action potential and other synapses. These three components form the autono- Published: 18 July 2011 mous learning rule from which Spike Timing Dependent doi:10.1186/1471-2202-12-S1-P355 * Correspondence: tjeerd.olde.scheper@cncr.vu.nl Cite this article as: olde Scheper et al.: Hebbian cross-correlation Department of Integrative Neurophysiology, Center for Neurogenomics and learning emerges as spike timing dependent plasticity. BMC Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Neuroscience 2011 12(Suppl 1):P355. 1081 HV, Amsterdam, The Netherlands Full list of author information is available at the end of the article © 2011 olde Scheper et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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BMC Neuroscience – Springer Journals

Published: Jul 18, 2011

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