dc.contributor.author |
Deco, Gustavo |
dc.contributor.author |
Hugues, Etienne |
dc.date |
2016-02-16 |
dc.identifier.citation |
Deco G, Hugues E. Neural network mechanisms underlying stimulus driven variability reduction. PLoS Computational Biology. 2012;8(3):1-10. DOI: 10.1371/journal.pcbi.1002395. |
dc.identifier.citation |
1553-734X |
dc.identifier.citation |
http://dx.doi.org/10.1371/journal.pcbi.1002395 |
dc.identifier.uri |
http://hdl.handle.net/10230/25841 |
dc.format |
application/pdf |
dc.language.iso |
eng |
dc.publisher |
Public Library of Science |
dc.relation |
PLoS Computational Biology. 2012;8(3):1-10. |
dc.relation |
info:eu-repo/grantAgreement/EC/FP7/200728 |
dc.relation |
info:eu-repo/grantAgreement/EC/FP7/269921 |
dc.relation |
info:eu-repo/grantAgreement/ES/3PN/SAF2010-16085 |
dc.relation |
info:eu-repo/grantAgreement/ES/2PN/CSD2007-00012 |
dc.rights |
@2012 Deco and Hugues. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits/nunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.rights |
http://creativecommons.org/licenses/by/4.0/ |
dc.title |
Neural network mechanisms underlying stimulus driven variability reduction |
dc.type |
info:eu-repo/semantics/article |
dc.type |
info:eu-repo/semantics/publishedVersion |
dc.description.abstract |
It is well established that the variability of the neural activity across trials, as measured by the Fano factor, is elevated. This/nfact poses limits on information encoding by the neural activity. However, a series of recent neurophysiological experiments/nhave changed this traditional view. Single cell recordings across a variety of species, brain areas, brain states and stimulus/nconditions demonstrate a remarkable reduction of the neural variability when an external stimulation is applied and when/nattention is allocated towards a stimulus within a neuron’s receptive field, suggesting an enhancement of information/nencoding. Using an heterogeneously connected neural network model whose dynamics exhibits multiple attractors, we/ndemonstrate here how this variability reduction can arise from a network effect. In the spontaneous state, we show that the/nhigh degree of neural variability is mainly due to fluctuation-driven excursions from attractor to attractor. This occurs when,/nin the parameter space, the network working point is around the bifurcation allowing multistable attractors. The application/nof an external excitatory drive by stimulation or attention stabilizes one specific attractor, eliminating in this way the/ntransitions between the different attractors and resulting in a net decrease in neural variability over trials. Importantly, nonresponsive/nneurons also exhibit a reduction of variability. Finally, this reduced variability is found to arise from an increased/nregularity of the neural spike trains. In conclusion, these results suggest that the variability reduction under stimulation and/nattention is a property of neural circuits |
dc.description.abstract |
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreements HEALTH F2 2008 200728 (Brainsync) and no. 269921 (BrainScaleS), from the Spanish Research Project SAF2010-16085 and from the CONSOLIDER-INGENIO 2010 Programme CSD2007-00012. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. |