dc.contributor.author | Rankin, J | |
dc.contributor.author | Chavane, F | |
dc.date.accessioned | 2017-11-16T09:58:01Z | |
dc.date.issued | 2017-10-24 | |
dc.description.abstract | Voltage-sensitive dye imaging experiments in primary visual cortex (V1) have shown that local, oriented visual stimuli elicit stable orientation-selective activation within the stimulus retinotopic footprint. The cortical activation dynamically extends far beyond the retinotopic footprint, but the peripheral spread stays non-selective—a surprising finding given a number of anatomo-functional studies showing the orientation specificity of long-range connections. Here we use a computational model to investigate this apparent discrepancy by studying the expected population response using known published anatomical constraints. The dynamics of input-driven localized states were simulated in a planar neural field model with multiple sub-populations encoding orientation. The realistic connectivity profile has parameters controlling the clustering of long-range connections and their orientation bias. We found substantial overlap between the anatomically relevant parameter range and a steep decay in orientation selective activation that is consistent with the imaging experiments. In this way our study reconciles the reported orientation bias of long-range connections with the functional expression of orientation selective neural activity. Our results demonstrate this sharp decay is contingent on three factors, that long-range connections are sufficiently diffuse, that the orientation bias of these connections is in an intermediate range (consistent with anatomy) and that excitation is sufficiently balanced by inhibition. Conversely, our modelling results predict that, for reduced inhibition strength, spurious orientation selective activation could be generated through long-range lateral connections. Furthermore, if the orientation bias of lateral connections is very strong, or if inhibition is particularly weak, the network operates close to an instability leading to unbounded cortical activation. | en_GB |
dc.description.sponsorship | R was supported at NYU on a postdoc fellowship from the Swartz Foundation. FC is supported by ANR project BalaV1 (ANR-13-BSV4-0014-02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. | en_GB |
dc.identifier.citation | Vol. 13 (10), article e1005821 | en_GB |
dc.identifier.doi | 10.1371/journal.pcbi.1005821 | |
dc.identifier.uri | http://hdl.handle.net/10871/30322 | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science for International Society for Computational Biology (ISCB) | en_GB |
dc.relation.source | All relevant information to reproduce the results are within the paper. Model code allowing for independent reproduction of the results is available in the supplemental information (S1 Code) and on the following online repository https://github.com/QBME/rankin-chavane-neural-field/. | en_GB |
dc.rights | Copyright: © 2017 Rankin, Chavane. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_GB |
dc.title | Neural field model to reconcile structure with function in primary visual cortex | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2017-11-16T09:58:01Z | |
dc.contributor.editor | Hilgetag, CC | en_GB |
dc.description | This is the final version of the article. Available from Public Library of Science via the DOI in this record. | en_GB |
dc.identifier.journal | PLOS Computational Biology | en_GB |