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Estimating the contribution of assembly activity to cortical dynamics from spike and population measures
The hypothesis that cortical networks employ the coordinated activity of groups of neurons, termed assemblies, to process information is debated. Results from multiple single-unit recordings are not conclusive because of the dramatic undersampling of the system. However, the local field potential (L...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Springer US
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978895/ https://www.ncbi.nlm.nih.gov/pubmed/20480218 http://dx.doi.org/10.1007/s10827-010-0241-8 |
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author | Denker, Michael Riehle, Alexa Diesmann, Markus Grün, Sonja |
author_facet | Denker, Michael Riehle, Alexa Diesmann, Markus Grün, Sonja |
author_sort | Denker, Michael |
collection | PubMed |
description | The hypothesis that cortical networks employ the coordinated activity of groups of neurons, termed assemblies, to process information is debated. Results from multiple single-unit recordings are not conclusive because of the dramatic undersampling of the system. However, the local field potential (LFP) is a mesoscopic signal reflecting synchronized network activity. This raises the question whether the LFP can be employed to overcome the problem of undersampling. In a recent study in the motor cortex of the awake behaving monkey based on the locking of coincidences to the LFP we determined a lower bound for the fraction of spike coincidences originating from assembly activation. This quantity together with the locking of single spikes leads to a lower bound for the fraction of spikes originating from any assembly activity. Here we derive a statistical method to estimate the fraction of spike synchrony caused by assemblies—not its lower bound—from the spike data alone. A joint spike and LFP surrogate data model demonstrates consistency of results and the sensitivity of the method. Combining spike and LFP signals, we obtain an estimate of the fraction of spikes resulting from assemblies in the experimental data. |
format | Text |
id | pubmed-2978895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-29788952010-12-08 Estimating the contribution of assembly activity to cortical dynamics from spike and population measures Denker, Michael Riehle, Alexa Diesmann, Markus Grün, Sonja J Comput Neurosci Article The hypothesis that cortical networks employ the coordinated activity of groups of neurons, termed assemblies, to process information is debated. Results from multiple single-unit recordings are not conclusive because of the dramatic undersampling of the system. However, the local field potential (LFP) is a mesoscopic signal reflecting synchronized network activity. This raises the question whether the LFP can be employed to overcome the problem of undersampling. In a recent study in the motor cortex of the awake behaving monkey based on the locking of coincidences to the LFP we determined a lower bound for the fraction of spike coincidences originating from assembly activation. This quantity together with the locking of single spikes leads to a lower bound for the fraction of spikes originating from any assembly activity. Here we derive a statistical method to estimate the fraction of spike synchrony caused by assemblies—not its lower bound—from the spike data alone. A joint spike and LFP surrogate data model demonstrates consistency of results and the sensitivity of the method. Combining spike and LFP signals, we obtain an estimate of the fraction of spikes resulting from assemblies in the experimental data. Springer US 2010-05-18 2010 /pmc/articles/PMC2978895/ /pubmed/20480218 http://dx.doi.org/10.1007/s10827-010-0241-8 Text en © The Author(s) 2010 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Article Denker, Michael Riehle, Alexa Diesmann, Markus Grün, Sonja Estimating the contribution of assembly activity to cortical dynamics from spike and population measures |
title | Estimating the contribution of assembly activity to cortical dynamics from spike and population measures |
title_full | Estimating the contribution of assembly activity to cortical dynamics from spike and population measures |
title_fullStr | Estimating the contribution of assembly activity to cortical dynamics from spike and population measures |
title_full_unstemmed | Estimating the contribution of assembly activity to cortical dynamics from spike and population measures |
title_short | Estimating the contribution of assembly activity to cortical dynamics from spike and population measures |
title_sort | estimating the contribution of assembly activity to cortical dynamics from spike and population measures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978895/ https://www.ncbi.nlm.nih.gov/pubmed/20480218 http://dx.doi.org/10.1007/s10827-010-0241-8 |
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