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Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings
Neural models describe brain activity at different scales, ranging from single cells to whole brain networks. Here, we attempt to reconcile models operating at the microscopic (compartmental) and mesoscopic (neural mass) scales to analyse data from microelectrode recordings of intralaminar neural ac...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academic Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5312791/ https://www.ncbi.nlm.nih.gov/pubmed/27871922 http://dx.doi.org/10.1016/j.neuroimage.2016.11.041 |
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author | Pinotsis, D.A. Geerts, J.P. Pinto, L. FitzGerald, T.H.B. Litvak, V. Auksztulewicz, R. Friston, K.J. |
author_facet | Pinotsis, D.A. Geerts, J.P. Pinto, L. FitzGerald, T.H.B. Litvak, V. Auksztulewicz, R. Friston, K.J. |
author_sort | Pinotsis, D.A. |
collection | PubMed |
description | Neural models describe brain activity at different scales, ranging from single cells to whole brain networks. Here, we attempt to reconcile models operating at the microscopic (compartmental) and mesoscopic (neural mass) scales to analyse data from microelectrode recordings of intralaminar neural activity. Although these two classes of models operate at different scales, it is relatively straightforward to create neural mass models of ensemble activity that are equipped with priors obtained after fitting data generated by detailed microscopic models. This provides generative (forward) models of measured neuronal responses that retain construct validity in relation to compartmental models. We illustrate our approach using cross spectral responses obtained from V1 during a visual perception paradigm that involved optogenetic manipulation of the basal forebrain. We find that the resulting neural mass model can distinguish between activity in distinct cortical layers – both with and without optogenetic activation – and that cholinergic input appears to enhance (disinhibit) superficial layer activity relative to deep layers. This is particularly interesting from the perspective of predictive coding, where neuromodulators are thought to boost prediction errors that ascend the cortical hierarchy. |
format | Online Article Text |
id | pubmed-5312791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Academic Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-53127912017-02-22 Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings Pinotsis, D.A. Geerts, J.P. Pinto, L. FitzGerald, T.H.B. Litvak, V. Auksztulewicz, R. Friston, K.J. Neuroimage Article Neural models describe brain activity at different scales, ranging from single cells to whole brain networks. Here, we attempt to reconcile models operating at the microscopic (compartmental) and mesoscopic (neural mass) scales to analyse data from microelectrode recordings of intralaminar neural activity. Although these two classes of models operate at different scales, it is relatively straightforward to create neural mass models of ensemble activity that are equipped with priors obtained after fitting data generated by detailed microscopic models. This provides generative (forward) models of measured neuronal responses that retain construct validity in relation to compartmental models. We illustrate our approach using cross spectral responses obtained from V1 during a visual perception paradigm that involved optogenetic manipulation of the basal forebrain. We find that the resulting neural mass model can distinguish between activity in distinct cortical layers – both with and without optogenetic activation – and that cholinergic input appears to enhance (disinhibit) superficial layer activity relative to deep layers. This is particularly interesting from the perspective of predictive coding, where neuromodulators are thought to boost prediction errors that ascend the cortical hierarchy. Academic Press 2017-02-01 /pmc/articles/PMC5312791/ /pubmed/27871922 http://dx.doi.org/10.1016/j.neuroimage.2016.11.041 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pinotsis, D.A. Geerts, J.P. Pinto, L. FitzGerald, T.H.B. Litvak, V. Auksztulewicz, R. Friston, K.J. Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings |
title | Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings |
title_full | Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings |
title_fullStr | Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings |
title_full_unstemmed | Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings |
title_short | Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings |
title_sort | linking canonical microcircuits and neuronal activity: dynamic causal modelling of laminar recordings |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5312791/ https://www.ncbi.nlm.nih.gov/pubmed/27871922 http://dx.doi.org/10.1016/j.neuroimage.2016.11.041 |
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