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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...

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Autores principales: Pinotsis, D.A., Geerts, J.P., Pinto, L., FitzGerald, T.H.B., Litvak, V., Auksztulewicz, R., Friston, K.J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2017
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.
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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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