Identifying neural drivers with functional MRI: an electrophysiological validation.

Whether functional magnetic resonance imaging (fMRI) allows the identification of neural drivers remains an open question of particular importance to refine physiological and neuropsychological models of the brain, and/or to understand neurophysiopathology. Here, in a rat model of absence epilepsy s...

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Autores principales:	Olivier David, Isabelle Guillemain, Sandrine Saillet, Sebastien Reyt, Colin Deransart, Christoph Segebarth, Antoine Depaulis
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2008
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/52c11011d9d04835b3a12cc86e0e837d
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spelling	oai:doaj.org-article:52c11011d9d04835b3a12cc86e0e837d2021-11-25T05:33:53ZIdentifying neural drivers with functional MRI: an electrophysiological validation.1544-91731545-788510.1371/journal.pbio.0060315https://doaj.org/article/52c11011d9d04835b3a12cc86e0e837d2008-12-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19108604/?tool=EBIhttps://doaj.org/toc/1544-9173https://doaj.org/toc/1545-7885Whether functional magnetic resonance imaging (fMRI) allows the identification of neural drivers remains an open question of particular importance to refine physiological and neuropsychological models of the brain, and/or to understand neurophysiopathology. Here, in a rat model of absence epilepsy showing spontaneous spike-and-wave discharges originating from the first somatosensory cortex (S1BF), we performed simultaneous electroencephalographic (EEG) and fMRI measurements, and subsequent intracerebral EEG (iEEG) recordings in regions strongly activated in fMRI (S1BF, thalamus, and striatum). fMRI connectivity was determined from fMRI time series directly and from hidden state variables using a measure of Granger causality and Dynamic Causal Modelling that relates synaptic activity to fMRI. fMRI connectivity was compared to directed functional coupling estimated from iEEG using asymmetry in generalised synchronisation metrics. The neural driver of spike-and-wave discharges was estimated in S1BF from iEEG, and from fMRI only when hemodynamic effects were explicitly removed. Functional connectivity analysis applied directly on fMRI signals failed because hemodynamics varied between regions, rendering temporal precedence irrelevant. This paper provides the first experimental substantiation of the theoretical possibility to improve interregional coupling estimation from hidden neural states of fMRI. As such, it has important implications for future studies on brain connectivity using functional neuroimaging.Olivier DavidIsabelle GuillemainSandrine SailletSebastien ReytColin DeransartChristoph SegebarthAntoine DepaulisPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Biology, Vol 6, Iss 12, Pp 2683-2697 (2008)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Olivier David Isabelle Guillemain Sandrine Saillet Sebastien Reyt Colin Deransart Christoph Segebarth Antoine Depaulis Identifying neural drivers with functional MRI: an electrophysiological validation.
description	Whether functional magnetic resonance imaging (fMRI) allows the identification of neural drivers remains an open question of particular importance to refine physiological and neuropsychological models of the brain, and/or to understand neurophysiopathology. Here, in a rat model of absence epilepsy showing spontaneous spike-and-wave discharges originating from the first somatosensory cortex (S1BF), we performed simultaneous electroencephalographic (EEG) and fMRI measurements, and subsequent intracerebral EEG (iEEG) recordings in regions strongly activated in fMRI (S1BF, thalamus, and striatum). fMRI connectivity was determined from fMRI time series directly and from hidden state variables using a measure of Granger causality and Dynamic Causal Modelling that relates synaptic activity to fMRI. fMRI connectivity was compared to directed functional coupling estimated from iEEG using asymmetry in generalised synchronisation metrics. The neural driver of spike-and-wave discharges was estimated in S1BF from iEEG, and from fMRI only when hemodynamic effects were explicitly removed. Functional connectivity analysis applied directly on fMRI signals failed because hemodynamics varied between regions, rendering temporal precedence irrelevant. This paper provides the first experimental substantiation of the theoretical possibility to improve interregional coupling estimation from hidden neural states of fMRI. As such, it has important implications for future studies on brain connectivity using functional neuroimaging.
format	article
author	Olivier David Isabelle Guillemain Sandrine Saillet Sebastien Reyt Colin Deransart Christoph Segebarth Antoine Depaulis
author_facet	Olivier David Isabelle Guillemain Sandrine Saillet Sebastien Reyt Colin Deransart Christoph Segebarth Antoine Depaulis
author_sort	Olivier David
title	Identifying neural drivers with functional MRI: an electrophysiological validation.
title_short	Identifying neural drivers with functional MRI: an electrophysiological validation.
title_full	Identifying neural drivers with functional MRI: an electrophysiological validation.
title_fullStr	Identifying neural drivers with functional MRI: an electrophysiological validation.
title_full_unstemmed	Identifying neural drivers with functional MRI: an electrophysiological validation.
title_sort	identifying neural drivers with functional mri: an electrophysiological validation.
publisher	Public Library of Science (PLoS)
publishDate	2008
url	https://doaj.org/article/52c11011d9d04835b3a12cc86e0e837d
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Identifying neural drivers with functional MRI: an electrophysiological validation.

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