Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure

This paper shows how gamma oscillations can be combined with neural population models and <em>dynamic causal modeling</em> (DCM) to distinguish among alternative hypotheses regarding cortical excitability and microstructure. This approach exploits inter-subject variability and trial-spec...

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Main Authors: Dimitris Pinotsis, Karl Friston
Format: Article
Language:English
Published: AIMS Press 2014-05-01
Series:AIMS Neuroscience
Subjects:
MEG
Online Access:http://www.aimspress.com/neuroscience/article/108/fulltext.html
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spelling doaj-11ab8aa37e094dcbad14bc60dec894752020-11-25T01:58:29ZengAIMS PressAIMS Neuroscience2373-79722014-05-0111183810.3934/Neuroscience.2014.1.1820140103Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and MicrostructureDimitris Pinotsis0Karl Friston1The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BGThe Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BGThis paper shows how gamma oscillations can be combined with neural population models and <em>dynamic causal modeling</em> (DCM) to distinguish among alternative hypotheses regarding cortical excitability and microstructure. This approach exploits inter-subject variability and trial-specific effects associated with modulations in the peak frequency of gamma oscillations. Neural field models are used to evaluate model evidence and obtain parameter estimates using invasive and non-invasive gamma recordings. Our overview comprises two parts: in the first part, we use neural fields to <em>simulate</em> neural activity and distinguish the effects of post synaptic filtering on predicted responses in terms of synaptic rate constants that correspond to different timescales and distinct neurotransmitters. We focus on model predictions of conductance and convolution based field models and show that these can yield spectral responses that are sensitive to biophysical properties of local cortical circuits like synaptic kinetics and filtering; we also consider two different mechanisms for this filtering: a nonlinear mechanism involving specific conductances and a linear convolution of afferent firing rates producing post synaptic potentials. In the second part of this paper, we use neural fields <em>quantitatively</em>—to <em>fit</em> empirical data recorded during visual stimulation. We present two studies of spectral responses obtained from the visual cortex during visual perception experiments: in the first study, MEG data were acquired during a task designed to show how activity in the gamma band is related to visual perception, while in the second study, we exploited high density electrocorticographic (ECoG) data to study the effect of varying stimulus contrast on cortical excitability and gamma peak frequency.http://www.aimspress.com/neuroscience/article/108/fulltext.htmlNeural field theorydynamic causal modelingcontrastattentiongamma oscillationselectrocorticographyVisual CortexelectrophysiologyMEGconnectivity
collection DOAJ
language English
format Article
sources DOAJ
author Dimitris Pinotsis
Karl Friston
spellingShingle Dimitris Pinotsis
Karl Friston
Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure
AIMS Neuroscience
Neural field theory
dynamic causal modeling
contrast
attention
gamma oscillations
electrocorticography
Visual Cortex
electrophysiology
MEG
connectivity
author_facet Dimitris Pinotsis
Karl Friston
author_sort Dimitris Pinotsis
title Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure
title_short Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure
title_full Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure
title_fullStr Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure
title_full_unstemmed Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure
title_sort gamma oscillations and neural field dcms can reveal cortical excitability and microstructure
publisher AIMS Press
series AIMS Neuroscience
issn 2373-7972
publishDate 2014-05-01
description This paper shows how gamma oscillations can be combined with neural population models and <em>dynamic causal modeling</em> (DCM) to distinguish among alternative hypotheses regarding cortical excitability and microstructure. This approach exploits inter-subject variability and trial-specific effects associated with modulations in the peak frequency of gamma oscillations. Neural field models are used to evaluate model evidence and obtain parameter estimates using invasive and non-invasive gamma recordings. Our overview comprises two parts: in the first part, we use neural fields to <em>simulate</em> neural activity and distinguish the effects of post synaptic filtering on predicted responses in terms of synaptic rate constants that correspond to different timescales and distinct neurotransmitters. We focus on model predictions of conductance and convolution based field models and show that these can yield spectral responses that are sensitive to biophysical properties of local cortical circuits like synaptic kinetics and filtering; we also consider two different mechanisms for this filtering: a nonlinear mechanism involving specific conductances and a linear convolution of afferent firing rates producing post synaptic potentials. In the second part of this paper, we use neural fields <em>quantitatively</em>—to <em>fit</em> empirical data recorded during visual stimulation. We present two studies of spectral responses obtained from the visual cortex during visual perception experiments: in the first study, MEG data were acquired during a task designed to show how activity in the gamma band is related to visual perception, while in the second study, we exploited high density electrocorticographic (ECoG) data to study the effect of varying stimulus contrast on cortical excitability and gamma peak frequency.
topic Neural field theory
dynamic causal modeling
contrast
attention
gamma oscillations
electrocorticography
Visual Cortex
electrophysiology
MEG
connectivity
url http://www.aimspress.com/neuroscience/article/108/fulltext.html
work_keys_str_mv AT dimitrispinotsis gammaoscillationsandneuralfielddcmscanrevealcorticalexcitabilityandmicrostructure
AT karlfriston gammaoscillationsandneuralfielddcmscanrevealcorticalexcitabilityandmicrostructure
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