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

Dimitris Pinotsis; Karl Friston; Dimitris Pinotsis; Karl Friston

doi:10.3934/Neuroscience.2014.1.18

AIMS Neuroscience

2014, Volume 1, Issue 1: 18-38. doi: 10.3934/Neuroscience.2014.1.18

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Theory article Special Issues

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

Dimitris Pinotsis ^,,
Karl Friston

The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG

Received: 24 February 2014 Accepted: 17 April 2014 Published: 10 May 2014

This paper shows how gamma oscillations can be combined with neural population models and dynamic causal modeling (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 simulate 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 quantitatively—to fit 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.
- Neural field theory,
- dynamic causal modeling,
- contrast,
- attention,
- gamma oscillations,
- electrocorticography,
- Visual Cortex,
- electrophysiology,
- MEG,
- connectivity
Citation: Dimitris Pinotsis, Karl Friston. Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure[J]. AIMS Neuroscience, 2014, 1(1): 18-38. doi: 10.3934/Neuroscience.2014.1.18

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Abstract

This paper shows how gamma oscillations can be combined with neural population models and dynamic causal modeling (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 simulate 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 quantitatively—to fit 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.

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