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Neural masses and fields: modeling the dynamics of brain activity

Pinotsis, D. A. ORCID: 0000-0002-6865-8103, Robinson, P., Graben, P. B. & Friston, K. J. (2013). Neural masses and fields: modeling the dynamics of brain activity. Frontiers in Computational Neuroscience, 8(NOV), article number 149. doi: 10.3389/fncom.2014.00149

Abstract

This technical note introduces a conductance-based neural field model that combines biologically realistic synaptic dynamics—based on transmembrane currents—with neural field equations, describing the propagation of spikes over the cortical surface. This model allows for fairly realistic inter-and intra-laminar intrinsic connections that underlie spatiotemporal neuronal dynamics. We focus on the response functions of expected neuronal states (such as depolarization) that generate observed electrophysiological signals (like LFP recordings and EEG). These response functions characterize the model's transfer functions and implicit spectral responses to (uncorrelated) input. Our main finding is that both the evoked responses (impulse response functions) and induced responses (transfer functions) show qualitative differences depending upon whether one uses a neural mass or field model. Furthermore, there are differences between the equivalent convolution and conductance models. Overall, all models reproduce a characteristic increase in frequency, when inhibition was increased by increasing the rate constants of inhibitory populations. However, convolution and conductance-based models showed qualitatively different changes in power, with convolution models showing decreases with increasing inhibition, while conductance models show the opposite effect. These differences suggest that conductance based field models may be important in empirical studies of cortical gain control or pharmacological manipulations.

Publication Type: Article
Additional Information: © 2013 Pinotsis, Leite and Friston. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Publisher Keywords: neural field theory, mean field modeling, electrophysiology, conductance based models, dynamic causal modeling
Departments: School of Health & Psychological Sciences > Psychology
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