A Model Of Power Spectral Density In Cortical
EEG, For The Study Of Cortical Connectivity
Author(s)
M. Zavaglia, E. Magosso, L. Astolfi, F. Babiloni & M. Ursino
Abstract
Neural mass models have been used for many years to study the dynamics of
neural groups, or of entire cortical areas, in a simple and computationally
inexpensive way. In this paper, we modified a model proposed by Wendling
et al. [6] to analyze EEG power density in some cortical areas during a simple
task (finger movement). The work consists of three subsequent stages: 1) in the
first we performed a sensitivity analysis of the main model parameters (i.e.,
strength of inhibitory and excitatory synapses and their time constants) and
evaluated their role in affecting power spectral density (PSD). This analysis
confirmed the possibility to simulate various EEG rhythms by modifying just the
strength and time constants of a few synapses. However, a single neural mass
model produces a narrow frequency band, which cannot mimic the overall
complexity of EEG in an entire cortical area. 2) Hence, in the second stage we
built a model of a region of interest (ROI) by combining three neural mass
models arranged in parallel. With this model, and using an automatic fitting
procedure to establish parameter values, we carefully reproduced the PSD of
cortical EEG in six ROIs during finger movement. Cortical EEGs were
computed with an inverse propagation model, starting from measurement
performed with 128 electrodes on the scalp. 3) In the third stage, we simulated
how PSD in some ROIs can be modified, as a consequence of some hypothetical
functional connectivity among the regions.
Results show that the proposed model is able to mimic PSD of cortical
activity acting on a few parameters only. The pattern of power spectra, however,
is significantly modified by a functional connectivity among the ROIs.
Knowledge obtained from the model may be exploited to derive information
on functional connectivity, starting from non-invasive EEG measurements.
Keywords: neural models, brain connectivity, intracerebral EEG.
Keywords
neural models, brain connectivity, intracerebral EEG.
Related Book
Other papers in this volume
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