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Updated: Aug 16, 2026
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
A comparative study of a theoretical neural net model with MEG data from epileptic patients and normal individuals
A Kotini1, P Anninos, A N Anastasiadis
1Laboratory of Medical Physics, Democritus University of Thrace, Medical School, Alex/polis, 68100, Greece. akotin@axd.forthnet.gr
Objective:
The aim of this study was to compare a theoretical neural net model with MEG data from epileptic patients and normal individuals.
Methods:
Our experimental study population included 10 epilepsy sufferers and 10 healthy subjects. The recordings were obtained with a one-channel biomagnetometer SQUID in a magnetically shielded room.
Results:
Using the method of x2-fitting it was found that the MEG amplitudes in epileptic patients and normal subjects had Poisson and Gauss distributions respectively. The Poisson connectivity derived from the theoretical neural model represents the state of epilepsy, whereas the Gauss connectivity represents normal behavior. The MEG data obtained from epileptic areas had higher amplitudes than the MEG from normal regions and were comparable with the theoretical magnetic fields from Poisson and Gauss distributions. Furthermore, the magnetic field derived from the theoretical model had amplitudes in the same order as the recorded MEG from the 20 participants.
Conclusion:
The approximation of the theoretical neural net model with real MEG data provides information about the structure of the brain function in epileptic and normal states encouraging further studies to be conducted.
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