1471-2202-15-S1-P211 1471-2202 Poster presentation <p>Reproduction of EEG power spectrum over frontal region during the propofol-induced general anesthesia</p> HashemiMeysammeysam.hashemi@inria.fr HuttAxel SleighJamie GrabenbeimPeter

INRIA CR Nancy - Grand Est, Villers-les-Nancy, France

Department of Anaesthetics, Waikato Hospital, Hamilton, New Zealand

Department of German Language and Linguistic, Hamboldt-Universitat zu Berlin, Germany

BMC Neuroscience <p>Abstracts from the Twenty Third Annual Computational Neuroscience Meeting: CNS*2014</p>The publication charges for this supplement were funded by the Organization for Computational Neurosciences.Meeting abstracts - A single PDF containing all abstracts in this supplement is available here.<p>The Twenty Third Annual Computational Neuroscience Meeting: CNS*2014</p>Québec City, Canada26-31 July 2014http://www.cnsorg.org/cns-20141471-2202 2014 15 Suppl 1 P211 http://www.biomedcentral.com/1471-2202/15/S1/P211 10.1186/1471-2202-15-S1-P211
2172014 2014Hashemi et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

The present work aims to reproduce certain changes observed experimentally in the EEG power spectrum over the frontal head region during general anesthesia induced by propofol. These observations include increased delta (0-4 Hz) and alpha (8-12 Hz) activities 1 . We extend a previous cortical model 2 and study a neuronal population model of a single thalamo-cortical module consisting of three different populations of neurons, namely cortical excitatory neurons, thalamocortical relay neurons and inhibitory thalamic reticular neurons (Fig. 1). Each module obeys a neural mass model. The cortical inhibitory population is neglected in our model to reveal the effect of propofol action in the thalamus. Our model describes well the characteristic spectral changes observed experimentally within the delta- and alpha- frequency bands in frontal and occipital electrodes with increasing concentration of propofol.

<p>Figure 1</p>

Schematic of a thalamocortical module. The blue and red lines indicate excitatory and inhibitory connections, respectively. The solid lines represent connections associated with the same delay and the dotted lines denote connections without delay.

Schematic of a thalamocortical module. The blue and red lines indicate excitatory and inhibitory connections, respectively. The solid lines represent connections associated with the same delay and the dotted lines denote connections without delay.

This shows that neglecting inhibitory action in the cortex but considering thalamic GABAergic action suffices to reproduce the data. From a modeling point of view, our reduced mathematical model is low dimensional and remains analytically treatable while still being adequate to reproduce observed changes in EEG rhythms. Moreover, it is shown that the propofol concentration acts as a control parameter of the system and that propofol-induced changes in the stationary states of the model system lead to changes in the corresponding nonlinear gain function that result in EEG power modulation: increases of power over the frontal region can be caused by an increase in the gain function of thalamocortical network. The results suggest that intra-thalamic inhibition from reticular neurons to relay cells plays an important role in the generation of the characteristic EEG patterns seen during general anesthesia.

<p>Tracking brain states under general anesthesia by using global coherence analysis</p>CimenserAPNAS201110888328837<p>The anaesthetic propofol shifts the frequency of maximum spectral power in EEG during general anaesthesia: analytical insights from a linear model,</p>HuttAFront. Comput. Neurosci201372