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Journal of Computational Neuroscience

Erschienen in:

01.06.2014

Open loop optogenetic control of simulated cortical epileptiform activity

verfasst von: Prashanth Selvaraj, Jamie W. Sleigh, Walter J. Freeman, Heidi E. Kirsch, Andrew J. Szeri

Erschienen in: Journal of Computational Neuroscience | Ausgabe 3/2014

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Abstract

We present a model for the use of open loop optogenetic control to inhibit epileptiform activity in a meso scale model of the human cortex. The meso scale cortical model first developed by Liley et al. (2001) is extended to two dimensions and the nature of the seizure waves is studied. We adapt to the meso scale a 4 state functional model of Channelrhodopsin-2 (ChR2) ion channels. The effects of pulsed and constant illumination on the conductance of these ion channels is presented. The inhibitory cell population is targeted for the application of open loop control. Seizure waves are successfully suppressed and the inherent properties of the optogenetic channels ensures charge balance in the cortex, protecting it from damage.

Vorheriger Artikel Numerical modelling of plasticity induced by transcranial magnetic stimulation

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The average human cortex has dimensions of \(500 \times 500 \ \text {mm}^{2}\) if it were laid open like a sheet. However, the spiral seizure waves have a radius of curvature that is too large to be appreciated within a domain of the size of an average human cortex, and because cortical dynamics is scale-free, we have used a larger cortical domain to illustrate them.

The fourth order solver is more accurate in producing results that match experimental observations of conductance, but the first order method takes less computation time to solve the equations. Because the optogenetic channels function at a smaller time scale, and because we are only interested in time scales of the cortical model, the use of the simpler first order method is justified.

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Titel: Open loop optogenetic control of simulated cortical epileptiform activity
verfasst von: Prashanth Selvaraj
Jamie W. Sleigh
Walter J. Freeman
Heidi E. Kirsch
Andrew J. Szeri
Publikationsdatum: 01.06.2014
Verlag: Springer US
Erschienen in: Journal of Computational Neuroscience / Ausgabe 3/2014
Print ISSN: 0929-5313
Elektronische ISSN: 1573-6873
DOI: https://doi.org/10.1007/s10827-013-0484-2

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