AN EFFICIENT STOCHASTIC BASED MODEL FOR SIMULATING MICROELECTRODE RECORDINGS OF THE DEEP BRAIN - Modelling and Analysis

K. J. Weegink, J. J. Varghese, P. A. Bellette, T. Coyne, P. A. Silburn, P. A. Meehan

Abstract

We have developed a computationally efficient stochastic model for simulating microelectrode recordings, including electronic noise and neuronal noise from the local field of 3000 neurons. From this we have shown that for a neuron network model spiking with a stationary Weibull distribution the power spectrum can change from exhibiting periodic behaviour to non-stationary behaviour as the distribution shape is changed. It is shown that the windowed power spectrum of the model follows an analytical result prediction in the range of 100-5000 Hz. The analysis of the simulation is compared to the analysis of real patient interoperative sub-thalamic nucleus microelectrode recordings. The model runs approximately 200 times faster compared to existing models that can reproduce power spectral behaviour. The results indicate that a spectrogram of the real patient recordings can exhibit non-stationary behaviour that can be re-created using this efficient model in real time.

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Paper Citation


in Harvard Style

J. Weegink K., Varghese J., Bellette P., Coyne T., Silburn P. and Meehan P. (2012). AN EFFICIENT STOCHASTIC BASED MODEL FOR SIMULATING MICROELECTRODE RECORDINGS OF THE DEEP BRAIN - Modelling and Analysis . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012) ISBN 978-989-8425-89-8, pages 76-84. DOI: 10.5220/0003782400760084


in Bibtex Style

@conference{biosignals12,
author={K. J. Weegink and J. J. Varghese and P. A. Bellette and T. Coyne and P. A. Silburn and P. A. Meehan},
title={AN EFFICIENT STOCHASTIC BASED MODEL FOR SIMULATING MICROELECTRODE RECORDINGS OF THE DEEP BRAIN - Modelling and Analysis},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)},
year={2012},
pages={76-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003782400760084},
isbn={978-989-8425-89-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)
TI - AN EFFICIENT STOCHASTIC BASED MODEL FOR SIMULATING MICROELECTRODE RECORDINGS OF THE DEEP BRAIN - Modelling and Analysis
SN - 978-989-8425-89-8
AU - J. Weegink K.
AU - Varghese J.
AU - Bellette P.
AU - Coyne T.
AU - Silburn P.
AU - Meehan P.
PY - 2012
SP - 76
EP - 84
DO - 10.5220/0003782400760084