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Authors: K. J. Weegink 1 ; J. J. Varghese 1 ; P. A. Bellette 1 ; T. Coyne 2 ; P. A. Silburn 1 and P. A. Meehan 1

Affiliations: 1 The University of Queensland, Australia ; 2 St. Andrew’s War Memorial Hospital, Australia

Keyword(s): Deep brain signals, Micro-electrode recordings, Point Process model.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Biomedical Signal Processing ; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics

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 several formats:
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 (BIOSTEC 2012) - BIOSIGNALS; ISBN 978-989-8425-89-8; ISSN 2184-4305, SciTePress, pages 76-84. DOI: 10.5220/0003782400760084

@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 (BIOSTEC 2012) - BIOSIGNALS},
year={2012},
pages={76-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003782400760084},
isbn={978-989-8425-89-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2012) - BIOSIGNALS
TI - AN EFFICIENT STOCHASTIC BASED MODEL FOR SIMULATING MICROELECTRODE RECORDINGS OF THE DEEP BRAIN - Modelling and Analysis
SN - 978-989-8425-89-8
IS - 2184-4305
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
PB - SciTePress

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