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Authors: Tim Tambuyzer 1 ; Tariq Ahmed 2 ; C. James Taylor 3 ; Daniel Berckmans 1 ; Detlef Balschun 2 and Jean-Marie Aerts 1

Affiliations: 1 Division Measure, Model & Manage Bioresponses (M3-BIORES), Department of Biosystems and Catholic University of Leuven, Belgium ; 2 Laboratory for Biological Psychology, Department of Psychology and Catholic University of Leuven, Belgium ; 3 Lancaster University, United Kingdom

ISBN: 978-989-8565-36-5

Keyword(s): Synaptic Plasticity, Long Term Depression, Dominant Sub-Processes, Discrete-Time Transfer Function Models.

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

Abstract: Recent advances have started to uncover the underlying mechanisms of metabotropic glutamate receptor (mGluR) dependent long-term depression (LTD). However, it is not completely clear how these mechanisms are linked and it is believed that several crucial mechanisms still remain to be revealed. In this study, we investigated whether system identification (SI) methods can be used to gain insight into the mechanisms of synaptic plasticity. SI methods have shown to be an objective and powerful approach for describing how sensory neurons encode information about stimuli. However, to the author’s knowledge it is the first time that SI methods are applied to electrophysiological brain slice recordings of synaptic plasticity responses. The results indicate that the SI approach is a valuable tool for reverse engineering of mGluR-LTD responses. It is suggested that such SI methods can aid to unravel the complexities of synaptic function.

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Paper citation in several formats:
Tambuyzer T., Ahmed T., James Taylor C., Berckmans D., Balschun D. and Aerts J. (2013). Dynamic Data-based Modelling of Synaptic Plasticity: mGluR-dependent Long-term Depression .In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 48-53. DOI: 10.5220/0004231100480053

@conference{biosignals13,
author={Tim Tambuyzer and Tariq Ahmed and C. James Taylor and Daniel Berckmans and Detlef Balschun and Jean-Marie Aerts},
title={Dynamic Data-based Modelling of Synaptic Plasticity: mGluR-dependent Long-term Depression },
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},
year={2013},
pages={48-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004231100480053},
isbn={978-989-8565-36-5},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - Dynamic Data-based Modelling of Synaptic Plasticity: mGluR-dependent Long-term Depression
SN - 978-989-8565-36-5
AU - Tambuyzer T.
AU - Ahmed T.
AU - James Taylor C.
AU - Berckmans D.
AU - Balschun D.
AU - Aerts J.
PY - 2013
SP - 48
EP - 53
DO - 10.5220/0004231100480053

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