Home > Research > Publications & Outputs > Dynamic data–based modelling of synaptic plasti...
View graph of relations

Dynamic data–based modelling of synaptic plasticity: mGluR–dependent long–term depression

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Published

Standard

Dynamic data–based modelling of synaptic plasticity: mGluR–dependent long–term depression. / Tambuyzer, T.; Ahmed, T.; Taylor, C. James et al.
6th International Conference on Bio–inspired Systems and Signal Processing. 2013. p. 48-53.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Harvard

Tambuyzer, T, Ahmed, T, Taylor, CJ, Berckmans, D, D., B & Aerts, J-M 2013, Dynamic data–based modelling of synaptic plasticity: mGluR–dependent long–term depression. in 6th International Conference on Bio–inspired Systems and Signal Processing. pp. 48-53, BIOSIGNALS 2013: 6th International Conference on Bio–inspired Systems and Signal Processing , Barcelona, Spain, 11/02/13. <http://www.biosignals.biostec.org/Abstracts/2013/BIOSIGNALS_2013_Abstracts.htm#Area0FullPapers>

APA

Tambuyzer, T., Ahmed, T., Taylor, C. J., Berckmans, D., D., B., & Aerts, J-M. (2013). Dynamic data–based modelling of synaptic plasticity: mGluR–dependent long–term depression. In 6th International Conference on Bio–inspired Systems and Signal Processing (pp. 48-53) http://www.biosignals.biostec.org/Abstracts/2013/BIOSIGNALS_2013_Abstracts.htm#Area0FullPapers

Vancouver

Tambuyzer T, Ahmed T, Taylor CJ, Berckmans D, D. B, Aerts J-M. Dynamic data–based modelling of synaptic plasticity: mGluR–dependent long–term depression. In 6th International Conference on Bio–inspired Systems and Signal Processing. 2013. p. 48-53

Author

Tambuyzer, T. ; Ahmed, T. ; Taylor, C. James et al. / Dynamic data–based modelling of synaptic plasticity: mGluR–dependent long–term depression. 6th International Conference on Bio–inspired Systems and Signal Processing. 2013. pp. 48-53

Bibtex

@inproceedings{d5a13b23a178481599224b78202cd8d0,
title = "Dynamic data–based modelling of synaptic plasticity: mGluR–dependent long–term depression",
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{\textquoteright}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 mGluRLTD responses. It is suggested that such SI methods can aid to unravel the complexities of synaptic function.",
keywords = "Synaptic Plasticity, Long Term Depression, Dominant Sub-processes, Discrete-time Transfer Function Models",
author = "T. Tambuyzer and T. Ahmed and Taylor, {C. James} and D. Berckmans and Balschun D. and J.-M. Aerts",
year = "2013",
month = feb,
language = "English",
pages = "48--53",
booktitle = "6th International Conference on Bio–inspired Systems and Signal Processing",
note = "BIOSIGNALS 2013: 6th International Conference on Bio–inspired Systems and Signal Processing ; Conference date: 11-02-2013 Through 14-02-2013",

}

RIS

TY - GEN

T1 - Dynamic data–based modelling of synaptic plasticity: mGluR–dependent long–term depression

AU - Tambuyzer, T.

AU - Ahmed, T.

AU - Taylor, C. James

AU - Berckmans, D.

AU - D., Balschun

AU - Aerts, J.-M.

PY - 2013/2

Y1 - 2013/2

N2 - 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 mGluRLTD responses. It is suggested that such SI methods can aid to unravel the complexities of synaptic function.

AB - 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 mGluRLTD responses. It is suggested that such SI methods can aid to unravel the complexities of synaptic function.

KW - Synaptic Plasticity

KW - Long Term Depression

KW - Dominant Sub-processes

KW - Discrete-time Transfer Function Models

M3 - Conference contribution/Paper

SP - 48

EP - 53

BT - 6th International Conference on Bio–inspired Systems and Signal Processing

T2 - BIOSIGNALS 2013: 6th International Conference on Bio–inspired Systems and Signal Processing

Y2 - 11 February 2013 through 14 February 2013

ER -