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

Tambuyzer, T. and Ahmed, T. and Taylor, C. James and Berckmans, D. and D., Balschun and 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. UNSPECIFIED, ESP, pp. 48-53.

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

Item Type:
Contribution in Book/Report/Proceedings
Subjects:
ID Code:
62561
Deposited By:
Deposited On:
14 Mar 2013 12:09
Refereed?:
No
Published?:
Published
Last Modified:
01 Jan 2020 05:42