12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

93%

93% of Lancaster students go into work or further study within six months of graduating

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

« Back

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

Research output: Contribution in Book/Report/ProceedingsPaper

Published

Publication date02/2013
Host publication6th International Conference on Bio–inspired Systems and Signal Processing
Pages48-53
Number of pages6
Original languageEnglish

Conference

ConferenceBIOSIGNALS 2013: 6th International Conference on Bio–inspired Systems and Signal Processing
CountrySpain
CityBarcelona
Period11/02/1314/02/13

Conference

ConferenceBIOSIGNALS 2013: 6th International Conference on Bio–inspired Systems and Signal Processing
CountrySpain
CityBarcelona
Period11/02/1314/02/13

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.