System identification of mGluR-dependent long-term depression.

Tim Tambuyzer, Tariq Ahmed, C James Taylor, Daniel Berckmans, Detlef Balschun, Jean-Marie Aerts

M3-BIORES: Measure, Model and Manage Bioresponses, Department of Biosystems, Catholic University of Leuven, Leuven B-3001, Belgium. tim.tambuyzer@biw.kuleuven.be

Neural computation 2013 Mar

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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 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 been shown to be an objective and powerful approach for describing how sensory neurons encode information about stimuli. However, to our knowledge, it is the first time that SI methods have been 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. We suggest that such SI methods can aid in unraveling the complexities of synaptic function.

Citation

Tim Tambuyzer, Tariq Ahmed, C James Taylor, Daniel Berckmans, Detlef Balschun, Jean-Marie Aerts. System identification of mGluR-dependent long-term depression. Neural computation. 2013 Mar;25(3):650-70