System identification of mGluR-dependent long-term depression

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

Research output: Contribution to journalLetter

5 Citations (Scopus)

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 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.

Original languageEnglish
Pages (from-to)650-670
Number of pages21
JournalNeural Computation
Volume25
Issue number3
DOIs
Publication statusPublished - 2013
Externally publishedYes

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ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Cognitive Neuroscience

Cite this

Tambuyzer, T., Ahmed, T., Taylor, C. J., Berckmans, D., Balschun, D., & Aerts, J. M. (2013). System identification of mGluR-dependent long-term depression. Neural Computation, 25(3), 650-670. https://doi.org/10.1162/NECO_a_00408