A two-compartment model of synaptic computation and plasticity.

Mol Brain

Centre of Discovery Brain Sciences, University of Edinburgh, 9 George Square, Edinburgh, EH8 9XD, UK.

Published: May 2020

AI Article Synopsis

  • The synapse is typically seen as a single compartment that controls the strength of signals entering the postsynaptic terminal through traditional plasticity rules
  • This view overlooks the complex dynamics happening at the presynaptic terminal, which is important for filtering input before it reaches the postsynaptic terminal
  • A new model presents the synapse as having two compartments, each with its own plasticity rules, allowing for optimized transmission of relevant information while enhancing our understanding of presynaptic function and plasticity for future research.

Article Abstract

The synapse is typically viewed as a single compartment, which acts as a linear gain controller on incoming input. Traditional plasticity rules enable this gain control to be dynamically optimized by Hebbian activity. Whilst this view nicely captures postsynaptic function, it neglects the non-linear dynamics of presynaptic function. Here we present a two-compartment model of the synapse in which the presynaptic terminal first acts to filter presynaptic input before the postsynaptic terminal, acting as a gain controller, amplifies or depresses transmission. We argue that both compartments are equipped with distinct plasticity rules to enable them to optimally adapt synaptic transmission to the statistics of pre- and postsynaptic activity. Specifically, we focus on how presynaptic plasticity enables presynaptic filtering to be optimally tuned to only transmit information relevant for postsynaptic firing. We end by discussing the advantages of having a presynaptic filter and propose future work to explore presynaptic function and plasticity in vivo.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7238589PMC
http://dx.doi.org/10.1186/s13041-020-00617-1DOI Listing

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