Although it is well known that long-term synaptic plasticity can be expressed both pre- and postsynaptically, the functional consequences of this arrangement have remained elusive. We show that spike-timing-dependent plasticity with both pre- and postsynaptic expression develops receptive fields with reduced variability and improved discriminability compared to postsynaptic plasticity alone. These long-term modifications in receptive field statistics match recent sensory perception experiments. In these simulations we demonstrate that learning with this form of plasticity leaves a hidden postsynaptic memory trace that enables fast relearning of previously stored information, providing a cellular substrate for memory savings. Our results reveal essential roles for presynaptic plasticity that are missed when only postsynaptic expression of long-term plasticity is considered, and suggest an experience-dependent distribution of pre- and postsynaptic strength changes.
Model Type: Synapse
Region(s) or Organism(s): Neocortex
Cell Type(s): Neocortex L5/6 pyramidal GLU cell
Transmitters: NO; Glutamate; Endocannabinoid
Model Concept(s): STDP
Simulation Environment: MATLAB; Brian; Python
Implementer(s): Costa, Rui Ponte [ruipontecosta at gmail.com]
References:
Costa RP, Froemke RC, Sjöström PJ, van Rossum MC. (2015). Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning. eLife. 4 [PubMed]