Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

Abstract

A fundamental unresolved problem in neuroscience is how the brain associates in memory events that are separated in time. Here we propose that reactivation-induced synaptic plasticity can solve this problem. Previously, we reported that the reinforcement signal dopamine converts hippocampal spike timing-dependent depression into potentiation during continued synaptic activity (Brzosko et al., 2015). Here, we report that postsynaptic bursts in the presence of dopamine produces input-specific LTP in hippocampal synapses 10 minutes after they were primed with coincident pre- and postsynaptic activity. The priming activity sets an NMDAR-dependent silent eligibility trace which, through the cAMP-PKA cascade, is rapidly converted into protein synthesis-dependent synaptic potentiation, mediated by a signaling pathway distinct from that of conventional LTP. Incorporated into a computational model, this synaptic learning rule adds specificity to reinforcement learning by controlling memory allocation and enabling both instructive and supervised reinforcement learning. We predicted that this mechanism would make reactivated neurons activate more strongly and carry more spatial information than non-reactivated cells, which was confirmed in freely moving mice performing a reward-based navigation task.