A biochemical description of postsynaptic plasticity-with timescales ranging from milliseconds to seconds.

Guanchun Li, David W McLaughlin, Charles S Peskin

Journal: Proceedings of the National Academy of Sciences of the United States of America 2024;121(7):e2311709121

PMID: 38324573

Abstract

Synaptic plasticity [long-term potentiation/depression (LTP/D)], is a cellular mechanism underlying learning. Two distinct types of early LTP/D (E-LTP/D), acting on very different time scales, have been observed experimentally-spike timing dependent plasticity (STDP), on time scales of tens of ms; and behavioral time scale synaptic plasticity (BTSP), on time scales of seconds. BTSP is a candidate for a mechanism underlying rapid learning of spatial location by place cells. Here, a computational model of the induction of E-LTP/D at a spine head of a synapse of a hippocampal pyramidal neuron is developed. The single-compartment model represents two interacting biochemical pathways for the activation (phosphorylation) of the kinase (CaMKII) with a phosphatase, with ion inflow through channels (NMDAR, CaV1,Na). The biochemical reactions are represented by a deterministic system of differential equations, with a detailed description of the activation of CaMKII that includes the opening of the compact state of CaMKII. This single model captures realistic responses (temporal profiles with the differing timescales) of STDP and BTSP and their asymmetries. The simulations distinguish several mechanisms underlying STDP vs. BTSP, including i) the flow of [Formula: see text] through NMDAR vs. CaV1 channels, and ii) the origin of several time scales in the activation of CaMKII. The model also realizes a priming mechanism for E-LTP that is induced by [Formula: see text] flow through CaV1.3 channels. Once in the spine head, this small additional [Formula: see text] opens the compact state of CaMKII, placing CaMKII ready for subsequent induction of LTP.

Address: Courant Institute and Center for Neural Science, Department of Mathematics, New York University, New York, NY 10012.; Courant Institute and Center for Neural Science, Department of Mathematics, New York University, New York, NY 10012.; Center for Neural Science, Department of Neural Science, New York University, New York, NY 10012.; Institute of Mathematical Science, Mathematics Department, New York University-Shanghai, Shanghai 200122, China.; Neuroscience Institute of New York University Langone Health, New York University, New York, NY 10016.; Courant Institute and Center for Neural Science, Department of Mathematics, New York University, New York, NY 10012.; Center for Neural Science, Department of Neural Science, New York University, New York, NY 10012.
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