A unified computational model for cortical post-synaptic plasticity

Abstract

Cortical synapses possess a machinery of signalling pathways that leads to various modes of post-synaptic plasticity. Such pathways have been examined to a great detail separately in many types of experimental studies. However, a unified picture on how multiple biochemical pathways collectively shape the observed synaptic plasticity in the neocortex is missing. Here, we built a biochemically detailed model of post-synaptic plasticity that includes the major signalling cascades, namely, CaMKII, PKA, and PKC pathways which, upon activation by Ca 2+ , lead to synaptic potentiation or depression. We adjusted model components from existing models of intracellular signalling into a single-compartment simulation framework. Furthermore, we propose a statistical model for the prevalence of different types of membrane-bound AMPA-receptor tetramers consisting of GluR1 and GluR2 subunits in proportions suggested by the biochemical signalling model, which permits the estimation of the AMPA-receptor-mediated maximal synaptic conductance. We show that our model can reproduce neuromodulator-gated spike-timing-dependent plasticity as observed in the visual cortex. Moreover, we demonstrate that our model can be fit to data from many cortical areas and that the resulting model parameters reflect the involvement of the pathways pinpointed by the underlying experimental studies. Our model explains the dependence of different forms of plasticity on the availability of different proteins and can be used for the study of mental disorder-associated impairments of cortical plasticity. Significance statementNeocortical synaptic plasticity has been studied experimentally in a number of cortical areas, showing how interactions between neuromodulators and post-synaptic proteins shape the outcome of the plasticity. On the other hand, non-detailed computational models of long-term plasticity, such as Hebbian rules of synaptic potentiation and depression, have been widely used in modelling of neocortical circuits. In this work, we bridge the gap between these two branches of neuroscience by building a detailed model of post-synaptic plasticity that can reproduce observations on cortical plasticity and provide biochemical meaning to the simple rules of plasticity. Our model can be used for predicting the effects of chemical or genetic manipulations of various intracellular signalling proteins on induction of plasticity in health and disease.

A stochastic model of hippocampal synaptic plasticity with geometrical readout of enzyme dynamics

“…Third, like most biophysical models, ours contained many parameters (Methods). Although we set these to physiologically plausible values and then tuned to match the plasticity data, other combinations of parameters may fit the data equally well (Marder and Taylor, 2011;Mäki-Marttunen et al, 2020) due to the ubiquitous phenomenon of redundancy in biochemical and neural systems (Gutenkunst et al, 2007;Marder, 2011). Indeed synapses are quite heterogeneous in receptor and ion channel counts (Takumi et al, 1999;Sabatini and Svoboda, 2000;Racca et al, 2000;Nimchinsky et al, 2004), protein abundances (Shepherd and Harris, 1998;Sugiyama et al, 2005), and spine morphologies (Harris and Stevens, 1989;Bartol et al, 2015), even within the subpopulation of CA1 pyramidal neuron synapses that we modelled here.…”

Silences, spikes and bursts: Three‐part knot of the neural code

“…Multiple chemical pathways depend on this elevation of postsynaptic calcium (Bhalla & Iyengar, 1999;Mäki-Marttunen et al, 2020). For calcium to be elevated at the synapse, it may arise from NMDAR-mediated currents, local release from calcium stores or VGCCs.…”

Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modelling

“…We used the CommonMind gene-expression datasets from post-mortem brains of SCZ patients and healthy controls (HCs) [Hoffman et al, 2019] that provide the information on whether the expression of genes, particularly those associated with risk single-nucleotide polymorphisms (SNPs), are up-or down-regulated or unaffected in SCZ. We applied a computational model [Mäki-Marttunen et al, 2020] to the patients' brain gene expression data and investigated the effects of gene variants on the pathways that lead to long-term potentiation (LTP) and depression (LTD).…”

“…Using the model of [Mäki-Marttunen et al, 2020] we explored the impact that the altered expression profile of plasticityregulating genes, as measured in prefrontal cortices (PFC) and anterior cingulate cortices (ACC) of SCZ patients, have on several forms of synaptic plasticity. We showed that both the conventional forms of plasticity and the plasticity induced by the VEP protocol are significantly impaired by the alterations of protein levels suggested by post-mortem expression data and that these alterations are driven by impaired PKA-pathway-mediated synaptic potentiation.…”