A prefrontal network model operating near steady and oscillatory states links spike desynchronization and synaptic deficits in schizophrenia

Abstract

Schizophrenia results in part from a failure of prefrontal networks but we lack full understanding of how disruptions at a synaptic level cause failures at the network level. This is a crucial gap in our understanding because it prevents us from discovering how genetic mutations and environmental risks that alter synaptic function cause prefrontal network to fail in schizophrenia. To address that question, we developed a recurrent spiking network model of prefrontal local circuits that can explain the link between NMDAR synaptic and spike timing deficits we recently observed in a pharmacological monkey model of prefrontal network failure in schizophrenia. We analyze how the balance between AMPA and NMDA components of recurrent excitation and GABA inhibition in the network influence spike timing to inform the biological data. We show that reducing recurrent NMDAR synaptic currents prevents the network from shifting from a steady to oscillatory state in response to extrinsic inputs such as might occur during behavior. This explains how NMDAR synaptic deficits, implicated by genetic evidence as causal in schizophrenia, could prevent the emergence of 0-lag synchronous spiking in prefrontal local circuits during behavior, potentially disconnecting those circuits via spike-timing dependent mechanisms in the human disease.

Overexpression of the schizophrenia risk gene C4 in PV cells drives sex-dependent behavioral deficits and circuit dysfunction

“…Using the specific experimental changes in intrinsic excitability and synaptic connectivity associated with PV-mC4-OE to guide our computational model, we too were led to exactly this same point of convergence. From the decades-enduring synaptic hypothesis of SCZ first proposed by Irwin Feinberg (98) to modern hypotheses of NMDAR hypofunction (111,156,162), many of the dominating views of SCZ pathogenesis feature disruptions in spike-timing and resultant deficits in the effective flow of information from one neuron to the next. Moreover, computational models of brain dysfunction relevant to SCZ from other groups consistently converge on this same feature (156).…”

“…The fundamental unit of this plasticity is the information transferred from the presynaptic partner to its postsynaptic partner(s), the efficacy or existence of this connection being largely an activity-dependent factor (152,154). Moreover, disruptions in spiketiming and consequential deficits in synaptic plasticity are core features of neuropsychiatric diseases, including SCZ (29,83,(155)(156)(157).…”