Cortical high gamma network oscillations and connectivity: a translational index for antipsychotics to normalize aberrant neurophysiological activity

摘要

Oscillatory activity in the gamma frequency range is a critical mechanism, which integrates neural networks within and across brain structures during cognitive processes. In schizophrenia, abnormalities in high gamma oscillations are ubiquitous and most likely reflect dysfunction in neuronal networks. In conscious rats, disturbed network oscillations associated with positive symptoms and cognitive deficits were modeled in different cortical areas by the dopaminergic agonist (amphetamine) and the N-methyl-D-aspartate (NMDA) receptor antagonists (PCP and MK801). Subsequently, the efficacies of marketed atypical antipsychotics (olanzapine, risperidone, and clozapine) to normalize dysfunctional oscillations and network connectivity were examined. Acute NMDA antagonists elicited aberrant synchrony in the gamma frequency oscillations. In addition, coherent slow alpha network activity was observed with MK801 and amphetamine, both of whose oscillatory rhythms were correlated with pronounced locomotor activity. All antipsychotics commonly decreased slow alpha and high gamma network oscillations in different cortical regions as well as motion behavior. In the combined treatments, antipsychotics attenuated NMDA antagonist-induced abnormalities in functional network oscillations and connectivity, whose effects on motor behavior is mechanistically related. These results suggest that pharmacologically induced disruption of cortical gamma oscillations and network connectivity in rats is a candidate model to study dysfunctional oscillatory patterns described in positive and negative symptoms of schizophrenia. The efficacy of antipsychotics to rescue cortical network oscillatory patterns is in line with the idea that glutamatergic and dopaminergic systems play a role in maintaining the integrity of cortical circuits. Thus, gamma oscillations could provide a powerful translational index to assess the integrity of neural networks and to evaluate the efficacy of drugs with potential antipsychotic properties.