Susin, E. | bioRxiv Science

bioRxiv2021

A network model of the modulation of gamma oscillations by NMDA receptors in cerebral cortex

Psychotic drugs such as ketamine induce symptoms close to schizophrenia, and stimulate the production of gamma oscillations, as also seen in patients, but the underlying mechanisms are still unclear. Here, we have used computational models of cortical networks generating gamma oscillations, and have integrated the action of drugs such as ketamine to partially block n-methyl-d-Aspartate (NMDA) receptors. The model can reproduce the paradoxical increase of gamma oscillations by NMDA-receptor antagonists, assuming that antagonists affect NMDA receptors with higher affinity on inhibitory interneurons. We next used the model to compare the responsiveness of the network to external stimuli, and found that when NMDA channnels are diminished, an increase of gamma power is observed altogether with an increase of network responsiveness. However, this responsiveness increase applies not only to gamma states, but was also present in asynchronous states with no apparent gamma. We conclude that NMDA antagonists induce an increased excitability state, which may or may not produce gamma oscillations, but the response to external inputs is exacerbated, which may explain phenomena such as altered perception or hallucinations. Significance Statementn-methyl-d-Aspartate (NMDA) synaptic receptors mediate excitatory interactions using the neurotransmitter glutamate. NMDA receptors have been implicated in psychosis such as schizophrenia and are also targeted by hallucinogenic drugs like Ketamine. However, the exact mechanisms of action are sill unclear. Furthermore, Ketamine paradoxially leads to and excited state, while it is a blocker of NMDA receptors, therefore in principle diminishing excitation. Here, we use models of cortical networks generating gamma oscillations, and show that this model can explain the paradoxical exciting effect of Ketamine if one assumes a higher affinity on NMDA receptors of inhibitory interneurons. The simulated Ketamine effect reproduces known symptoms of psychosis such as increased gamma oscillations and exacerbated responses to external inputs, compatible with hallucinations.

neuroscience↗

bioRxiv2021

Integration, coincidence detection and resonance in networks of spiking neurons expressing gamma oscillations and asynchronous states

Gamma oscillations are widely seen in the awake and sleeping cerebral cortex, but the exact role of these oscillations is still debated. Here, we used biophysical models to examine how gamma oscillations may participate to the processing of afferent stimuli. We constructed conductance-based network models of gamma oscillations, based on different cell types found in cerebral cortex. The models were adjusted to extracellular unit recordings in humans, where gamma oscillations always coexist with the asynchronous firing mode. We considered three different mechanisms to generate gamma, first a mechanism based on the interaction between pyramidal neurons and interneurons (PING), second a mechanism in which gamma is generated in interneuron networks (ING) and third, a mechanism which relies on gamma oscillations generated by pacemaker chattering neurons (CHING). We find that all three mechanisms generate features consistent with human recordings, but that the ING mechanism is most consistent with the firing rate change inside Gamma bursts seen in the human data. We next evaluated the responsiveness and resonant properties of these networks, contrasting gamma oscillations with the asynchronous mode. We find that for both slowly-varying stimuli and precisely-timed stimuli, the responsiveness is generally lower during Gamma compared to asynchronous states, while resonant properties are similar around the Gamma band. We could not find conditions where Gamma oscillations were more responsive. We therefore predict that asynchronous states provide the highest responsiveness to external stimuli, while Gamma oscillations tend to overall diminish responsiveness. Author summaryIn the awake and attentive brain, the activity of neurons is typically asynchronous and irregular. It also occasionally displays oscillations in the Gamma frequency range (30-90 Hz), which are believed to be involved in information processing. Here, we use computational models to investigate how brain circuits generate oscillations in a manner consistent with microelectrode recordings in humans. We then study how these networks respond to external input, comparing asynchronous and oscillatory states. This is tested according to several paradigms, an integrative mode, where slowly varying inputs are progressively integrated, a coincidence detection mode, where brief inputs are processed according to the phase of the oscillations, and a resonance mode where the network is probed with oscillatory inputs. Surprisingly, we find that in all cases, the presence of Gamma oscillations tends to diminish the responsiveness to external inputs, and we found no paradigm by which Gamma oscillations would favor information flow compared to asynchronous states. We discuss possible implications of this responsiveness decrease on information processing and propose new directions for further exploration.

neuroscience↗