These models were published at: Susin E, Destexhe A. 2021. Integration, coincidence detection and resonance in networks of spiking neurons expressing gamma oscillations and asynchronous states. bioRxiv doi: 10.1101/2021.05.03.442436 In this article, we constructed conductance-based network models of gamma oscillations, based on different cell types found in cerebral cortex: Regular Spiking (RS), Fast Spiking (FS) and Chattering cells. 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 found that in all cases, the presence of Gamma oscillations tends to diminish the responsiveness of the networks to external inputs. We tested different paradigms and found none in which Gamma oscillations would favor information flow compared to asynchronous states.
Model Type: Neuron or other electrically excitable cell; Realistic Network
Region(s) or Organism(s): Neocortex
Cell Type(s): Abstract integrate-and-fire adaptive exponential (AdEx) neuron
Model Concept(s): Gamma oscillations
Simulation Environment: Brian 2
Implementer(s): Susin, Eduarda [eduardadsusin at gmail dot com]
References:
Susin E, Destexhe A. (2021). Integration, coincidence detection and resonance in networks of spiking neurons expressing gamma oscillations and asynchronous states PLoS computational biology. 17 [PubMed]