" ... The coupled oscillator model implemented with Wang–Buzsaki model neurons is not sufficiently robust to heterogeneity in excitatory drive, and therefore intrinsic frequency, to account for in vitro models of ING. Similarly, in a tightly synchronized regime, the stochastic population oscillator model is often characterized by sparse firing, whereas interneurons both in vivo and in vitro do not fire sparsely during gamma,but rather on average every other cycle. We substituted so-called resonator neural models, which exhibit class 2 excitability and postinhibitory rebound (PIR), for the integrators that are typically used. This results in much greater robustness to heterogeneity that actually increases as the average participation in spikes per cycle approximates physiological levels. Moreover, dynamic clamp experiments that show autapse-induced firing in entorhinal cortical interneurons support the idea that PIR can serve as a network gamma mechanism. ..."
Model Type: Realistic Network
Region(s) or Organism(s): Entorhinal cortex
Cell Type(s): Wide dynamic range neuron
Model Concept(s): Gamma oscillations
Simulation Environment: NEURON; Python
Implementer(s): Tikidji-Hamburyan, Ruben [ruben.tikidji.hamburyan at gmail.com]
References:
Tikidji-Hamburyan RA, Martínez JJ, White JA, Canavier CC. (2015). Resonant Interneurons Can Increase Robustness of Gamma Oscillations. The Journal of neuroscience : the official journal of the Society for Neuroscience. 35 [PubMed]