In the idling brain, neuronal circuits transition between periods of sustained firing (UP state) and quiescence (DOWN state), a pattern the mechanisms of which remain unclear. We analyzed spontaneous cortical population activity from anesthetized rats and found that UP and DOWN durations were highly variable and that population rates showed no significant decay during UP periods. We built a network rate model with excitatory (E) and inhibitory (I) populations exhibiting a novel bistable regime between a quiescent and an inhibition-stabilized state of arbitrarily low rate, where fluctuations triggered state transitions. In addition, we implemented these mechanisms in a more biophysically realistic spiking network, where DOWN-to-UP transitions are caused by synchronous high-amplitude events impinging onto the network.
Model Type: Realistic Network; Neuron or other electrically excitable cell
Region(s) or Organism(s): Neocortex
Cell Type(s): Abstract integrate-and-fire leaky neuron
Model Concept(s): Spike Frequency Adaptation; Activity Patterns; Oscillations
Simulation Environment: C or C++ program; MATLAB
Implementer(s): Jercog, Daniel [daniel dot jercog at inserm dot fr]
References:
Jercog D et al. (2017). UP-DOWN cortical dynamics reflect state transitions in a bistable network. eLife. 6 [PubMed]