Recent experimental studies have suggested that the astrocytes of the local network can actually control the emergence of Up-Down regimes. Here we propose and study a neural net- work model to explore the implication of astrocytes in this dynamical phenomenon. We consider three populations of cells: excitatory neurons, inhibitory neurons and astrocytes, interconnected by gliotransmission events, from neurons to astrocytes and back. We derive two models for this three-population system: a rate model and a stochastic spiking neural network with thousands of neurons and astrocytes. In numerical simulations of these three-population models, the presence of astrocytes is indeed observed to promote the emergence of Up-Down regimes with realistic characteristics.
Model Type: Neuron or other electrically excitable cell; Glia
Region(s) or Organism(s): Neocortex
Cell Type(s): Abstract integrate-and-fire leaky neuron; Abstract rate-based neuron
Model Concept(s): Bifurcation; Oscillations
Implementer(s): Berry, Hughes [hughes.berry at inria.fr]
References:
Blum Moyse L, Berry H. (2022). Modelling the modulation of cortical Up-Down state switching by astrocytes PLoS computational biology. 18 [PubMed]