Emergence of Irregular Activity in Networks of Strongly Coupled Conductance-Based Neurons
Alessandro Sanzeni, Mark H. Histed, Nicolas Brunel
Abstract
). In such networks, unlike in the standard balanced state model, current fluctuations are small and firing is maintained by a drift-diffusion balance. This balance emerges dynamically, without fine-tuning, if inputs are smaller than a critical value, which depends on synaptic time constants and coupling strength, and is significantly more robust to connection heterogeneities than the classical balanced state model. Our analysis makes experimentally testable predictions of how the network response properties should evolve as input increases.
Topics & Concepts
ConductanceChemical physicsPhysicsComputer scienceStatistical physicsMaterials scienceCondensed matter physicsNeural dynamics and brain functionNeuroscience and Neural EngineeringPhotoreceptor and optogenetics research