title: Synchronization properties of coupled chaotic neurons: The role of random shared input.
abstract: Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag-synchronous states, and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.
authors.affiliation: School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
authors.forename: Rupesh
authors.initials: R
authors.lastname: Kumar
authors.affiliation: Department of Physics and Astrophysics, University of Delhi, Delhi 110 007, India.
authors.forename: Shakir
authors.initials: S
authors.lastname: Bilal
authors.affiliation: School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
authors.forename: Ram
authors.initials: R
authors.lastname: Ramaswamy
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics