title: Uncovering bifurcation patterns in cortical synapses.
abstract: Individual cortical synapses are known to exhibit a very complex short-time dynamic behaviour in response to simple "naturalistic" stimulation. We describe a computational study of the experimentally obtained excitatory post-synaptic potential trains of individual cortical synapses. By adopting a new nonlinear modelling scheme we construct robust and repeatable models of the underlying dynamics. These models suggest that cortical synapses exhibit a wide range of either periodic or chaotic dynamics. For stimulus at a fixed rate our models predict that the response of the individual synapse will vary from a fixed point to periodic and chaotic, depending on the frequency of stimulus. Dynamics for individual synapses vary widely, suggesting that the individual behaviour of synapses is highly tuned and that the dynamic behaviour of even a small network of synapse-coupled neurons could be extremely varied.
authors: Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong. ensmall@polyu.edu.hk
authors: Michael
authors: M
authors: Small
authors: Hugh P C
authors: HP
authors: Robinson
authors: Ingo C
authors: IC
authors: Kleppe
authors: Chi Kong
authors: CK
authors: Tse
mesh_terms: D000465:Algorithms; D000818:Animals; D002540:Cerebral Cortex / Q000502:physiology*; D003198:Computer Simulation; D008959:Models, Neurological; D017711:Nonlinear Dynamics; D051381:Rats; D017208:Rats, Wistar; D013269:Stochastic Processes; D013569:Synapses / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*