2024-03-29T10:23:22Zhttps://eprints.lib.hokudai.ac.jp/dspace-oai/requestoai:eprints.lib.hokudai.ac.jp:2115/5892022-11-17T02:08:08Zhdl_2115_20039hdl_2115_116Chaotic itinerancy as a mechanism of irregular changes between synchronization and desynchronization in a neural network1000010207384Tsuda, Ichiro津田, 一郎Fujii, HiroshiTadokoro, SatoruYasuoka, TakuiYamaguti, Yutakaopen accessCopyright (c) 2004 Imperial College Press. The original publication is available at www.worldscinet.comGap junction-coupled systemclass I* neuronsdynamic cell assemblychaotic itinerancyMilnor attractormetachronal wavessynchronization481.37We investigate the dynamic character of a network of electrotonically coupled cells consisting of class I point neurons, in terms of a finite dimensional dynamical system. We classify a subclass of class I point neurons, called class I* point neurons. Based on this classification, we use a reduced Hindmarsh-Rose (H-R) model, which consists of two dynamical variables, to construct a network model consisting of electrotonically coupled H-R neurons. Although biologically simple, the system is sufficient to extract the essence of the complex dynamics, which the system may yield under certain physiological conditions. The network model produces a transitory behavior as well as a periodic motion and spatio-temporal chaos. The transitory dynamics that the network model exhibits is shown numerically to be chaotic itinerancy. The transitions appear between various metachronal waves and all-synchronization states. The network model shows that this transitory dynamics can be viewed as a chaotic switch between synchronized and desynchronized states. Despite the use of spatially discrete point neurons as basic elements of the network, the overall dynamics exhibits scale-free activity including various scales of spatio-temporal patterns.http://www.worldscinet.com/jin/jin.shtmlImperial College Press2004-06engjournal articleAMhttp://hdl.handle.net/2115/589https://doi.org/10.1142/S021963520400049X02196352Journal of Integrative Neuroscience32159182https://eprints.lib.hokudai.ac.jp/dspace/bitstream/2115/589/1/TF.JIN.pdfapplication/pdf2.83 MB2004-06