Chaotic itinerancy, temporal segmentation and spatio-temporal combinatorial codes
作者: Juliana R. DiasRodrigo F. OliveiraOsame Kinouchi
作者单位: 1Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Av. dos Bandeirantes 3900, 14040-901, Ribeirão Preto, SP, Brazil
刊名: Physica D: Nonlinear Phenomena, 2007, Vol.237 (1), pp.1-5
来源数据库: Elsevier Journal
DOI: 10.1016/j.physd.2007.06.021
关键词: Chaotic itinerancyNeural networksNeural codesCombinatorial codesOlfactory systemSensory systems
英文摘要: Abstract(#br)We study a deterministic dynamics with two time scales in a continuous state attractor network. To the usual (fast) relaxation dynamics towards point attractors (“patterns”) we add a slow coupling dynamics that makes the visited patterns lose stability, leading to an itinerant behavior in the form of punctuated equilibria. One finds that the transition frequency matrix for transitions between patterns shows non-trivial statistical properties in the chaotic itinerant regime. We show that mixture input patterns can be temporally segmented by the itinerant dynamics. The viability of a combinatorial spatio-temporal neural code is also demonstrated.
全文获取路径: Elsevier  (合作)
分享到:
来源刊物:
影响因子:1.669 (2012)

×