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Critical Reviews™ in Biomedical Engineering
SJR: 0.207 SNIP: 0.376 CiteScore™: 0.79

ISSN Imprimir: 0278-940X
ISSN En Línea: 1943-619X

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Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.2013006724
pages 501-518

Plasticity, Learning, and Complexity in Spiking Networks

Christopher T. Kello
Department of Cognitive and Information Sciences, University of California at Merced, Merced California
Jeffrey Rodny
Department of Cognitive and Information Sciences, University of California at Merced, Merced California
Anne S. Warlaumont
Department of Cognitive and Information Sciences, University of California at Merced, Merced California
David C. Noelle
Department of Cognitive and Information Sciences, University of California at Merced, Merced California

SINOPSIS

Complexity is widespread in neuronal spike trains and propagation of spike activity, in that variations in measurements of neural activity are irregular, heterogeneous, non-stationary, transient, and scale-free. There are numerous possible reasons for this complexity, and numerous possible consequences for neural and behavioral function. The present review is focused on relationships among neural plasticity, learning, and complex spike dynamics in animal nervous systems, including those of humans. The literature on complex spike dynamics and mechanisms of synaptic plasticity are reviewed for the purpose of considering the roles that each might play for the other. That is, the roles of complex spike dynamics in learning and regulatory functions are considered, as well as the roles of learning and regulatory functions in generating complex spike dynamics. Experimental and computational studies from a range of disciplines and perspectives are discussed, and it is concluded that cognitive science and neuroscience have much to gain from investigating the adaptive aspects of complex spike dynamics for neural and cognitive function.


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