Possible roles of electrical synapse in temporal information processing: A computational study
Author(s) -
Xulong Wang,
Xiaodong Jiang,
Pei-Ji Liang
Publication year - 2008
Publication title -
journal of biomedical science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1937-688X
pISSN - 1937-6871
DOI - 10.4236/jbise.2008.11005
Subject(s) - computer science , sensory system , neuroscience , information processing , artificial neural network , biological neural network , synapse , electrical synapses , sensory processing , computational model , artificial intelligence , machine learning , biology , intracellular , gap junction , microbiology and biotechnology
Temporal information processing in the range of tens to hundreds of milliseconds is critical in many forms of sensory and motor tasks. However, little has been known about the neural mechanisms of temporal information processing. Experimental observations indicate that sensory neurons of the nervous system do not show selective response to temporal properties of external stimuli. On the other hand, temporal selective neurons in the cortex have been reported in many species. Thus, processes which realize the temporal-to-spatial transformation of neuronal activities might be required for temporal information processing. In the present study, we propose a computational model to explore possible roles of electrical synapses in processing the duration of external stimuli. Firstly, we construct a small-scale network with neurons interconnected by electrical synapses in addition to chemical synapses. Basic properties of this small-scale neural network in processing duration information are analyzed. Secondly, a large-scale neural network which is more biologically realistic is further explored. Our results suggest that neural networks with electrical synapses functioning together with chemical synapses can effectively work for the temporal-to-spatial transformation of neuronal activities, and the spatially distributed sequential neural activities can potentially represent temporal information
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