Neural information processing with dynamical synapses

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Neural information processing with dynamical synapses

1 State Key Laboratory of Cognitive Neuroscience & Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China 2 Center for Innovation and Collaboration in Brain and Learning Sciences, Beijing Normal University, Beijing, China 3 Department of Physics, Hong Kong University of Science & Technology, Hong Kong, China 4 Department of Neurobiology, Weizmann Insti...

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The present study investigates a potential computational role of dynamical electrical synapses in neural information process. Compared with chemical synapses, electrical synapses are more efficient in modulating the concerted activity of neurons. Based on the experimental data, we propose a phenomenological model for short-term facilitation of electrical synapses. The model satisfactorily repro...

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Dynamical Synapses Enhance Neural Information Processing: Gracefulness, Accuracy, and Mobility

Experimental data have revealed that neuronal connection efficacy exhibits two forms of short-term plasticity: short-term depression (STD) and short-term facilitation (STF). They have time constants residing between fast neural signaling and rapid learning and may serve as substrates for neural systems manipulating temporal information on relevant timescales. This study investigates the impact ...

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Dynamical Synapses Enhance Neural Information Processing: Mobility, Memory and Decoding

Neuronal connection efficacy exhibits two forms of short-term plasticity, namely, short-term depression (STD) and short-term facilitation (STF). They have time constants residing between fast neural signaling and slow learning, and may serve as substrates for neural systems manipulating temporal information in relevant time scales. The present study investigates the impact of STD and STF on the...

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ژورنال

عنوان ژورنال: Frontiers in Computational Neuroscience

سال: 2013

ISSN: 1662-5188

DOI: 10.3389/fncom.2013.00188