Dynamical synapses enhance neural information processing : Gracefulness, accuracy, and mobility

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

37 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)1147-1185
Journal / PublicationNeural Computation
Volume24
Issue number5
Publication statusPublished - 2012
Externally publishedYes

Abstract

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 of STD and STF on the dynamics of continuous attractor neural networks and their potential roles in neural information processing. We find that STD endows the network with slow-decaying plateau behaviors: the network that is initially being stimulated to an active state decays to a silent state very slowly on the timescale of STD rather than on that of neuralsignaling. This provides a mechanism for neural systems to hold sensory memory easily and shut off persistent activities gracefully. With STF, we find that the network can hold a memory trace of external inputs in the facilitated neuronal interactions, which provides a way to stabilize the network response to noisy inputs, leading to improved accuracy in population decoding. Furthermore, we find that STD increases the mobility of the network states. The increased mobility enhances the tracking performance of the network in response to time-varying stimuli, leading to anticipative neural responses. In general, we find that STD and STP tend to have opposite effects on network dynamics and complementary computational advantages, suggesting that the brain may employ a strategy of weighting them differentially depending on the computational purpose. © 2012 Massachusetts Institute of Technology.

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Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to lbscholars@cityu.edu.hk.

Citation Format(s)

Dynamical synapses enhance neural information processing: Gracefulness, accuracy, and mobility. / Fung, C. C. Alan; Michaelwong, K. Y.; Wang, He et al.
In: Neural Computation, Vol. 24, No. 5, 2012, p. 1147-1185.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review