中国科学院上海生命科学研究院神经科学研究所机构知识库
Advanced  
SIBS OpenIR  > 神经所(总)  > 期刊论文
Title: Dynamical Synapses Enhance Neural Information Processing: Gracefulness, Accuracy, and Mobility
Author: Fung, C. C. Alan ; Wong, K. Y. Michael ; Wang, He ; Wu, Si
Source: NEURAL COMPUTATION
Issued Date: 2012
Volume: 24, Issue:5, Pages:1147-1185
Keyword: NEOCORTICAL PYRAMIDAL NEURONS ; SYNAPTIC DEPRESSION ; RELEASE PROBABILITY ; WORKING-MEMORY ; HEAD-DIRECTION ; NETWORKS ; FACILITATION ; CORTEX ; ORIENTATION ; PLASTICITY
Subject: Computer Science ; Neurosciences & Neurology
Corresponding Author: Fung, CCA (reprint author), Hong Kong Univ Sci & Technol, Dept Phys, Hong Kong, Hong Kong, Peoples R China,alanfung@ust.hk ; phkywong@ust.hk ; wangheaq@gmail.com ; wusi@bnu.edu.cn
English 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.
Indexed Type: sci
Language: 英语
Content Type: 期刊论文
URI: http://ir.sibs.ac.cn/handle/331001/1488
Appears in Collections:神经所(总)_期刊论文

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
2.pdf(677KB)----开放获取View Download

Recommended Citation:
Fung, C. C. Alan; Wong, K. Y. Michael; Wang, He; Wu, Si.Dynamical Synapses Enhance Neural Information Processing: Gracefulness, Accuracy, and Mobility,NEURAL COMPUTATION,2012,24(5):1147-1185
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Fung, C. C. Alan]'s Articles
[Wong, K. Y. Michael]'s Articles
[Wang, He]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Fung, C. C. Alan]‘s Articles
[Wong, K. Y. Michael]‘s Articles
[Wang, He]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: 2.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!