A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks
文献类型：期刊论文
| 作者 | Fung, C. C. Alan ; Wong, K. Y. Michael ; Wu, Si |
| 刊名 | NEURAL COMPUTATION
 |
| 出版日期 | 2010 |
| 卷号 | 22期号:3页码:752-792 |
| ISSN号 | 0899-7667 |
| 关键词 | HEAD-DIRECTION PERSISTENT ACTIVITY PREFRONTAL CORTEX PATH-INTEGRATION WORKING-MEMORY MOTOR CORTEX NEURONS MODEL ORIENTATION SYSTEMS |
| 通讯作者 | Wu, S (reprint author), Univ Sussex, Dept Informat, Brighton BN1 9QH, E Sussex, England,alanfung@ust.hk ; phkywong@ust.hk ; siwu@ion.ac.cn |
| 英文摘要 | Understanding how the dynamics of a neural network is shaped by the network structure and, consequently, how the network structure facilitates the functions implemented by the neural system is at the core of using mathematical models to elucidate brain functions. This study investigates the tracking dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of neuronal recurrent interactions, CANNs can hold a continuous family of stationary states. They form a continuous manifold in which the neural system is neutrally stable. We systematically explore how this property facilitates the tracking performance of a CANN, which is believed to have clear correspondence with brain functions. By using the wave functions of the quantum harmonic oscillator as the basis, we demonstrate how the dynamics of a CANN is decomposed into different motion modes, corresponding to distortions in the amplitude, position, width, or skewness of the network state. We then develop a perturbation approach that utilizes the dominating movement of the network's stationary states in the state space. This method allows us to approximate the network dynamics up to an arbitrary accuracy depending on the order of perturbation used. We quantify the distortions of a gaussian bump during tracking and study their effects on tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable and the reaction time for the network to catch up with an abrupt change in the stimulus. |
| 学科主题 | Computer Science ; Neurosciences & Neurology |
| 资助信息 | Research Grants Council of Hong Kong[HKUST 603606, HKUST 603607, HKUST 604008]; BBSRC[BB/E017436/1]; Royal Society of UK |
| 收录类别 | SCI |
| 语种 | 英语 |
| 公开日期 | 2012-07-13 |
| 源URL | [http://ir.sibs.ac.cn/handle/331001/1604]  |
| 专题 | 上海神经科学研究所_神经所(总) |
| 推荐引用方式 GB/T 7714 | Fung, C. C. Alan,Wong, K. Y. Michael,Wu, Si. A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks[J]. NEURAL COMPUTATION,2010,22(3):752-792. |
| APA | Fung, C. C. Alan,Wong, K. Y. Michael,&Wu, Si.(2010).A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks.NEURAL COMPUTATION,22(3),752-792. |
| MLA | Fung, C. C. Alan,et al."A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks".NEURAL COMPUTATION 22.3(2010):752-792. |
入库方式： OAI收割
来源：上海神经科学研究所
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