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动态突触延迟补偿

Delay Compensation with Dynamical Synapses
课程网址: https://videolectures.net/videos/machine_fung_delay  
主讲教师: C. C. Alan Fung
开课单位: 信息不详。欢迎您在右侧留言补充。
开课时间: 2013-01-11
课程语种: 英语
中文简介:
时间延迟在神经信息处理中普遍存在。为了实现实时跟踪,补偿神经系统中的传输和处理延迟至关重要。在本研究中,我们展示了具有短期抑制的动态突触可以增强连续吸引子网络的移动性,使系统及时跟踪时变刺激。网络的状态可以完美地跟踪移动刺激的瞬时位置(零滞后),也可以有效地引导它恒定的时间,与啮齿动物头部方向系统的实验一致。延迟、完美和预期跟踪的参数区域分别对应于静态、准备移动和自发移动的网络状态,证明了跟踪性能与网络内在动态之间的强相关性。我们还发现,当刺激的速度与网络状态的自然速度一致时,延迟变得有效地独立于刺激幅度。
课程简介: Time delay is pervasive in neural information processing. To achieve real-time tracking, it is critical to compensate the transmission and processing delays in a neural system. In the present study we show that dynamical synapses with short-term depression can enhance the mobility of a continuous attractor network to the extent that the system tracks time-varying stimuli in a timely manner. The state of the network can either track the instantaneous position of a moving stimulus perfectly (with zero-lag) or lead it with an effectively constant time, in agreement with experiments on the head-direction systems in rodents. The parameter regions for delayed, perfect and anticipative tracking correspond to network states that are static, ready-to-move and spontaneously moving, respectively, demonstrating the strong correlation between tracking performance and the intrinsic dynamics of the network. We also find that when the speed of the stimulus coincides with the natural speed of the network state, the delay becomes effectively independent of the stimulus amplitude.
关 键 词: 时间延迟; 动态突触; 连续吸引子网络
课程来源: vidiolectures
数据采集: 2025-02-25:yuhongrui
最后编审: 2025-02-25:yuhongrui
阅读次数: 1