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主动树突:适应基于穗的通信

Active dendrites: adaptation to spike-based communication
课程网址: http://videolectures.net/nips2011_ujfalussy_dendrites/  
主讲教师: Balazs B Ujfalussy
开课单位: 剑桥大学
开课时间: 2012-09-06
课程语种: 英语
中文简介:
树突计算的计算分析通常假定神经元的输入是固定的,忽略了神经元之间基于尖峰的通信的脉动性质以及由这种尖峰输入引起的瞬间波动。相反,带尖峰神经元的电路计算通常是形式化的,而不考虑树突处理的丰富非线性性质。在这里,我们解决了神经元计算和表示模拟量但与数字峰值通信所面临的计算挑战,并表明即使是纯线性输入函数的可靠计算也需要突触后树突树内强非线性亚单位的相互作用。我们的理论预测了树突非线性和突触重量分布与突触前输入联合统计的匹配。这种方法为一些令人费解的非线性枝晶动力学和塑性形式提供了规范的作用。
课程简介: Computational analyses of dendritic computations often assume stationary inputs to neurons, ignoring the pulsatile nature of spike-based communication between neurons and the moment-to-moment fluctuations caused by such spiking inputs. Conversely, circuit computations with spiking neurons are usually formalized without regard to the rich nonlinear nature of dendritic processing. Here we address the computational challenge faced by neurons that compute and represent analogue quantities but communicate with digital spikes, and show that reliable computation of even purely linear functions of inputs can require the interplay of strongly nonlinear subunits within the postsynaptic dendritic tree. Our theory predicts a matching of dendritic nonlinearities and synaptic weight distributions to the joint statistics of presynaptic inputs. This approach suggests normative roles for some puzzling forms of nonlinear dendritic dynamics and plasticity.
关 键 词: 树突状计算; 神经元; 非线性性质
课程来源: 视频讲座网
最后编审: 2020-06-02:毛岱琦(课程编辑志愿者)
阅读次数: 37