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第97期心理沙龙--主讲人:韩彪 特聘研究员

2019-03-15 10:23:49 来源:华南师范大学心理应用研究中心 点击: 收藏本文
题目:Correlated spiking-times create symmetrical backpropagation weights with reversed signs
主讲人:韩彪 特聘研究员
时间:2019年3月14日(周四)下午16:00-17:00

地点:心理学院301会议室


摘要:In many computational neuroscience and machine learning models (e.g. predictive coding and backpropagation), symmetrical feedback weights was the one key ingredient for the implementation. However, there are no empirical evidence supporting the existence of such symmetric reciprocal connections, resulting one of the greatest obstacles for linking the machine world with the real world. In this talk, I will propose a simple neural network model to address this issue. This model is implemented using current-based neurons (leaky integrate-and-fire neurons) and widely observed selective excitatory feedforward connections and non-selective excitatory feedback connections. We demonstrated that, taking advantage of the temporal information of the neuron spikes, the simple neural model can imitate the feedforward weights in the feedback pathway with reversed signs.


简历

韩彪,于2016年获得法国图卢兹大学/法国国家科学研究中心 “最高荣誉”(Très honorable)神经科学博士学位,师从Rufin VanRullen博士。在结束博士学习生涯后,获得了法国Fyssen基金会的博士后奖学金并开始了在荷兰唐德思研究所(Donders Institute)的博士后研究,师从Floris de Lange博士。韩彪博士主要使用计算模型、EEG/MEG/sEEG和fMRI研究大脑中的“反馈”通路。