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真实神经元网络中的临界行为

Critical behavior in networks of real neurons
课程网址: http://videolectures.net/kolokviji_tkacik_real_neurons/  
主讲教师: Gašper Tkačik
开课单位: 奥地利科学技术研究所
开课时间: 2014-04-29
课程语种: 英语
中文简介:
视网膜神经节细胞群的联合活动模式编码了有关视觉世界的完整信息,因此限制了大脑对环境的了解。我们通过构建精确的网络活动状态分布最大熵模型,分析了100多个这样的神经元在单峰水平上对自然刺激作出反应的交互群体中记录的同时活动。这基本上是一个逆自旋玻璃结构,揭示了神经元之间成对耦合的强烈挫败感,导致了具有许多局部极值的崎岖能量景观;神经元亚群中强烈的集体相互作用,尽管个体间存在微弱的成对相关性;活动的联合分布具有极其广泛的动态范围,其特征是类似齐普夫的幂律,与典型性的强烈偏差,以及许多关键行为的特征。我们假设,调整到临界工作点可能是系统的一种动态特性,并建议进行实验来验证这一假设
课程简介: The patterns of joint activity in a population of retinal ganglion cells encode the complete information about the visual world, and thus place limits on what could be learned about the environment by the brain. We analyze the recorded simultaneous activity of more than a hundred such neurons from an interacting population responding to naturalistic stimuli, at the single spike level, by constructing accurate maximum entropy models for the distribution of network activity states. This – essentially an inverse spin glass – construction reveals strong frustration in the pairwise couplings between the neurons that results in a rugged energy landscape with many local extrema; strong collective interactions in subgroups of neurons despite weak individual pairwise correlations; and a joint distribution of activity that has an extremely wide dynamic range characterized by a Zipf-like power law, strong deviations from typicality, and a number of signatures of critical behavior. We hypothesize that this tuning to a critical operating point might be a dynamic property of the system and suggest experiments to test this hypothesis
关 键 词: 视网膜神经节细胞群; 神经元; 网络活动状态分布最大熵模型
课程来源: 视频讲座网
数据采集: 2021-12-17:zkj
最后编审: 2021-12-17:zkj
阅读次数: 48