Collective Behavior of Place and Non-place Neurons in the Hippocampal Network
Collective Behavior of Place and Non-place Neurons in the Hippocampal Network
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DOI：
10.1016/j.neuron.2017.10.027
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发表时间：
2017-12-06
期刊：
影响因子：
16.2
通讯作者：
Bialek, William
中科院分区：
文献类型：
--
作者：
Meshulam, Leenoy;Gauthier, Jeffrey L.;Bialek, William
关于海马体的讨论通常集中在位置细胞上，但许多神经元在任何给定的环境中都不是位置细胞。在这里，我们描述的集体活动，在这样的混合人口，治疗的地方和非地方细胞在同一基础上。我们首先对小鼠的CA 1进行光学成像实验，因为它们沿着沿着一个虚拟的线性轨道运行，并使用最大熵方法来近似群体中活动模式的分布，匹配细胞对之间的相关性，但在其他方面假设尽可能少的结构。我们发现，这些简单的模型可以根据网络中所有其他神经元的状态准确地预测每个神经元的活动，而不管该神经元对位置的编码有多好。我们的研究结果表明，了解神经活动可能不仅需要了解外部变量调制它，但也内部网络状态。
Discussions of the hippocampus often focus on place cells, but many neurons are not place cells in any given environment. Here we describe the collective activity in such mixed populations, treating place and non-place cells on the same footing. We start with optical imaging experiments on CA1 in mice as they run along a virtual linear track and use maximum entropy methods to approximate the distribution of patterns of activity in the population, matching the correlations between pairs of cells but otherwise assuming as little structure as possible. We find that these simple models accurately predict the activity of each neuron from the state of all the other neurons in the network, regardless of how well that neuron codes for position. Our results suggest that understanding the neural activity may require not only knowledge of the external variables modulating it but also of the internal network state.