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作者机构:RIKEN Brain Science Institute 2-1 Hirosawa Wako-shi Saitama 351-0198 Japan. Commonwealth Computer Research Inc. 1422 Sachem Pl. Unit #1 Charlottesville VA 22901 U.S.A. Graduate School of Pharmaceutical Sciences The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan. Heart to Heart Science Center for Information and Neural Networks 1-4 Yamadaoka Suita Osaka 565-0871 Japan. Department of Computational Intelligence and Systems Science Tokyo Institute of Technology Yokohama 226-8502 Japan.
出 版 物:《SCIENTIFIC REPORTS》 (Sci. Rep.)
年 卷 期:2015年第5卷第1期
页 面:1-13页
核心收录:
基 金:Ministry of Health, Labour and Welfare, MHLW RIKEN, (22115003) RIKEN
摘 要:Activity patterns of neural population are constrained by underlying biological mechanisms. These patterns are characterized not only by individual activity rates and pairwise correlations but also by statistical dependencies among groups of neurons larger than two, known as higher-order interactions (HOIs). While HOIs are ubiquitous in neural activity, primary characteristics of HOIs remain unknown. Here, we report that simultaneous silence (SS) of neurons concisely summarizes neural HOIs. Spontaneously active neurons in cultured hippocampal slices express SS that is more frequent than predicted by their individual activity rates and pairwise correlations. The SS explains structured HOIs seen in the data, namely, alternating signs at successive interaction orders. Inhibitory neurons are necessary to maintain significant SS. The structured HOIs predicted by SS were observed in a simple neural population model characterized by spiking nonlinearity and correlated input. These results suggest that SS is a ubiquitous feature of HOIs that constrain neural activity patterns and can influence information processing.