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Detecting Synchronous Cell Assemblies with Limited Data and Overlapping Assemblies

机译:使用受限数据和重叠程序集检测同步单元程序集

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摘要

Two statistical methods—cross-correlation (Moore et al. 1966) and gravity clustering (Gerstein et al. 1985)—were evaluated for their ability to detect synchronous cell assemblies from simulated spike train data. The two methods were first analyzed for their temporal sensitivity to synchronous cell assemblies. The presented approach places a lower bound on the amount of data required to detect a synchronous assembly. On average, both methods required the same minimum amount of recording time to detect significant pairwise correlations, but the gravity method exhibited less variance in the recording time. The precise length of recording depends on the consistency with which a neuron fires synchronously with the assembly but was independent of the assembly firing rate. Next, the statistical methods were tested with respect to their ability to differentiate two distinct assemblies that overlapped in time and space. Both statistics could adequately differentiate two overlapping synchronous assemblies. For cross-correlation, this ability deteriorates quickly when considering three or more simultaneously active, overlapping assemblies, whereas the gravity method should be more flexible in this regard. The work demonstrates the difficulty of detecting assembly phenomena from simultaneous neuronal recordings. Other statistical methods and the detection of other types of assemblies are also discussed.
机译:对两种统计方法(互相关(Moore等人,1966年)和重力聚类(Gerstein等人,1985年)进行了评估,以评估它们从模拟峰值序列数据中检测同步单元装配的能力。首先分析这两种方法对同步电池组件的时间敏感性。提出的方法对检测同步程序集所需的数据量设置了下限。平均而言,两种方法都需要相同的最小记录时间量才能检测到显着的成对相关性,但是重力方法显示出的记录时间变化较小。记录的精确长度取决于神经元与程序集同步触发的一致性,但与程序集触发率无关。接下来,就统计方法区分时空重叠的两个不同程序集的能力进行了测试。两种统计信息都可以充分区分两个重叠的同步程序集。对于互相关,当考虑三个或更多同时活动的重叠组件时,此功能会迅速变差,而重力方法在这方面应该更加灵活。这项工作证明了从同时的神经元记录中检测组装现象的难度。还讨论了其他统计方法和其他类型的程序集的检测。

著录项

  • 来源
    《Neural computation》 |1997年第1期|51-76|共26页
  • 作者

    Strangman G;

  • 作者单位

    Department of Cognitive and Linguistic Sciences, Brown University, Providence, RI 02912 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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