...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The Journal of Neuroscience: The Official Journal of the Society for Neuroscience >Redundancy and synergy of neuronal ensembles in motor cortex.
【24h】

Redundancy and synergy of neuronal ensembles in motor cortex.

机译：运动皮层神经元集成的冗余和协同作用。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We examined the ability of neuronal ensembles from rat motor cortex to predict behavioral performance during a reaction time task. We found that neurons that were the best individual predictors of task performance were not necessarily the neurons that contributed the most predictive information to an ensemble of neurons. To understand this result, we applied a framework for quantifying statistical relationships between neurons (Schneidman et al., 2003) to all possible combinations of neurons within our ensembles. We found that almost all neurons (96%) contributed redundant predictive information to the ensembles. This redundancy resulted in the maintenance of predictive information despite the removal of many neurons from each ensemble. Moreover, the balance of synergistic and redundant interactions depended on the number of neurons in the ensemble. Small ensembles could exhibit synergistic interactions (e.g., 23 +/- 9% of ensembles with two neurons were synergistic). In contrast, larger ensembles exhibited mostly redundant interactions (e.g., 99 +/- 0.1% of ensembles with eight neurons were redundant). We discuss these results with regard to constraints on interpreting neuronal ensemble data and with respect to motor cortex involvement in reaction time performance.
机译：我们检查了大鼠运动皮质神经元集成体预测反应时间任务期间行为表现的能力。我们发现，作为任务绩效的最佳个体预测指标的神经元不一定是对一组神经元贡献最预测信息的神经元。为了理解此结果，我们应用了一个框架来量化神经元之间的统计关系（Schneidman等人，2003）到我们集合中神经元的所有可能组合。我们发现几乎所有神经元（96％）都为集合体贡献了多余的预测信息。尽管从每个合奏中删除了许多神经元，但这种冗余仍可维持预测信息。此外，协同相互作用和冗余相互作用的平衡取决于集合中神经元的数量。小的合奏可能表现出协同作用（例如，具有两个神经元的合奏有23 +/- 9％具有协同作用）。相反，较大的乐团大多表现出多余的交互作用（例如，具有八个神经元的乐团有99 +/- 0.1％是多余的）。我们讨论这些结果有关解释神经元合奏数据的约束和关于反应时间表现中运动皮层的参与。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号