Time course of information representation of macaque AIP neurons in hand manipulation task revealed by information analysis.
Time course of information representation of macaque AIP neurons in hand manipulation task revealed by information analysis.
复制标题
信息分析揭示猕猴 AIP 神经元在手操作任务中信息表征的时间过程。
作者：
Y. Sakaguchi;F. Ishida;Takashi Shimizu;A. Murata
我们使用的猕猴前顶内区（AIP）的神经元活动的互信息分析，检查信息处理过程中的手操作任务。该任务是达到把握一个三维（3D）的物体后，提出了一个去的信号。在50 ms宽的时间仓中的单个神经元的尖峰计数和6个独特的形状分类或15个这些形状的一对一分类之间计算互信息。将互信息的时空分布可视化为二维图像（“信息图”），以更好地观察信息表示的全局轮廓。此外，一个非负矩阵分解技术被应用于提取其结构。我们的主要发现是，根据不同类别的任务相关神经元的互信息的时间过程显着不同。这有力地表明，不同类别的神经元参与了不同的信息处理阶段，在执行手操作任务。另一方面，我们的分析揭示了AIP神经元信息表征的异质性。例如，即使在相同的神经元类别和相同的形状分类中，“信息延迟”（或信息起始）在各个神经元之间也是不同的。此外，一些神经元改变了“信息偏好”（即，具有最大信息量的形状分类）。这表明神经元在不同的任务时期编码不同的信息。将目前的结果与以前的研究结果结合起来，我们使用了一个甘特图来提出一个假设方案，说明不同类型的AIP神经元之间的动态相互作用。
We used mutual information analysis of neuronal activity in the macaque anterior intraparietal area (AIP) to examine information processing during a hand manipulation task. The task was to reach-to-grasp a three-dimensional (3D) object after presentation of a go signal. Mutual information was calculated between the spike counts of individual neurons in 50-ms-wide time bins and six unique shape classifications or 15 one-versus-one classifications of these shapes. The spatiotemporal distribution of mutual information was visualized as a two-dimensional image ("information map") to better observe global profiles of information representation. In addition, a nonnegative matrix factorization technique was applied for extracting its structure. Our major finding was that the time course of mutual information differed significantly according to different classes of task-related neurons. This strongly suggests that different classes of neurons were engaged in different information processing stages in executing the hand manipulation task. On the other hand, our analysis revealed the heterogeneous nature of information representation of AIP neurons. For example, "information latency" (or information onset) varied among individual neurons even in the same neuron class and the same shape classification. Further, some neurons changed "information preference" (i.e., shape classification with the largest amount of information) across different task periods. These suggest that neurons encode different information in the different task periods. Taking the present result together with previous findings, we used a Gantt chart to propose a hypothetical scheme of the dynamic interactions between different types of AIP neurons.
影响因子：
2.5
作者：
Victor, JD;Purpura, KP
通讯作者：
Purpura, KP