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Does the Cerebral Cortex Exploit High-Dimensional Non-linear Dynamics for Information Processing?

机译:脑皮质是否利用高维非线性动力学进行信息处理?

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摘要

The discovery of stimulus induced synchronization in the visual cortex suggested the possibility that the relations among low-level stimulus features are encoded by the temporal relationship between neuronal discharges. In this framework, temporal coherence is considered a signature of perceptual grouping. This insight triggered a large number of experimental studies which sought to investigate the relationship between temporal coordination and cognitive functions. While some core predictions derived from the initial hypothesis were confirmed, these studies, also revealed a rich dynamical landscape beyond simple coherence whose role in signal processing is still poorly understood. In this paper, a framework is presented which establishes links between the various manifestations of cortical dynamics by assigning specific coding functions to low-dimensional dynamic features such as synchronized oscillations and phase shifts on the one hand and high-dimensional non-linear, non-stationary dynamics on the other. The data serving as basis for this synthetic approach have been obtained with chronic multisite recordings from the visual cortex of anesthetized cats and from monkeys trained to solve cognitive tasks. It is proposed that the low-dimensional dynamics characterized by synchronized oscillations and large-scale correlations are substates that represent the results of computations performed in the high-dimensional state-space provided by recurrently coupled networks.
机译:刺激引起的视觉皮层同步性的发现表明,低级刺激特征之间的关系可能由神经元放电之间的时间关系编码。在此框架中,时间连贯性被认为是感知分组的标志。这一见识引发了大量的实验研究,旨在研究时间协调与认知功能之间的关系。尽管从最初的假设得出的一些核心预测得到了证实,但这些研究还揭示了简单的连贯性之外的丰富动态格局,其在信号处理中的作用仍知之甚少。在本文中,我们提出了一个框架,该框架通过将特定的编码功能分配给低维动态特征(例如一方面是同步振荡和相移)以及高维非线性,非非线性,从而在皮层动力学的各种表现形式之间建立了联系。另一方面是平稳的动力学。作为这种合成方法基础的数据,是通过从麻醉猫的视觉皮层和经过训练以解决认知任务的猴子的慢性多点记录获得的。提出以同步振荡和大规模相关为特征的低维动力学是子状态,表示在递归耦合网络提供的高维状态空间中执行的计算结果。

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