Experimental Otolaryngology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.
Department of Physics, Center for Medical Physics and Technology, Biophysics Group, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.
Sci Rep. 2018 Apr 3;8(1):5433. doi: 10.1038/s41598-018-23765-w.
Information in the cortex is encoded in spatiotemporal patterns of neuronal activity, but the exact nature of that code still remains elusive. While onset responses to simple stimuli are associated with specific loci in cortical sensory maps, it is completely unclear how the information about a sustained stimulus is encoded that is perceived for minutes or even longer, when discharge rates have decayed back to spontaneous levels. Using a newly developed statistical approach (multidimensional cluster statistics (MCS)) that allows for a comparison of clusters of data points in n-dimensional space, we here demonstrate that the information about long-lasting stimuli is encoded in the ongoing spatiotemporal activity patterns in sensory cortex. We successfully apply MCS to multichannel local field potential recordings in different rodent models and sensory modalities, as well as to human MEG and EEG data, demonstrating its universal applicability. MCS thus indicates novel ways for the development of powerful read-out algorithms of spatiotemporal brain activity that may be implemented in innovative brain-computer interfaces (BCI).
信息在皮质中以神经元活动的时空模式进行编码，但该代码的确切性质仍然难以捉摸。虽然对简单刺激的起始反应与皮质感觉图中的特定位置有关，但完全不清楚如何对持续刺激进行编码，因为当放电率回落到自发水平时，刺激的感知可以持续几分钟甚至更长时间。使用一种新开发的统计方法（多维聚类统计（MCS）），该方法允许比较 n 维空间中的数据点簇，我们在这里证明，关于长时间刺激的信息是在感觉皮层的持续时空活动模式中进行编码的。我们成功地将 MCS 应用于不同啮齿动物模型和感觉模态的多通道局部场电位记录，以及人类 MEG 和 EEG 数据，证明了其普遍适用性。因此，MCS 为开发强大的时空脑活动读出算法提供了新的途径，这些算法可在创新的脑机接口（BCI）中实现。
