Wittkuhn Lennart, Schuck Nicolas W
Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany.
Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
Nat Commun. 2021 Mar 19;12(1):1795. doi: 10.1038/s41467-021-21970-2.
Neural computations are often fast and anatomically localized. Yet, investigating such computations in humans is challenging because non-invasive methods have either high temporal or spatial resolution, but not both. Of particular relevance, fast neural replay is known to occur throughout the brain in a coordinated fashion about which little is known. We develop a multivariate analysis method for functional magnetic resonance imaging that makes it possible to study sequentially activated neural patterns separated by less than 100 ms with precise spatial resolution. Human participants viewed five images individually and sequentially with speeds up to 32 ms between items. Probabilistic pattern classifiers were trained on activation patterns in visual and ventrotemporal cortex during individual image trials. Applied to sequence trials, probabilistic classifier time courses allow the detection of neural representations and their order. Order detection remains possible at speeds up to 32 ms between items (plus 100 ms per item). The frequency spectrum of the sequentiality metric distinguishes between sub- versus supra-second sequences. Importantly, applied to resting-state data our method reveals fast replay of task-related stimuli in visual cortex. This indicates that non-hippocampal replay occurs even after tasks without memory requirements and shows that our method can be used to detect such spontaneously occurring replay.
神经计算通常速度快且在解剖学上具有局部性。然而，在人类中研究此类计算具有挑战性，因为非侵入性方法要么具有高时间分辨率，要么具有高空间分辨率，但不能同时具备两者。特别相关的是，已知快速神经重放以协调的方式在整个大脑中发生，而对此了解甚少。我们开发了一种用于功能磁共振成像的多变量分析方法，该方法能够以精确的空间分辨率研究间隔小于100毫秒依次激活的神经模式。人类参与者以高达32毫秒的间隔逐个顺序观看五张图像。在单个图像试验期间，基于视觉和颞下皮质的激活模式训练概率模式分类器。应用于序列试验时，概率分类器的时间进程允许检测神经表征及其顺序。在项目之间的速度高达32毫秒（每个项目再加100毫秒）时，顺序检测仍然可行。顺序度量的频谱区分亚秒级和超秒级序列。重要的是，将我们的方法应用于静息状态数据时，揭示了视觉皮质中与任务相关刺激的快速重放。这表明即使在没有记忆要求的任务之后，非海马体重放也会发生，并且表明我们的方法可用于检测这种自发发生的重放。
