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Intrinsic neural timescales: temporal integration and segregation
Trends in Cognitive Sciences ( IF 16.7 ) Pub Date : 2022-01-03 , DOI: 10.1016/j.tics.2021.11.007
Annemarie Wolff 1 , Nareg Berberian 1 , Mehrshad Golesorkhi 1 , Javier Gomez-Pilar 2 , Federico Zilio 3 , Georg Northoff 4
Affiliation  

We are continuously bombarded by external inputs of various timescales from the environment. How does the brain process this multitude of timescales? Recent resting state studies show a hierarchy of intrinsic neural timescales (INT) with a shorter duration in unimodal regions (e.g., visual cortex and auditory cortex) and a longer duration in transmodal regions (e.g., default mode network). This unimodal–transmodal hierarchy is present across acquisition modalities [electroencephalogram (EEG)/magnetoencephalogram (MEG) and fMRI] and can be found in different species and during a variety of different task states. Together, this suggests that the hierarchy of INT is central to the temporal integration (combining successive stimuli) and segregation (separating successive stimuli) of external inputs from the environment, leading to temporal segmentation and prediction in perception and cognition.



中文翻译:

内在神经时间尺度:时间整合和分离

我们不断受到来自环境的各种时间尺度的外部输入的轰炸。大脑如何处理如此多的时间尺度?最近的静息状态研究显示了内在神经时间尺度 (INT) 的层次结构,在单峰区域(例如,视觉皮层和听觉皮层)中持续时间较短,而在跨峰区域(例如,默认模式网络)中持续时间较长。这种单模态-跨模态层次结构存在于采集模式 [脑电图 (EEG)/脑磁图 (MEG) 和 fMRI] 中,并且可以在不同的物种和各种不同的任务状态中找到。总之,这表明 INT 的层次结构对于外部输入与环境的时间整合(结合连续刺激)和分离(分离连续刺激)至关重要,

更新日期:2022-01-19
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