期刊
ELIFE
卷 11, 期 -, 页码 -出版社
eLIFE SCIENCES PUBL LTD
DOI: 10.7554/eLife.75769
关键词
memory; sleep spindles; memory consolidation; deep learning; Human; Rhesus macaque
类别
资金
- Canada First Research Excellence Fund
- National Science Foundation [2015276]
- Fields Institute for Research in Mathematical Sciences
- Compute Canada
- Kyoto University
- Div Of Biological Infrastructure
- Direct For Biological Sciences [2015276] Funding Source: National Science Foundation
Sleep is not just a state of large-scale synchrony across thalamus and neocortex, but also involves isolated sleep rhythms such as slow oscillations and spindles. This study used deep learning algorithms to analyze neural recordings during sleep and found that widespread spindles occur more frequently than previously reported. The study also investigated the spatiotemporal patterns of these spindles and their changes after a visual memory task, revealing a potential role for widespread, multi-area spindles in memory consolidation across primate cortex.
Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of sleep rhythms? To answer this question, we adapted deep learning algorithms initially developed for detecting earthquakes and gravitational waves in high-noise settings for analysis of neural recordings in sleep. We then studied sleep spindles in non-human primate electrocorticography (ECoG), human electroencephalogram (EEG), and clinical intracranial electroencephalogram (iEEG) recordings in the human. Within each recording type, we find widespread spindles occur much more frequently than previously reported. We then analyzed the spatiotemporal patterns of these large-scale, multi-area spindles and, in the EEG recordings, how spindle patterns change following a visual memory task. Our results reveal a potential role for widespread, multi-area spindles in consolidation of memories in networks widely distributed across primate cortex.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据