期刊
TRENDS IN NEUROSCIENCES
卷 40, 期 5, 页码 260-275出版社
ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tins.2017.03.005
关键词
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资金
- NSF/NIH CRCNS award from the US National Science Foundation [IIS-1307645]
- NSF/NIH CRCNS award from the NINDS [R01-NS100065]
- Office of Naval Research MURI grant [N00014-10-1-0936]
- NIH [TR01-GM104948]
- Center for Brains, Minds, and Machines (CBMM) - NSF STC award [CCF-1231216]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1443032] Funding Source: National Science Foundation
Memories of experiences are stored in the cerebral cortex. Sleep is critical for the consolidation of hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms in memory consolidation and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches to the analysis of sleep-associated neural codes (SANCs). We focus on two analysis paradigms for sleep-associated memory and propose a new unsupervised learning framework ('memory first, meaning later') for unbiased assessment of SANCs.
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