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A probabilistic approach to discovering dynamic full-brain functional connectivity patterns.

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Title: A probabilistic approach to discovering dynamic full-brain functional connectivity patterns.
Authors: Manning JR; Dartmouth College, Hanover, NH, United States. Electronic address: jeremy.r.manning@dartmouth.edu., Zhu X; Intel Corporation, Hillsboro, OR, United States., Willke TL; Intel Corporation, Hillsboro, OR, United States., Ranganath R; Princeton University, Princeton, NJ, United States., Stachenfeld K; DeepMind, London, UK., Hasson U; Princeton University, Princeton, NJ, United States., Blei DM; Columbia University, New York, NY, United States., Norman KA; Princeton University, Princeton, NJ, United States.
Source: NeuroImage [Neuroimage] 2018 Oct 15; Vol. 180 (Pt A), pp. 243-252. Date of Electronic Publication: 2018 Feb 12.
Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.; Review
Journal Info: Publisher: Academic Press Country of Publication: United States NLM ID: 9215515 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-9572 (Electronic) Linking ISSN: 10538119 NLM ISO Abbreviation: Neuroimage Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="JN" term="%229215515%22">NeuroImage</searchLink> [Neuroimage] 2018 Oct 15; Vol. 180 (Pt A), pp. 243-252. <i>Date of Electronic Publication: </i>2018 Feb 12.
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