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A dynamic spatiotemporal representation framework for deciphering personal brain function

delete2025-09-05
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OA
AI
X
Xuyang Wang
T
Ting Zou
H
Haofei Wang
H
Huafu Chen *
V
Vince D. Calhoun *
R
Rong Li *
DOI:10.1016/j.neuroimage.2025.121443delete
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Abstract

Abstract

En 中文
• A simple yet effective framework decomposes whole brain dynamics into four fundamental states • State sequences derive multi-mode representations of brain function at regional and network levels. • State-based representations serve as discriminative ‘brain fingerprints’ for identifying individuals. • State-based representations enhance the power of brain-phenotype modeling.
Keywords:
Functional MRI
State decomposition
Functional representation
Brain-phenotype modeling
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

NeuroImage cover
NeuroImage
IF:
4.5
Papers:
1.5K
Citations:
10.6W

Organization

U
university of electronic science and technology of china
Scholars:
1.3W
Papers: 4.8K
Citations: 4
E
Emory University
Scholars:
5.0W
Papers: 4.2W
Citations: 5.7W
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