Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

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Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

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2016 nî lūn-bûn

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2016年の論文

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2016年学术文章

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2016年学术文章

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2016年学术文章

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2016年学术文章

@zh-my

2016年学术文章

@zh-sg

2016年學術文章

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2016年學術文章

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2016年學術文章

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Quantifying Individual Brain C ...... mponent Analysis for Networks.

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Quantifying Individual Brain C ...... mponent Analysis for Networks.

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label

Quantifying Individual Brain C ...... mponent Analysis for Networks.

@en

Quantifying Individual Brain C ...... mponent Analysis for Networks.

@nl

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Quantifying Individual Brain C ...... mponent Analysis for Networks.

@en

Quantifying Individual Brain C ...... mponent Analysis for Networks.

@nl

P1476

Quantifying Individual Brain C ...... mponent Analysis for Networks.

@en

P2093

Alexander Petersen

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Hans-Georg Müller

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Jianyang Zhao

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Owen Carmichael

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P2860

Intra- and inter-frequency brain network structure in health and schizophrenia

Complex network measures of brain connectivity: uses and interpretations

A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs

Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease

Regional homogeneity approach to fMRI data analysis.

Normalized cut group clustering of resting-state FMRI data

Comparing brain networks of different size and connectivity density using graph theory.

Brain network analysis: separating cost from topology using cost-integration.

Adaptive strategy for the statistical analysis of connectomes.

P304

540-547

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P31

scholarly article

P356

10.1089/BRAIN.2016.0420

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P433

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P478

http://www.w3.org/2001/XMLSchema#string

P577

2016-06-07T00:00:00Z

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P698

27267074

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P921

principal component analysis

P932

5084364

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