Modeling and interpreting mesoscale network dynamics.

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Generative models for network neuroscience: prospects and promise.The behavioral and cognitive relevance of time-varying, dynamic changes in functional connectivity.Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs

P2860

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P2860

Modeling and interpreting mesoscale network dynamics.

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http://www.wikidata.org/entity/Q38667383

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2017 nî lūn-bûn

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2017年の論文

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2017年学术文章

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Modeling and interpreting mesoscale network dynamics.

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Modeling and interpreting mesoscale network dynamics.

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Modeling and interpreting mesoscale network dynamics.

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P1476

Modeling and interpreting mesoscale network dynamics.

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P2093

Ankit N Khambhati

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Ann E Sizemore

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

Richard F Betzel

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P2860

Non-stationarity in the "resting brain's" modular architecture.

The human connectome: A structural description of the human brain

Generating surrogate data for time series with several simultaneously measured variables

Evolvability

Two's company, three (or more) is a simplex : Algebraic-topological tools for understanding higher-order structure in neural data

The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery

Multivoxel pattern analysis for FMRI data: a review

Neuroimaging of the Philadelphia neurodevelopmental cohort.

General overview on the merits of multimodal neuroimaging data fusion

Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD

P31

scholarly article

P356

10.1016/J.NEUROIMAGE.2017.06.029

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P407

English

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Danielle Bassett

P577

2017-06-20T00:00:00Z

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P698

28645844

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P932

5738302

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Modeling and interpreting mesoscale network dynamics.

about

P2860

P2860

Modeling and interpreting mesoscale network dynamics.

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P2860

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