Statistical Learning for Resting-State fMRI: Successes and Challenges

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Statistical Learning for Resting-State fMRI: Successes and Challenges

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wetenschappelijk artikel

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наукова стаття, опублікована у 2012

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Statistical Learning for Resting-State fMRI: Successes and Challenges

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Statistical Learning for Resting-State fMRI: Successes and Challenges

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Statistical Learning for Resting-State fMRI: Successes and Challenges

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Statistical Learning for Resting-State fMRI: Successes and Challenges

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Statistical Learning for Resting-State fMRI: Successes and Challenges

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Statistical Learning for Resting-State fMRI: Successes and Challenges

@nl

P1476

Statistical Learning for Resting-State fMRI: Successes and Challenges

@en

P2860

Toward discovery science of human brain function

Consistent resting-state networks across healthy subjects

Functional connectivity in the motor cortex of resting human brain using echo-planar MRI

Complex brain networks: graph theoretical analysis of structural and functional systems

Probabilistic independent component analysis for functional magnetic resonance imaging

A method for making group inferences from functional MRI data using independent component analysis.

Uncovering intrinsic modular organization of spontaneous brain activity in humans.

Advances and pitfalls in the analysis and interpretation of resting-state FMRI data.

Independent component analysis for brain fMRI does not select for independence

A group model for stable multi-subject ICA on fMRI datasets.

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172-177

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scholarly article

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10.1007/978-3-642-34713-9_22

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P407

English

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Gaël Varoquaux

Bertrand Thirion

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2012-01-01T00:00:00Z

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Amar