Benchmarking functional connectome-based predictive models for resting-state fMRI

Author:

Dadi Kamalaker,Rahim Mehdi,Abraham Alexandre,Chyzhyk Darya,Milham Michael,Thirion Bertrand,Varoquaux Gaël

Funder

NiConnect project

European Union's Horizon 2020 Research and Innovation Programme

CATI project

Alzheimer’s Disease Neuroimaging Initiative

National Institutes of Health

DOD ADNI (Department of Defense

ADNI

National Institute on Aging

National Institute of Biomedical Imaging and Bioengineering

AbbVie

Alzheimer's Association

Alzheimer's Drug Discovery Foundation

Araclon Biotech; BioClinica, Inc.

Biogen

Bristol-Myers Squibb Company

CereSpir, Inc.

Cogstate

Eisai

Elan Pharmaceuticals, Inc.

Eli Lilly and Company

EuroImmun

F. Hoffmann-La Roche Ltd

Genentech, Inc.

Fujirebio

GE Healthcare

IXICO Ltd.

Janssen Alzheimer Immunotherapy Research and Development, LLC.

Johnson and Johnson Pharmaceutical Research and Development LLC.

Lumosity

Lundbeck

Merck

Meso Scale Diagnostics, LLC.

NeuroRx Research

Neurotrack Technologies

Novartis Pharmaceuticals Corporation

Pfizer Inc.

Piramal Imaging

Servier

Takeda Pharmaceutical Company

Transition Therapeutics

The Canadian Institutes of Health Research

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference106 articles.

1. Extracting Brain Regions from Rest fMRI with Total-Variation Constrained Dictionary Learning;Abraham,2013

2. Region segmentation for sparse decompositions: better brain parcellations from rest fMRI;Abraham;Front. Neuroinf.,2014

3. Deriving reproducible biomarkers from multi-site resting-state data: an autism-based example;Abraham;Neuroimage,2017

4. Machine learning for neuroimaging with scikit-learn;Abraham;Front. Neuroinf.,2014

5. Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD;Anderson;Neuroimage,2014

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