Alexandre Abraham

Cognitive Neuroscience · NeuroImage · 2014–2019

A researcher in the Science corpus: 5 papers; trusts 10 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 121 citations into it
• Radiology, Nuclear Medicine and Imaging — 70 citations into it
• Signal Processing — 15 citations into it
• Statistics and Probability — 13 citations into it
• Experimental and Cognitive Psychology — 9 citations into it
• Analytical Chemistry — 5 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Alexandre Abraham trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Stephen M. Smith
2. Christian F. Beckmann
3. R. Craddock
4. Trevor J. Hastie
5. Bertrand Thirion
6. Gaël Varoquaux
7. Jerome H. Friedman
8. Michael D. Greicius
9. Olivier Ledoit
10. Aapo Hyvärinen

Who trusts Alexandre Abraham overall

1. Sarah Parisot
2. Sofia Ira Ktena
3. Gaël Varoquaux
4. Kamalaker Dadi
5. Charlotte Caucheteux
6. Dan Ofer
7. Nikolaas N. Oosterhof
8. Taban Eslami
9. Enzo Ferrante
10. Mehdi Rahim

Papers from Alexandre Abraham's perspective

Ordered by how strongly the researchers Alexandre Abraham trusts endorse each paper. Same corpus, a different order for every researcher.

1. Probabilistic independent component analysis for functional magnetic resonance imaging (IEEE Transactions on Medical Imaging)
2. The Human Connectome: A Structural Description of the Human Brain
3. Network modelling methods for FMRI
4. The global signal and observed anticorrelated resting state brain networks. (Journal of Neurophysiology)
5. Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI (Proc. Natl. Acad. Sci. USA)
6. Advances in functional and structural MR image analysis and implementation as FSL.
7. Correspondence of the brain's functional architecture during activation and rest
8. Prediction of Individual Brain Maturity Using fMRI (Science)
9. Mapping the Structural Core of Human Cerebral Cortex (PLoS Biology)
10. Scikit-learn: Machine Learning in Python

Their papers

• Benchmarking functional connectome‐based predictive models for resting‐state fMRI (2019) — 312 citations
• Deriving reproducible biomarkers from multi‐site resting‐state data: An Autism‐based example (2016) — 654 citations
• Predicting brain-age from multimodal imaging data captures cognitive impairment (2016) — 505 citations
• Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease (2015) — 11 citations
• Machine learning for neuroimaging with scikit-learn (2014) — 2,159 citations