Mehdi Rahim
Cognitive Neuroscience · 2015–2019
A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 76 citations into it
- Radiology, Nuclear Medicine and Imaging — 52 citations into it
- Experimental and Cognitive Psychology — 6 citations into it
- Statistics and Probability — 6 citations into it
Whom Mehdi Rahim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Gaël Varoquaux
- Stephen M. Smith
- Bertrand Thirion
- Alexandre Gramfort
- Trevor J. Hastie
- Joshua Carp
- Jerome H. Friedman
- Christian F. Beckmann
- Daoqiang Zhang
- Alexandre Abraham
Who trusts Mehdi Rahim overall
Papers from Mehdi Rahim's perspective
Ordered by how strongly the researchers Mehdi Rahim trusts endorse each paper. Same corpus, a different order for every researcher.
- Probabilistic independent component analysis for functional magnetic resonance imaging (IEEE Transactions on Medical Imaging)
- The global signal and observed anticorrelated resting state brain networks. (Journal of Neurophysiology)
- Network modelling methods for FMRI
- The Human Connectome: A Structural Description of the Human Brain
- Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain (NeuroImage)
- Resting-state functional connectivity in neuropsychiatric disorders (Current Opinion in Neurology)
- Machine learning classifiers and fMRI: a tutorial overview
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- A positive-negative mode of population covariation links brain connectivity, demographics and behavior (Nature Neuroscience)
- Functional segmentation of the brain cortex using high model order group PICA (Human Brain Mapping)
Their papers
- Benchmarking functional connectome‐based predictive models for resting‐state fMRI (2019) — 312 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