Kamalaker Dadi
Cognitive Neuroscience · 2019
A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 61 citations into it
- Radiology, Nuclear Medicine and Imaging — 35 citations into it
- Statistics and Probability — 16 citations into it
- Experimental and Cognitive Psychology — 9 citations into it
Whom Kamalaker Dadi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Stephen M. Smith
- Trevor J. Hastie
- Joshua Carp
- Gaël Varoquaux
- Jerome H. Friedman
- Christian F. Beckmann
- Alexandre Abraham
- Bertrand Thirion
- Olaf Sporns
- R. Craddock
Papers from Kamalaker Dadi's perspective
Ordered by how strongly the researchers Kamalaker Dadi 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
- Prediction of Individual Brain Maturity Using fMRI (Science)
- Correspondence of the brain's functional architecture during activation and rest
- Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain (NeuroImage)
- 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)
- The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? (NeuroImage)
Their papers
- Variability in the analysis of a single neuroimaging dataset by many teams (2019) — 901 citations
- Benchmarking functional connectome‐based predictive models for resting‐state fMRI (2019) — 312 citations