Xavier Guell
Cognitive Neuroscience · 2018
A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 56 citations into it
- Radiology, Nuclear Medicine and Imaging — 38 citations into it
- Neurology — 28 citations into it
- Social Psychology — 16 citations into it
- Endocrine and Autonomic Systems — 6 citations into it
- Sensory Systems — 5 citations into it
Whom Xavier Guell trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jeremy D. Schmahmann
- Jörn Diedrichsen
- Catherine J. Stoodley
- Matthew F. Glasser
- Stephen M. Smith
- P. Lachenbruch
- Klaus Nordhausen
- Mark Jenkinson
- Steen Moeller
- David C. Van Essen
Who trusts Xavier Guell overall
Papers from Xavier Guell's perspective
Ordered by how strongly the researchers Xavier Guell trusts endorse each paper. Same corpus, a different order for every researcher.
- Multiplexed Echo Planar Imaging for Sub-Second Whole Brain FMRI and Fast Diffusion Imaging (PLoS ONE)
- Correspondence of the brain's functional architecture during activation and rest
- Multiband Multislice GE-EPI at 7 Tesla, With 16-Fold Acceleration Using Partial Parallel Imaging With Application to High Spatial and Temporal Whole-Brain FMRI (Magnetic Resonance in Medicine)
- Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images (NeuroImage)
- A multi-modal parcellation of human cerebral cortex (Nature)
- Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data (NeuroImage)
- The Amygdala Response to Emotional Stimuli: A Comparison of Faces and Scenes (NeuroImage)
- Resting-state functional connectivity reflects structural connectivity in the default mode network. (Cerebral Cortex)
- Predicting human resting-state functional connectivity from structural connectivity (Proceedings of the National Academy of Sciences of the United States of America)
- Informatics and Data Mining Tools and Strategies for the Human Connectome Project