887 citations · 924 across the 5 of their papers we have counts for
5 papers
Assessing and tuning brain decoders: cross-validation, caveats, and guidelines
Gaël Varoquaux, Pradeep Reddy Raamana, Denis Engemann +3
Decoding, ie prediction from brain images or signals, calls for empirical evaluation of its predictive power. Such evaluation is achieved via cross-validation, a method also used t…
Mapping cognitive ontologies to and from the brain
Yannick Schwartz, Bertrand Thirion, Gaël Varoquaux
Imaging neuroscience links brain activation maps to behavior and cognition via correlational studies. Due to the nature of the individual experiments, based on eliciting neural res…
PyXNAT: XNAT in Python
Yannick Schwartz, Alexis Barbot, Benjamin Thyreau +5
As neuroimaging databases grow in size and complexity, the time researchers spend investigating and managing the data increases to the expense of data analysis. As a result, invest…
Improving accuracy and power with transfer learning using a meta-analytic database
Yannick Schwartz, Gaël Varoquaux, Christophe Pallier +3
Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investiga…
On spatial selectivity and prediction across conditions with fMRI
Yannick Schwartz, Gaël Varoquaux, Bertrand Thirion
Researchers in functional neuroimaging mostly use activation coordinates to formulate their hypotheses. Instead, we propose to use the full statistical images to define regions of…