Russ Poldrack is visiting Parietal for the News workshop on June 8-9, 2017
See you there: https://news2017.sciencesconf.org/
May 22
Russ Poldrack is visiting Parietal for the News workshop on June 8-9, 2017
See you there: https://news2017.sciencesconf.org/
May 22
Joke Durnez will present our activities during this workshop.
BIS’2017 event page: https://project.inria.fr/siliconvalley/workshops/bis2017/
Nov 22
MetaMRI partners will present several works at NIPS:
Nov 01
The project aims at broaden the knowledge about accurate effect sizes and their variability in neuroimaging analysis and to provide intuition about effect sizes for different tasks and brain regions. It also aims at increasing the availability and ease the use of a variety of power analyses for neuroimaging data.
The project fund Joke Durnez (Inria Parietal, Stanford University).
Oct 01
This project funds the PhD thesis of J. Dockès.
The purpose of this thesis is to learn a semantic structure in cognitive terms from their occurrence in brain activations. This structure will simplify massive multi-label statistical-learning problems that arise in brain mapping by providing compact representations of cognitive concepts while capturing the imprecision on the definition these concepts.
Jul 23
The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.
Work supported by MetaMRI. See http://www.hal.inserm.fr/inserm-01345616
Jul 02
Our paper in Plos Computational biology is out:
We contribute a multivariate statistical learning approach that can extract the major brain networks and quantify their configuration during various psychological tasks. The method is validated in two datasets by model-based generation of synthetic activity maps from recombination of shared network topographies. We demonstrate that task-specific neural activity patterns can be explained by plausible combinations of resting-state networks.
See https://hal.archives-ouvertes.fr/hal-01338307 for more information
Feb 22
The Paris 2016 Brainhack has been an opportunity for a demonstration of the visualization capabilities of Nilearn and many improvements: better visualization, better examples. In particular, we are getting an example on seed-based correlation, for instance for resting-state, and an encoding example, mapping receptor fields in the visual cortex.
Some longer terms projects have started, such as surface-based visualization and GLM API discussions (currently in Nistats).
Stay tuned for the next release!
Oct 27
We will be presenting our recent work on the joint analysis of rest and task fMRI in Montreal.