Decoding and modelling of brain function with fMRI

Spatial patterns of spontaneous activity

Algorithms and models for extracting salient and reproducible spatial features from the correlation structure of functional MRI images without using a paradigm, such as in resting-state studies

misc

Various contributions related to decoding work

Brain decoding and inverse inference in fMRI.

A new approach for brain decoding, called inverse inference (or brain-reading), has been introduced recently [Dehaene 98, Cox 03]. This method relies on statistical learning tools, and more precisely on pattern recognition approaches. The main idea is to consider the fMRI analysis as a pattern recognition problem, i.e. using a pattern of voxels to predict a behavioral, perceptual or cognitive variable. In this approach, the accuracy of the prediction can be used to validate (or invalidate) that the pattern of voxels used in the predictive model is implied in the neural coding. In short, inverse inference is an approach for decoding the neural coding.