The brain can be regarded as a network: a connected system where nodes, or units,
represent different specialized regions and links, or connections, represent communication …

The increasing power of computer technology does not dispense with the need to extract
meaningful information out of data sets of ever growing size, and indeed typically …

This work presents a novel method for learning a model that can diagnose Attention Deficit
Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional …

Sparse models are particularly useful in scientific applications, such as biomarker discovery
in genetic or neuroimaging data, where the interpretability of a predictive model is essential …

Spontaneous brain activity, as observed in functional neuroimaging, has been shown to
display reproducible structure that expresses brain architecture and carries markers of brain …

Functional connectomes capture brain interactions via synchronized fluctuations in the
functional magnetic resonance imaging signal. If measured during rest, they map the …

The observation and description of the living brain has attracted a lot of research over the
past centuries. Many noninvasive imaging modalities have been developed, such as …

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic
Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from …

There is a growing interest in automatic classification of mental disorders based on
neuroimaging data. Small training data sets (subjects) and very large amount of high …

Neuroimaging-based diagnostics could potentially assist clinicians to make more accurate
diagnoses resulting in faster, more effective treatment. We participated in the 2011 ADHD …