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Being able to detect reliably functional activity in a population of subjects is crucial in human brain mapping, both for the understanding of cognitive functions in normal subjects and for the analysis of patient data. The usual approach proceeds by normalizing brain volumes to a common three-dimensional template. However, a large part of the data acquired(More)
The main objective of this structural magnetic resonance imaging (MRI) study was to investigate, using diffusion tensor imaging, whether a neurofeedback training (NFT) protocol designed to improve sustained attention might induce structural changes in white matter (WM) pathways, purportedly implicated in this cognitive ability. Another goal was to examine(More)
This paper presents a connectivity-based parcellation of the human post-central gyrus, at the level of the group of subjects. The dimension of the clustering problem is reduced using a set of cortical regions of interest determined at the inter-subject level using a surface-based coordinate system, and representing the regions with a strong connection to(More)
Group studies of functional magnetic resonance imaging datasets are usually based on the computation of the mean signal across subjects at each voxel (random effects analyses), assuming that all subjects have been set in the same anatomical space (normalization). Although this approach allows for a correct specificity (rate of false detections), it is not(More)
Individuals with post-traumatic stress disorder (PTSD) exhibit exaggerated emotional reactions to threatening stimuli, which may represent deregulated fear-conditioning, associated with long-term adaptations in the sympathetic nervous system. Within a repeated measures design, functional magnetic resonance imaging (fMRI) was employed to investigate neural(More)
Gilles de la Tourette syndrome is a childhood-onset syndrome characterized by the presence and persistence of motor and vocal tics. A dysfunction of cortico-striato-pallido-thalamo-cortical networks in this syndrome has been supported by convergent data from neuro-pathological, electrophysiological as well as structural and functional neuroimaging studies.(More)
Inferring the position of functionally active regions from a multi-subject fMRI dataset involves the comparison of the individual data and the inference of a common activity model. While voxel-based analyzes, e.g. Random Effect statistics, are widely used, they do not model each individual activation pattern. Here, we develop a new procedure that extracts(More)
In this paper, we study the recognition of about 60 sulcal structures over a new T1 MRI database of 62 subjects. It continues our previous work [7] and more specifically extends the localization model of sulci (SPAM). This model is sensitive to the chosen common space during the group study. Thus, we focus the current work on refining this space using(More)
Understanding brain structure and function entails the inclusion of anatomical and functional information in a common space, in order to study how these different informations relate to each other in a population of subjects. In this paper, we revisit the parcellation model and explicitly combine anatomical features, i.e. a segmentation of the cortex into(More)
Huntington disease (HD) is associated with early and severe damage to the basal ganglia and particularly the striatum. We investigated cortico-striatal connectivity modifications occurring in HD patients using a novel approach which focuses on the projection of the connectivity profile of the basal ganglia onto the cortex. This approach consists in(More)