Testing the model of caudo-rostral organization of cognitive control in the human with frontal lesions.

The cascade model of cognitive control, mostly relying on functional neuroimaging studies, stipulates that the lateral frontal cortex (LFC) is organized as a cascade of executive processes involving three levels of cognitive control, implemented in distinct LFC areas from the premotor to the anterior prefrontal regions. The present experiment tested this model in patients with LFC lesions and studied the hierarchy of executive functions along the caudo-rostral axis, i.e. the respective roles of the different LFC areas in the control of behavior. Voxel-based lesion-symptom mapping and region of interest group analyses were conducted in 32 patients with focal LFC lesions who performed cognitive tasks assessing the cascade model. We first showed that three different LFC areas along the caudo-rostral axis subserved three distinct control levels, whose integrity is necessary for adaptive behavior. Second, we found that prefrontal cognitive control has an asymmetric organization: higher control processes involving more anterior prefrontal regions rely on the integrity of lower control processes in more posterior regions, while lower control processes can operate irrespective of the integrity of higher control processes. Altogether, these findings support a caudo-rostral cascade of executive processes from premotor to anterior prefrontal regions.

VBM anticipates the rate of progression of Alzheimer disease: a 3-year longitudinal study.

OBJECTIVE: To determine whether regional atrophy or neuropsychological factors can predict the rate of decline in patients with mild Alzheimer disease (AD). BACKGROUND: Despite important implications for planning the care and treatment strategy, few prognostic factors of severe AD progression are known. METHODS: Twenty-three patients with mild AD were followed up every 6 months over the course of 3 years. At baseline, patients with AD and 18 controls underwent a neuropsychological battery and a brain MRI. At the end of the 3 years, patients with AD were dichotomized into slow decliners (SLD) or fast decliners (FD) groups on the basis of their decline in Mini-Mental State Examination score over time. We compared baseline cognitive performance and imaging data using voxel-based morphometry (VBM). RESULTS: SLD and FD groups did not differ in age, gender, level of education, mean estimated duration of illness, and standard neuropsychological data at inclusion, except for the Attentional Battery of the Cambridge Neuropsychological Tests Automated Battery (speed processing in shifting condition). VBM comparison between SLD and FD groups demonstrated more gray matter tissue loss in the FD group in the medial occipitoparietal areas, especially in the precuneus, the lingual gyrus, the cuneus, and the surrounding cortex of the parieto-occipital sulcus bilaterally. CONCLUSION: Voxel-based morphometry analysis demonstrated that patients who will have a faster decline at 3 years already had a more extensive cortical atrophy than SLD patients, especially in the medial occipitoparietal areas, which was not yet detected by clinical and neuropsychological assessment.

Federating distributed and heterogeneous information sources in neuroimaging: the NeuroBase Project.

The NeuroBase project aims at studying the requirements for federating, through the Internet, information sources in neuroimaging. These sources are distributed in different experimental sites, hospitals or research centers in cognitive neurosciences, and contain heterogeneous data and image processing programs. More precisely, this project consists in creating of a shared ontology, suitable for supporting various neuroimaging applications, and a computer architecture for accessing and sharing relevant distributed information. We briefly describe the semantic model and report in more details the architecture we chose, based on a media-tor/wrapper approach. To give a flavor of the future deployment of our architecture, we de-scribe a demonstrator that implements the comparison of distributed image processing tools applied to distributed neuroimaging data.