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Scikit-learn: Machine Learning in Python
Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringingExpand
A framework to study the cortical folding patterns
A framework of using artificial neuroanatomists that are trained to identify sulci from a database is developed, which relies on a renormalization of the brain warping problem, which consists in matching the cortices at the scale of the folds. Expand
Asynchrony of the early maturation of white matter bundles in healthy infants: Quantitative landmarks revealed noninvasively by diffusion tensor imaging
A specific maturation model, based on the respective roles of different maturational processes on the diffusion phenomena, was designed to highlight asynchronous maturation across bundles by evaluating the time‐course of mean diffusivity and anisotropy changes over the considered developmental period. Expand
Inverse retinotopy: Inferring the visual content of images from brain activation patterns
This work uses the well-known retinotopy of the visual cortex to infer the visual content of real or imaginary scenes from the brain activation patterns that they elicit, and presents two decoding algorithms that could reconstruct and predict with significant accuracy a pattern imagined by the subjects. Expand
Object-based morphometry of the cerebral cortex
This study reveals some correlates of handedness on the size of the sulci located in motor areas, which was not detected previously using standard voxel based morphometry. Expand
Significant correlation between a set of genetic polymorphisms and a functional brain network revealed by feature selection and sparse Partial Least Squares
This paper investigates the use of different strategies of regularisation and dimension reduction techniques combined with PLS or CCA to face the very high dimensionality of imaging genetics studies, and estimates the generalisability of the multivariate association with a cross-validation scheme. Expand
Cortical folding abnormalities in schizophrenia patients with resistant auditory hallucinations
Sulcal abnormalities in language-related cortex might underlie these patients' particular vulnerability to hallucinations and suggest abnormalities in cortical gyrification in these patients. Expand
Feature selection and classification of imbalanced datasets Application to PET images of children with autistic spectrum disorders
A feature selection/classification algorithm based on generative methods is proposed in order to predict the clinical status of a highly imbalanced dataset made of PET scans of forty-five low-functioning children with autism spectrum disorders (ASD) and thirteen non-ASD low functioning children. Expand
Striatal and extrastriatal dopamine transporter in cannabis and tobacco addiction: a high‐resolution PET study
The results support the existence of a decrease in DAT availability associated with tobacco and cannabis addictions involving all dopaminergic brain circuits and are consistent with the idea of a global decrease in cerebral DA activity in dependent subjects. Expand
Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer's disease.
The findings emphasize the potential of 18FDG-positron emission tomography for monitoring early Alzheimer's disease progression and suggest that compensatory processes may occur in this dorso-medial prefrontal region. Expand