The role of neural impulse control mechanisms for dietary success in obesity.

Deficits in impulse control are discussed as key mechanisms for major worldwide health problems such as drug addiction and obesity. For example, obese subjects have difficulty controlling their impulses to overeat when faced with food items. Here, we investigated the role of neural impulse control mechanisms for dietary success in middle-aged obese subjects.

Multi-scale classification of disease using structural MRI and wavelet transform.

Recently, multivariate analysis algorithms have become a popular tool to diagnose neurological diseases based on neuroimaging data. Most studies, however, are biased for one specific scale, namely the scale given by the spatial resolution (i.e.

Can we overcome the 'clinico-radiological paradox' in multiple sclerosis?

The association between common neuroradiological markers of multiple sclerosis (MS) and clinical disability is weak, a phenomenon known as the clinico-radiological paradox. Here, we investigated to which degree it is possible to predict individual disease profiles from conventional magnetic resonance imaging (MRI) using multivariate analysis algorithms. Specifically, we conducted cross-validated canonical correlation analyses to investigate the predictive information contained in conventional MRI data of 40 MS patients for the following clinical parameters: disease duration, motor disability (9-Hole Peg Test, Timed 25-Foot Walk Test), cognitive dysfunction (Paced Auditory Serial Addition Test), and the expanded disability status scale (EDSS).

fMRI pattern recognition in obsessive-compulsive disorder.

Patients suffering from obsessive-compulsive disorder (OCD) are characterized by dysregulated neuronal processing of disorder-specific and also unspecific affective stimuli. In the present study, we investigated whether generic fear-inducing, disgust-inducing, and neutral stimuli can be decoded from brain patterns of single fMRI time samples of individual OCD patients and healthy controls. Furthermore, we tested whether differences in the underlying encoding provide information to classify subjects into groups (OCD patients or healthy controls).

MRI pattern recognition in multiple sclerosis normal-appearing brain areas.

Objective: Here, we use pattern-classification to investigate diagnostic information for multiple sclerosis (MS; relapsing-remitting type) in lesioned areas, areas of normal-appearing grey matter (NAGM), and normal-appearing white matter (NAWM) as measured by standard MR techniques.

Methods: A lesion mapping was carried out by an experienced neurologist for Turbo Inversion Recovery Magnitude (TIRM) images of individual subjects. Combining this mapping with templates from a neuroanatomic atlas, the TIRM images were segmented into three areas of homogenous tissue types (Lesions, NAGM, and NAWM) after spatial standardization.