Learn More
In recent research, many univariate and multivariate approaches have been proposed to improve automatic classification of various dementia syndromes using imaging data. Some of these methods do not provide the possibility to integrate possible confounding variables like age into the statistical evaluation. A similar problem sometimes exists in clinical(More)
Long-term motor skill learning has been consistently shown to result in functional as well as structural changes in the adult human brain. However, the effect of short learning periods on brain structure is not well understood. In the present study, subjects performed a sequential pinch force task (SPFT) for 20 min on 5 consecutive days. Changes in brain(More)
We investigated morphometric brain changes in patients with Parkinson's disease (PD) that are associated with balance training. A total of 20 patients and 16 healthy matched controls learned a balance task over a period of 6 weeks. Balance testing and structural magnetic resonance imaging were performed before and after 2, 4, and 6 training weeks. Balance(More)
The application of support vector machine classification (SVM) to combined information from magnetic resonance imaging (MRI) and [F18]fluorodeoxyglucose positron emission tomography (FDG-PET) has been shown to improve detection and differentiation of Alzheimer's disease dementia (AD) and frontotemporal lobar degeneration. To validate this approach for the(More)
INTRODUCTION We aimed at dissociating the neural correlates of memory disorders in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). METHODS We included patients with AD (n = 19, 11 female, mean age 61 years) and FTLD (n = 11, 5 female, mean age 61 years) in early stages of their diseases. Memory performance was assessed by means of(More)
BACKGROUND Neuroimaging studies show cerebellar activations in a wide range of cognitive tasks and patients with cerebellar lesions often present cognitive deficits suggesting a cerebellar role in higher-order cognition. OBJECTIVE We used cathodal transcranial direct current stimulation (tDCS), known to inhibit neuronal excitability, over the cerebellum(More)
INTRODUCTION Various biomarkers have been reported in recent literature regarding imaging abnormalities in different types of dementia. These biomarkers have helped to significantly improve early detection and also differentiation of various dementia syndromes. In this study, we systematically applied whole-brain and region-of-interest (ROI) based support(More)
The failure of current strategies to provide an explanation for controversial findings on the pattern of pathophysiological changes in Alzheimer's Disease (AD) motivates the necessity to develop new integrative approaches based on multi-modal neuroimaging data that captures various aspects of disease pathology. Previous studies using [18F]fluorodeoxyglucose(More)
Computational anatomy with magnetic resonance imaging (MRI) is well established as a noninvasive biomarker of Alzheimer's disease (AD); however, there is less certainty about its dependency on the staging of AD. We use classical group analyses and automated machine learning classification of standard structural MRI scans to investigate AD diagnostic(More)
The early diagnostic value of glucose hypometabolism and atrophy as potential neuroimaging biomarkers of mild cognitive impairment (MCI) and Alzheimer's disease (AD) have been extensively explored using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (MRI). The vast majority of previous imaging(More)