We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector ma...
BACKGROUND: White matter hyperintensities (WMHs) are foci of abnormal signal intensity in white matter regions seen with magnetic resonance imaging (MRI). WMHs are associated with normal ageing and have shown prognostic value in neurological conditio...
The analysis of positron emission tomography (PET) scan image is challenging due to a high level of noise and a low resolution and also because differences between healthy and demented are very subtle. High dimensional classification methods based on...
Alzheimer's disease (AD) is a chronic neurodegenerative disease of the central nervous system that has no cure and leads to death. One of the most prevalent tools for AD diagnosis is magnetic resonance imaging (MRI), because of its capability to visu...
BACKGROUND: Robot-assisted and treadmill-gait training are promising neurorehabilitation techniques, with advantages over conventional gait training, but the neural substrates underpinning locomotor control remain unknown particularly during differen...
Research on an early detection of Mild Cognitive Impairment (MCI), a prodromal stage of Alzheimer's Disease (AD), with resting-state functional Magnetic Resonance Imaging (rs-fMRI) has been of great interest for the last decade. Witnessed by recent s...
Classification of individuals based on patterns of brain activity observed in functional MRI contrasts may be helpful for diagnosis of neurological disorders. Prior work for classification based on these patterns have primarily focused on using a sin...
The Journal of neuroscience : the official journal of the Society for Neuroscience
May 6, 2015
Trunk motor control is crucial for postural stability and propulsion after low thoracic spinal cord injury (SCI) in animals and humans. Robotic rehabilitation aimed at trunk shows promise in SCI animal models and patients. However, little is known ab...
Multivariate pattern analysis (MVPA) methods have become an important tool in neuroimaging, revealing complex associations and yielding powerful prediction models. Despite methodological developments and novel application domains, there has been litt...
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