Publications by authors named "R J Renken"

Introduction: The Next Move in Movement Disorders (NEMO) study is an initiative aimed at advancing our understanding and the classification of hyperkinetic movement disorders, including tremor, myoclonus, dystonia, and myoclonus-dystonia. The study has two main objectives: (a) to develop a computer-aided tool for precise and consistent classification of these movement disorder phenotypes, and (b) to deepen our understanding of brain pathophysiology through advanced neuroimaging techniques. This protocol review details the neuroimaging data acquisition and preprocessing procedures employed by the NEMO team to achieve these goals.

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Article Synopsis
  • Multiple sclerosis (MS) has two primary types: relapse-remitting MS (RRMS) and progressive MS (PMS), which differ in disability and treatment response, making it hard to identify using traditional MRI.
  • A study utilized scaled subprofile modeling with principal component analysis (SSM/PCA) on MRI scans from RRMS and PMS patients to better distinguish these MS types.
  • Results showed that qihMT imagery provided the best differentiation between PMS and RRMS at 87% specificity, while Tw data offered higher sensitivity at 93%; when both analyses agreed, prediction accuracy increased significantly for identifying MS phenotypes.
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Tinnitus is a common phantom auditory percept believed to be related to plastic changes in the brain due to hearing loss. However, tinnitus can also occur in the absence of any clinical hearing loss. In this case, since there is no hearing loss, the mechanisms that drive plastic changes remain largely enigmatic.

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In machine learning, data often comes from different sources, but combining them can introduce extraneous variation that affects both generalization and interpretability. For example, we investigate the classification of neurodegenerative diseases using FDG-PET data collected from multiple neuroimaging centers. However, data collected at different centers introduces unwanted variation due to differences in scanners, scanning protocols, and processing methods.

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Research has shown that maladaptive personality characteristics, such as Neuroticism, are associated with poor outcome after mild traumatic brain injury (mTBI). The current exploratory study investigated the neural underpinnings of this process using dynamic functional network connectivity (dFNC) analyses of resting-state (rs) fMRI, and diffusion MRI (dMRI). Twenty-seven mTBI patients and 21 healthy controls (HC) were included.

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