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Valérie Cochen De Cock

Researcher at University of Montpellier

Publications -  36
Citations -  1227

Valérie Cochen De Cock is an academic researcher from University of Montpellier. The author has contributed to research in topics: REM sleep behavior disorder & Restless legs syndrome. The author has an hindex of 13, co-authored 35 publications receiving 704 citations. Previous affiliations of Valérie Cochen De Cock include McGill University & French Institute of Health and Medical Research.

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Risk and predictors of dementia and parkinsonism in idiopathic REM sleep behaviour disorder: a multicentre study

TL;DR: In a prospective multicentre study involving 1280 patients with idiopathic RBD, Postuma et al. test the predictive power of 21 prodromal markers of neurodegeneration, providing a template for planning neuroprotective trials.
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Executive control of attention in narcolepsy.

TL;DR: It is demonstrated that drug-free patients with NC and NwC complained of attention deficit, with altered executive control of attention being explained by the severity of objective sleepiness and global intellectual level.
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Genetic, Structural, and Functional Evidence Link TMEM175 to Synucleinopathies.

TL;DR: The TMEM175/GAK/DGKQ locus is the 3rd strongest risk locus in genome‐wide association studies of Parkinson disease (PD) and specific disease‐associated variants in this locus are identified and their potential implications are identified.
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Why do we move to the beat? A multi-scale approach, from physical principles to brain dynamics

TL;DR: This work defends the view that modelling brain and locomotor oscillatory activities as dynamical systems, at both neural and physical levels, provides a unified theoretical framework for the understanding of externally driven rhythmic entrainment of biological systems.
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Individualization of music-based rhythmic auditory cueing in Parkinson's disease.

TL;DR: An individualized approach to rhythmic auditory cueing with music that calls for using assistive mobile technologies capable of delivering cues that adapt in real time to patients’ gait kinematics, thus affording step synchronization to the beat.