scispace - formally typeset
M

Mark Hallett

Researcher at National Institutes of Health

Publications -  1234
Citations -  136876

Mark Hallett is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Transcranial magnetic stimulation & Motor cortex. The author has an hindex of 186, co-authored 1170 publications receiving 123741 citations. Previous affiliations of Mark Hallett include Government of the United States of America & Armed Forces Institute of Pathology.

Papers
More filters
Journal ArticleDOI

Trial of magnetic resonance-guided putaminal gene therapy for advanced Parkinson's disease.

TL;DR: To investigate the safety and tolerability of convection‐enhanced delivery of an adeno‐associated virus, serotype‐2 vector carrying glial cell line‐derived neurotrophic factor into the bilateral putamina of PD patients, convection-enhanced delivered virus is used.
Journal ArticleDOI

Treatment of action tremor in multiple sclerosis with isoniazid

TL;DR: Four patients with disabling action tremor in the setting of MS were treated with isoniazid (800 to 1200 mg per day), showing significant improvement of the tremor, allowing more functional use of their extremities.
Journal ArticleDOI

Relevance of Stimulus Duration for Activation of Motor and Sensory Fibers: Implications for the Study of H-Reflexes and Magnetic Stimulation

TL;DR: In this article, the authors studied the excitation thresholds for motor and sensory fibers in the ulnar, median and tibial nerves using both electric and magnetic stimulation, and they found that for short duration electrical stimuli (0.1 msec) the threshold for motor fibers is lower than for sensory fibers.
Journal ArticleDOI

Linear and nonlinear information flow based on time-delayed mutual information method and its application to corticomuscular interaction.

TL;DR: This is the first study to show separate linear and nonlinear information flow in CM interaction, and is a viable model-free measure of temporally varying causal interactions that is capable of distinguishinglinear and non linear information flow.