The University of Southampton
University of Southampton Institutional Repository

A dominant bursting electromyograph pattern in dystonic conditions predicts an early response to pallidal stimulation

Yianni, John, Wang, Shou Yan, Liu, Xuguang, Bain, Peter G., Nandi, Dipankar, Gregory, Ralph, Joint, Carole, Stein, John F. and Aziz, Tipu Z. (2006) A dominant bursting electromyograph pattern in dystonic conditions predicts an early response to pallidal stimulation Journal of Clinical Neuroscience, 13, (7), pp. 738-746. (doi:10.1016/j.jocn.2005.07.022).

Record type: Article


Although chronic pallidal deep brain stimulation (DBS) is effective in the treatment of medically intractable dystonia, there is no way of predicting the variations in clinical outcome, partly due to our limited understanding of the pathophysiological mechanisms underlying this condition. We recorded electromyographic (EMG) activity from the most severely affected muscle groups in seven dystonia patients before and after pallidal DBS. Patient EMG recordings could be classified into two groups: one consisting of patients who at rest demonstrated a dominant low frequency component of activity on power spectral analysis (ranging from 2 to 5 Hz), and one group in which this dominant pattern was absent. Early postoperative improvements (within 2–3 days) were observed in the former group, whereas the latter group benefited more gradually (over several months). Analysis of EMG activity may provide a sensitive means of identifying dystonic patients who are likely to be most responsive to functional neurosurgical intervention.

Full text not available from this repository.

More information

Published date: August 2006
Keywords: dystonia, EMG, pallidum, stimulation
Organisations: Human Sciences Group


Local EPrints ID: 49596
ISSN: 0967-5868
PURE UUID: 77353f06-b621-432f-b888-01685a8c2957

Catalogue record

Date deposited: 21 Nov 2007
Last modified: 17 Jul 2017 14:55

Export record



Author: John Yianni
Author: Shou Yan Wang
Author: Xuguang Liu
Author: Peter G. Bain
Author: Dipankar Nandi
Author: Ralph Gregory
Author: Carole Joint
Author: John F. Stein
Author: Tipu Z. Aziz

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.