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A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation. / Yousif, Nada; Mace, Michael; Pavese, Nicola; Borisyuk, Roman; Nandi, Dipankar; Bain, Peter.

In: PLoS Computational Biology, Vol. 13, No. 1, 09.01.2017, p. e1005326.

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Yousif, Nada ; Mace, Michael ; Pavese, Nicola ; Borisyuk, Roman ; Nandi, Dipankar ; Bain, Peter. / A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation. In: PLoS Computational Biology. 2017 ; Vol. 13, No. 1. pp. e1005326.

Bibtex

@article{f001cb475e5c4147b0213359938683c7,
title = "A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation",
abstract = "Essential tremor (ET), a movement disorder characterised by an uncontrollable shaking of the affected body part, is often professed to be the most common movement disorder, affecting up to one percent of adults over 40 years of age. The precise cause of ET is unknown, however pathological oscillations of a network of a number of brain regions are implicated in leading to the disorder. Deep brain stimulation (DBS) is a clinical therapy used to alleviate the symptoms of a number of movement disorders. DBS involves the surgical implantation of electrodes into specific nuclei in the brain. For ET the targeted region is the ventralis intermedius (Vim) nucleus of the thalamus. Though DBS is effective for treating ET, the mechanism through which the therapeutic effect is obtained is not understood. To elucidate the mechanism underlying the pathological network activity and the effect of DBS on such activity, we take a computational modelling approach combined with electrophysiological data. The pathological brain activity was recorded intra-operatively via implanted DBS electrodes, whilst simultaneously recording muscle activity of the affected limbs. We modelled the network hypothesised to underlie ET using the Wilson-Cowan approach. The modelled network exhibited oscillatory behaviour within the tremor frequency range, as did our electrophysiological data. By applying a DBS-like input we suppressed these oscillations. This study shows that the dynamics of the ET network support oscillations at the tremor frequency and the application of a DBS-like input disrupts this activity, which could be one mechanism underlying the therapeutic benefit.",
author = "Nada Yousif and Michael Mace and Nicola Pavese and Roman Borisyuk and Dipankar Nandi and Peter Bain",
note = "Copyright: {\textcopyright} 2017 Yousif et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The version of record, Yousif N, Mace M, Pavese N, Borisyuk R, Nandi D, Bain P (2017) 'A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation', PLoS Comput Biol 13(1): e1005326. doi:10.1371/journal.pcbi.1005326 ",
year = "2017",
month = jan,
day = "9",
doi = "10.1371/journal.pcbi.1005326",
language = "English",
volume = "13",
pages = "e1005326",
journal = "PLoS Computational Biology",
issn = "1553-734X",
publisher = "Public Library of Science",
number = "1",

}

RIS

TY - JOUR

T1 - A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation

AU - Yousif, Nada

AU - Mace, Michael

AU - Pavese, Nicola

AU - Borisyuk, Roman

AU - Nandi, Dipankar

AU - Bain, Peter

N1 - Copyright: © 2017 Yousif et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The version of record, Yousif N, Mace M, Pavese N, Borisyuk R, Nandi D, Bain P (2017) 'A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation', PLoS Comput Biol 13(1): e1005326. doi:10.1371/journal.pcbi.1005326

PY - 2017/1/9

Y1 - 2017/1/9

N2 - Essential tremor (ET), a movement disorder characterised by an uncontrollable shaking of the affected body part, is often professed to be the most common movement disorder, affecting up to one percent of adults over 40 years of age. The precise cause of ET is unknown, however pathological oscillations of a network of a number of brain regions are implicated in leading to the disorder. Deep brain stimulation (DBS) is a clinical therapy used to alleviate the symptoms of a number of movement disorders. DBS involves the surgical implantation of electrodes into specific nuclei in the brain. For ET the targeted region is the ventralis intermedius (Vim) nucleus of the thalamus. Though DBS is effective for treating ET, the mechanism through which the therapeutic effect is obtained is not understood. To elucidate the mechanism underlying the pathological network activity and the effect of DBS on such activity, we take a computational modelling approach combined with electrophysiological data. The pathological brain activity was recorded intra-operatively via implanted DBS electrodes, whilst simultaneously recording muscle activity of the affected limbs. We modelled the network hypothesised to underlie ET using the Wilson-Cowan approach. The modelled network exhibited oscillatory behaviour within the tremor frequency range, as did our electrophysiological data. By applying a DBS-like input we suppressed these oscillations. This study shows that the dynamics of the ET network support oscillations at the tremor frequency and the application of a DBS-like input disrupts this activity, which could be one mechanism underlying the therapeutic benefit.

AB - Essential tremor (ET), a movement disorder characterised by an uncontrollable shaking of the affected body part, is often professed to be the most common movement disorder, affecting up to one percent of adults over 40 years of age. The precise cause of ET is unknown, however pathological oscillations of a network of a number of brain regions are implicated in leading to the disorder. Deep brain stimulation (DBS) is a clinical therapy used to alleviate the symptoms of a number of movement disorders. DBS involves the surgical implantation of electrodes into specific nuclei in the brain. For ET the targeted region is the ventralis intermedius (Vim) nucleus of the thalamus. Though DBS is effective for treating ET, the mechanism through which the therapeutic effect is obtained is not understood. To elucidate the mechanism underlying the pathological network activity and the effect of DBS on such activity, we take a computational modelling approach combined with electrophysiological data. The pathological brain activity was recorded intra-operatively via implanted DBS electrodes, whilst simultaneously recording muscle activity of the affected limbs. We modelled the network hypothesised to underlie ET using the Wilson-Cowan approach. The modelled network exhibited oscillatory behaviour within the tremor frequency range, as did our electrophysiological data. By applying a DBS-like input we suppressed these oscillations. This study shows that the dynamics of the ET network support oscillations at the tremor frequency and the application of a DBS-like input disrupts this activity, which could be one mechanism underlying the therapeutic benefit.

U2 - 10.1371/journal.pcbi.1005326

DO - 10.1371/journal.pcbi.1005326

M3 - Article

C2 - 28068428

VL - 13

SP - e1005326

JO - PLoS Computational Biology

JF - PLoS Computational Biology

SN - 1553-734X

IS - 1

ER -