Computational Modeling of Ultrasonic Subthalamic Nucleus Stimulation.


Journal

IEEE transactions on bio-medical engineering
ISSN: 1558-2531
Titre abrégé: IEEE Trans Biomed Eng
Pays: United States
ID NLM: 0012737

Informations de publication

Date de publication:
04 2019
Historique:
pubmed: 7 9 2018
medline: 8 2 2020
entrez: 7 9 2018
Statut: ppublish

Résumé

To explore the potential of ultrasonic modulation of plateau-potential generating subthalamic nucleus neurons (STN), by modeling their interaction with continuous and pulsed ultrasonic waves. A computational model for ultrasonic stimulation of the STN is created by combining the Otsuka-model with the bilayer sonophore model. The neuronal response to continuous and pulsed ultrasonic waves is computed in parallel for a range of frequencies, duty cycles, pulse repetition frequencies, and intensities. Ultrasonic intensity in continuous-wave stimulation determines the firing pattern of the STN. Three observed spiking modes in order of increasing intensity are low frequency spiking, high frequency spiking with significant spike-frequency and spike-amplitude adaptation, and a silenced mode. Continuous-wave stimulation has little capability to manipulate the saturated spiking rate in the high frequency spiking mode. In contrast, STN firing rates induced by pulsed ultrasound insonication will saturate to the pulse repetition frequency with short latencies, for sufficiently large intensity and repetition frequency. Computational results show that the activity of plateau-potential generating STN can be modulated by selection of the stimulus parameters. Low intensities result in repetitive firing, while higher intensities silence the STN. Pulsed ultrasonic stimulation results in a shorter saturation latency and is able to modulate spiking rates. Stimulation or suppresion of the STN is important in the treatment of Parkinson's disease, e.g., in deep brain stimulation. This explorative study on ultrasonic modulation of the STN, could be a step in the direction of minimally invasive alternatives to conventional deep brain stimulation.

Identifiants

pubmed: 30188811
doi: 10.1109/TBME.2018.2869042
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1155-1164

Auteurs

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Classifications MeSH