Journal article
Adaptive Stimulations in a Biophysical Network Model of Parkinson's Disease
International journal of molecular sciences, v 24(6), p5555
14 Mar 2023
PMID: 36982630
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Deep brain stimulation (DBS)-through a surgically implanted electrode to the subthalamic nucleus (STN)-has become a widely used therapeutic option for the treatment of Parkinson's disease and other neurological disorders. The standard conventional high-frequency stimulation (HF) that is currently used has several drawbacks. To overcome the limitations of HF, researchers have been developing closed-loop and demand-controlled, adaptive stimulation protocols wherein the amount of current that is delivered is turned on and off in real-time in accordance with a biophysical signal. Computational modeling of DBS in neural network models is an increasingly important tool in the development of new protocols that aid researchers in animal and clinical studies. In this computational study, we seek to implement a novel technique of DBS where we stimulate the STN in an adaptive fashion using the interspike time of the neurons to control stimulation. Our results show that our protocol eliminates bursts in the synchronized bursting neuronal activity of the STN, which is hypothesized to cause the failure of thalamocortical neurons (TC) to respond properly to excitatory cortical inputs. Further, we are able to significantly decrease the TC relay errors, representing potential therapeutics for Parkinson's disease.
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Details
- Title
- Adaptive Stimulations in a Biophysical Network Model of Parkinson's Disease
- Creators
- Thomas Stojsavljevic - Beloit CollegeYixin Guo - Drexel UniversityDominick Macaluso - University of Pennsylvania Health System
- Publication Details
- International journal of molecular sciences, v 24(6), p5555
- Publisher
- Mdpi
- Number of pages
- 25
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Mathematics
- Web of Science ID
- WOS:000954779200001
- Scopus ID
- 2-s2.0-85151112427
- Other Identifier
- 991020532113604721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Biochemistry & Molecular Biology
- Chemistry, Multidisciplinary