Systems approaches to optimizing deep brain stimulation therapies in Parkinson's disease

• Type of Material: Article
• Authors: Sabato Santaniello, University of Connecticut; John T. Gale, Emory University; Sridevi V. Sarma, Johns Hopkins University
• Language: English
• Date: 2018-09-01
• Publisher: Wiley: 12 months
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2018 Wiley Periodicals, Inc.
• Final Published Version (URL): http://dx.doi.org/10.1002/wsbm.1421
• Title of Journal or Parent Work: Wiley Interdisciplinary Reviews: Systems Biology and Medicine
• ISSN: 1939-5094
• Volume: 10
• Issue: 5
• Start Page: e1421
• End Page: e1421
• Grant/Funding Information: Work of authors in this field was supported by Burroughs Wellcome Fund CASI Award 1007274; NSF PECASE Award 1055560; and NIH Grant R01NS073118-02.
• Keywords: HIGH-FREQUENCY STIMULATION; neuroprosthetics; neuroengineering; PALLIDAL NEURONS; Medicine, Research & Experimental; EVOKED-POTENTIALS; deep brain stimulation; Science & Technology; Parkinson's disease; NEURONAL-ACTIVITY; NEURAL SPIKING ACTIVITY; MODEL; VERBAL FLUENCY; Research & Experimental Medicine; MOTOR; SUBTHALAMIC NUCLEUS STIMULATION; BASAL GANGLIA; Life Sciences & Biomedicine; neural systems and control
• Research Categories: Engineering, Biomedical; Biology, Neuroscience; Health Sciences, Medicine and Surgery

Abstract

Over the last 30 years, deep brain stimulation (DBS) has been used to treat chronic neurological diseases like dystonia, obsessive–compulsive disorders, essential tremor, Parkinson’s disease, and more recently, dementias, depression, cognitive disorders, and epilepsy. Despite its wide use, DBS presents numerous challenges for both clinicians and engineers. One challenge is the design of novel, more efficient DBS therapies, which are hampered by the lack of complete understanding about the cellular mechanisms of therapeutic DBS. Another challenge is the existence of redundancy in clinical outcomes, that is, different DBS programs can result in similar clinical benefits but very little information (e.g., predictive models, longitudinal data, metrics, etc.) is available to select one program over another. Finally, there is high variability in patients’ responses to DBS, which forces clinicians to carefully adjust the stimulation settings to each patient via lengthy programming sessions. Researchers in neural engineering and systems biology have been tackling these challenges over the past few years with the specific goal of developing novel DBS therapies, design methodologies, and computational tools that optimize the therapeutic effects of DBS in each patient. Furthermore, efforts are being made to automatically adapt the DBS treatment to the fluctuations of disease symptoms. A review of the quantitative approaches currently available for the treatment of Parkinson’s disease is presented here with an emphasis on the contributions that systems theoretical approaches have provided to understand the global dynamics of complex neuronal circuits in the brain under DBS. This article is categorized under: Translational, Genomic, and Systems Medicine > Therapeutic Methods Analytical and Computational Methods > Computational Methods Analytical and Computational Methods > Dynamical Methods Physiology > Mammalian Physiology in Health and Disease.