Clinical applications of neurochemical and electrophysiological measurements for closed-loop neurostimulation.
Authors: Price JB, Rusheen AE, Barath AS, Rojas Cabrera JM, Shin H, Chang SY, Kimble CJ, Bennet KE, Blaha CD, Lee KH, Oh Y
Journal: Neurosurgical focus
ACC = anterior cingulate cortex
ALIC = anterior limb of the internal capsule
CM-Pf = centromedian-parafascicular complex
DBS = deep brain stimulation
ET = essential tremor
FSCV = fast-scan cyclic voltammetry
GABA = gamma-aminobutyric acid
GPi = globus pallidus interna
LFP = local field potential
NAc = nucleus accumbens
OCD = obsessive-compulsive disorder
PAG = periaqueductal gray
PD = Parkinson’s disease
PVG = periventricular gray matter
SANTE = Stimulation of the Anterior Nucleus of the Thalamus for Epilepsy
Abstract
The development of closed-loop deep brain stimulation (DBS) systems represents a significant opportunity for innovation in the clinical application of neurostimulation therapies. Despite the highly dynamic nature of neurological diseases, open-loop DBS applications are incapable of modifying parameters in real time to react to fluctuations in disease states. Thus, current practice for the designation of stimulation parameters, such as duration, amplitude, and pulse frequency, is an algorithmic process. Ideal stimulation parameters are highly individualized and must reflect both the specific disease presentation and the unique pathophysiology presented by the individual. Stimulation parameters currently require a lengthy trial-and-error process to achieve the maximal therapeutic effect and can only be modified during clinical visits. The major impediment to the development of automated, adaptive closed-loop systems involves the selection of highly specific disease-related biomarkers to provide feedback for the stimulation platform. This review explores the disease relevance of neurochemical and electrophysiological biomarkers for the development of closed-loop neurostimulation technologies. Electrophysiological biomarkers, such as local field potentials, have been used to monitor disease states. Real-time measurement of neurochemical substances may be similarly useful for disease characterization. Thus, the introduction of measurable neurochemical analytes has significantly expanded biomarker options for feedback-sensitive neuromodulation systems. The potential use of biomarker monitoring to advance neurostimulation approaches for treatment of Parkinson's disease, essential tremor, epilepsy, Tourette syndrome, obsessive-compulsive disorder, chronic pain, and depression is examined. Further, challenges and advances in the development of closed-loop neurostimulation technology are reviewed, as well as opportunities for next-generation closed-loop platforms.