Advances in neurochemical measurements: A review of biomarkers and devices for the development of closed-loop deep brain stimulation systems

Abstract

Neurochemical recording techniques have expanded our understanding of the pathophysiology of neurological disorders, as well as the mechanisms of action of treatment modalities like deep brain stimulation (DBS). DBS is used to treat diseases such as Parkinson’s disease, Tourette syndrome, and obsessive-compulsive disorder, among others. Although DBS is effective at alleviating symptoms related to these diseases and improving the quality of life of these patients, the mechanism of action of DBS is currently not fully understood. A leading hypothesis is that DBS modulates the electrical field potential by modifying neuronal firing frequencies to non-pathological rates thus providing therapeutic relief. To address this gap in knowledge, recent advances in electrochemical sensing techniques have given insight into the importance of neurotransmitters, such as dopamine, serotonin, glutamate, and adenosine, in disease pathophysiology. These studies have also highlighted their potential use in tandem with electrophysiology to serve as biomarkers in disease diagnosis and progression monitoring, as well as characterize response to treatment. Here, we provide an overview of disease-relevant neurotransmitters and their roles and implications as biomarkers, as well as innovations to the biosensors used to record these biomarkers. Furthermore, we discuss currently available neurochemical and electrophysiological recording devices, and discuss their viability to be implemented into the development of a closed-loop DBS system.

Surface‐enhanced Raman spectroscopy combined with multivariate analysis for the detection and differentiation of dopamine and DOPAC in cerebrospinal fluid

“…We collected SERS spectra of DA, HVA, DOPAC, 3-OMD, and 3-MT at concentrations similar to those used for the electrochemical measurements for comparison (Figure S4) and to establish the SERS limits of detection (LODs; Figures S5 and S6). For the detailed comparison of DA and DOPAC at physiologically relevant concentrations for the brain, 20 sample groups were prepared in aCSF, with five samples prepared at each concentration/ mixture: four pure DA samples (1, 3, 7, and 10 μM), five pure DOPAC samples (3,7,10,12, and 18 μM), 10 mixtures, and blanks (AuNPs in aCSF). Two mixtures were included that fall outside of the physiologically relevant range: 7 μM DA + 3 μM DOPAC and 10 μM DA + 10 μM DOPAC.…”

“…[3][4][5] Imaging techniques used to monitor DA involve indirect detection through secondary molecules to trace DA through fluorescence, magnetic resonance imaging, and positron emission tomography. [6][7][8][9][10] Drawbacks of these techniques include complexity, overlap with other molecular signals, and labeling of traces with either fluorescent or radioactive probes. 7,11 High-performance liquid chromatography (HPLC) and ultra-performance liquid chromatography (UPLC) combined with mass spectrometry (MS) are both commonly utilized in DA detection, [12][13][14] to assess complex biological matter without sacrificing the Paula A. Pimiento and Natalie E. Dunn are joint first authors.…”

“…Imaging techniques used to monitor DA involve indirect detection through secondary molecules to trace DA through fluorescence, magnetic resonance imaging, and positron emission tomography 6–10 . Drawbacks of these techniques include complexity, overlap with other molecular signals, and labeling of traces with either fluorescent or radioactive probes 7,11 .…”

Molecular Mechanisms and Therapeutic Strategies for Levodopa-Induced Dyskinesia in Parkinson’s Disease: A Perspective Through Preclinical and Clinical Evidence

“…They also reported 38–45% less energy consumption than classical DBS to maintain the same therapeutic efficacy ( Dastin-van Rijn et al, 2021 ). Recently, more responsive adaptive DBS systems have been developed using accelerometer-based technology, which detects movements by utilizing peripheral kinematic sensors to detect dyskinesia ( Rojas Cabrera et al, 2020 ).…”

The development of ultra–high field MRI guidance technology for neuronavigation

“…[6][7][8] As the indications for image-guided surgery expand into neuro-oncology, neuropsychiatric diseases, and closed-loop neuromodulation systems, improved imaging guidance technologies will have a farreaching impact. [9][10][11][12] The recent introduction of ultra-high field strength 7T MRI scanners offers significant potential to improve surgical planning because of the superior image quality afforded by the greater SNR, CNR, and spatial resolution. 13 These qualities allow 1) improved visualization of targets, 2) avoidance of eloquent structures and vasculature, 3) resolution of unseen neural connections, and 4) mitigation of off-target effects of passing fiber stimulation.…”