Clinical applications of neurochemical and electrophysiological measurements for closed-loop neurostimulation

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.

Toward adaptive deep brain stimulation for dystonia

The presence of abnormal neural oscillations within the cortico-basal ganglia-thalamo-cortical (CBGTC) network has emerged as one of the current principal theories to explain the pathophysiology of movement disorders. In theory, these oscillations can be used as biomarkers and thereby serve as a feedback signal to control the delivery of deep brain stimulation (DBS). This new form of DBS, dependent on different characteristics of pathological oscillations, is called adaptive DBS (aDBS), and it has already been applied in patients with Parkinson's disease. In this review, the authors summarize the scientific research to date on pathological oscillations in dystonia and address potential biomarkers that might be used as a feedback signal for controlling aDBS in patients with dystonia.

Approaches to closed-loop deep brain stimulation for movement disorders

OBJECTIVE Deep brain stimulation (DBS) is a safe and effective therapy for movement disorders, such as Parkinson's disease (PD), essential tremor (ET), and dystonia. There is considerable interest in developing "closed-loop" DBS devices capable of modulating stimulation in response to sensor feedback. In this paper, the authors review related literature and present selected approaches to signal sources and approaches to feedback being considered for deployment in closed-loop systems. METHODS A literature search using the keywords "closed-loop DBS" and "adaptive DBS" was performed in the PubMed database. The search was conducted for all articles published up until March 2018. An in-depth review was not performed for publications not written in the English language, nonhuman studies, or topics other than Parkinson's disease or essential tremor, specifically epilepsy and psychiatric conditions. RESULTS The search returned 256 articles. A total of 71 articles were primary studies in humans, of which 50 focused on treatment of movement disorders. These articles were reviewed with the aim of providing an overview of the features of closed-loop systems, with particular attention paid to signal sources and biomarkers, general approaches to feedback control, and clinical data when available. CONCLUSIONS Closed-loop DBS seeks to employ biomarkers, derived from sensors such as electromyography, electrocorticography, and local field potentials, to provide real-time, patient-responsive therapy for movement disorders. Most studies appear to focus on the treatment of Parkinson's disease. Several approaches hold promise, but additional studies are required to determine which approaches are feasible, efficacious, and efficient.

Gamma oscillations in the somatosensory thalamus of a patient with a phantom limb: case report

The amputation of an extremity is commonly followed by phantom sensations that are perceived to originate from the missing limb. The mechanism underlying the generation of these sensations is still not clear although the development of abnormal oscillatory bursting in thalamic neurons may be involved. The theory of thalamocortical dysrhythmia implicates gamma oscillations in phantom pathophysiology although this rhythm has not been previously observed in the phantom limb thalamus. In this study, the authors report the novel observation of widespread 38-Hz gamma oscillatory activity in spike and local field potential recordings obtained from the ventral caudal somatosensory nucleus of the thalamus (Vc) of a phantom limb patient undergoing deep brain stimulation (DBS) surgery. Interestingly, microstimulation near tonically firing cells in the Vc resulted in high-frequency, gamma oscillatory discharges coincident with phantom sensations reported by the patient. Recordings from the somatosensory thalamus of comparator groups (essential tremor and pain) did not reveal the presence of gamma oscillatory activity.

Chronic multisite brain recordings from a totally implantable bidirectional neural interface: experience in 5 patients with Parkinson's disease

OBJECTIVE Dysfunction of distributed neural networks underlies many brain disorders. The development of neuromodulation therapies depends on a better understanding of these networks. Invasive human brain recordings have a favorable temporal and spatial resolution for the analysis of network phenomena but have generally been limited to acute intraoperative recording or short-term recording through temporarily externalized leads. Here, the authors describe their initial experience with an investigational, first-generation, totally implantable, bidirectional neural interface that allows both continuous therapeutic stimulation and recording of field potentials at multiple sites in a neural network. METHODS Under a physician-sponsored US Food and Drug Administration investigational device exemption, 5 patients with Parkinson's disease were implanted with the Activa PC+S system (Medtronic Inc.). The device was attached to a quadripolar lead placed in the subdural space over motor cortex, for electrocorticography potential recordings, and to a quadripolar lead in the subthalamic nucleus (STN), for both therapeutic stimulation and recording of local field potentials. Recordings from the brain of each patient were performed at multiple time points over a 1-year period. RESULTS There were no serious surgical complications or interruptions in deep brain stimulation therapy. Signals in both the cortex and the STN were relatively stable over time, despite a gradual increase in electrode impedance. Canonical movement-related changes in specific frequency bands in the motor cortex were identified in most but not all recordings. CONCLUSIONS The acquisition of chronic multisite field potentials in humans is feasible. The device performance characteristics described here may inform the design of the next generation of totally implantable neural interfaces. This research tool provides a platform for translating discoveries in brain network dynamics to improved neurostimulation paradigms. Clinical trial registration no.: NCT01934296 (clinicaltrials.gov).

Prediction and detection of seizures from simultaneous thalamic and scalp electroencephalography recordings

OBJECTIVE The authors explored the feasibility of seizure detection and prediction using signals recorded from the anterior thalamic nucleus, a major target for deep brain stimulation (DBS) in the treatment of epilepsy. METHODS Using data from 5 patients (13 seizures in total), the authors performed a feasibility study and analyzed the performance of a seizure prediction and detection algorithm applied to simultaneously acquired scalp and thalamic electroencephalography (EEG). The thalamic signal was obtained from DBS electrodes. The applied algorithm used the similarity index as a nonlinear measure for seizure identification, with patient-specific channel and threshold selection. Receiver operating characteristic (ROC) curves were calculated using data from all patients and channels to compare the performance between DBS and EEG recordings. RESULTS Thalamic DBS recordings were associated with a mean prediction rate of 84%, detection rate of 97%, and false-alarm rate of 0.79/hr. In comparison, scalp EEG recordings were associated with a mean prediction rate of 71%, detection rate of 100%, and false-alarm rate of 1.01/hr. From the ROC curves, when considering all channels, DBS outperformed EEG for both detection and prediction of seizures. CONCLUSIONS This is the first study to compare automated seizure detection and prediction from simultaneous thalamic and scalp EEG recordings. The authors have demonstrated that signals recorded from DBS leads are more robust than EEG recordings and can be used to predict and detect seizures. These results indicate feasibility for future designs of closed-loop anterior nucleus DBS systems for the treatment of epilepsy.

Intraoperative electrocorticography for physiological research in movement disorders: principles and experience in 200 cases

OBJECTIVE Contemporary theories of the pathophysiology of movement disorders emphasize abnormal oscillatory activity in basal ganglia-thalamocortical loops, but these have been studied in humans mainly using depth recordings. Recording from the surface of the cortex using electrocorticography (ECoG) provides a much higher amplitude signal than depth recordings, is less susceptible to deep brain stimulation (DBS) artifacts, and yields a surrogate measure of population spiking via "broadband gamma" (50-200 Hz) activity. Therefore, a technical approach to movement disorders surgery was developed that employs intraoperative ECoG as a research tool. METHODS One hundred eighty-eight patients undergoing DBS for the treatment of movement disorders were studied under an institutional review board-approved protocol. Through the standard bur hole exposure that is clinically indicated for DBS lead insertion, a strip electrode (6 or 28 contacts) was inserted to cover the primary motor or prefrontal cortical areas. Localization was confirmed by the reversal of the somatosensory evoked potential and intraoperative CT or 2D fluoroscopy. The ECoG potentials were recorded at rest and during a variety of tasks and analyzed offline in the frequency domain, focusing on activity between 3 and 200 Hz. Strips were removed prior to closure. Postoperative MRI was inspected for edema, signal change, or hematoma that could be related to the placement of the ECoG strip. RESULTS One hundred ninety-eight (99%) strips were successfully placed. Two ECoG placements were aborted due to resistance during the attempted passage of the electrode. Perioperative surgical complications occurred in 8 patients, including 5 hardware infections, 1 delayed chronic subdural hematoma requiring evacuation, 1 intraparenchymal hematoma, and 1 venous infarction distant from the site of the recording. None of these appeared to be directly related to the use of ECoG. CONCLUSIONS Intraoperative ECoG has long been used in neurosurgery for functional mapping and localization of seizure foci. As applied during DBS surgery, it has become an important research tool for understanding the brain networks in movement disorders and the mechanisms of therapeutic stimulation. In experienced hands, the technique appears to add minimal risk to surgery.