Objective Contemporary deep brain stimulation for Parkinson’s disease is delivered continuously, and adjustments based on patient’s changing symptoms must be made manually by a trained clinician. Patients may be subjected to energy intensive settings at times when they are not needed, possibly resulting in stimulation-induced adverse effects, such as dyskinesia. One solution is “adaptive” DBS, in which stimulation is modified in real time based on neural signals that co-vary with the severity of motor signs or of stimulation-induced adverse effects. Here we show the feasibility of adaptive DBS using a fully implanted neural prosthesis. Approach We demonstrate adaptive deep brain stimulation in two patients with Parkinson’s disease using a fully implanted neural prosthesis that is enabled to utilize brain sensing to control stimulation amplitude (Activa PC+S). We used a cortical narrowband gamma (60-90 Hz) oscillation related to dyskinesia to decrease stimulation voltage when gamma oscillatory activity is high (indicating dyskinesia) and increase stimulation voltage when it is low. Main Results We demonstrate the feasibility of “adaptive deep brain stimulation” in two patients with Parkinson’s disease. In short term in-clinic testing, energy savings were substantial (38-45%), and therapeutic efficacy was maintained. Significance This is the first demonstration of adaptive DBS in Parkinson’s disease using a fully implanted device and neural sensing. Our approach is distinct from other strategies utilizing basal ganglia signals for feedback control.

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The subthalamic nucleus (STN) is the most common target for the treatment of Parkinson's disease (PD) with deep brain stimulation (DBS). DBS of the globus pallidus internus (GPi) is also effective in the treatment of PD. The output fibers of the GPi that form the lenticular fasciculus pass in close proximity to STN DBS electrodes. In turn, both STN projection neurons and GPi fibers of passage represent possible therapeutic targets of DBS in the STN region. We built a comprehensive computational model of STN DBS in parkinsonian macaques to study the effects of stimulation in a controlled environment. The model consisted of three fundamental components: 1) a three-dimensional (3D) anatomical model of the macaque basal ganglia, 2) a finite element model of the DBS electrode and electric field transmitted to the tissue medium, and 3) multicompartment biophysical models of STN projection neurons, GPi fibers of passage, and internal capsule fibers of passage. Populations of neurons were positioned within the 3D anatomical model. Neurons were stimulated with electrode positions and stimulation parameters defined as clinically effective in two parkinsonian monkeys. The model predicted axonal activation of STN neurons and GPi fibers during STN DBS. Model predictions regarding the degree of GPi fiber activation matched well with experimental recordings in both monkeys. Only axonal activation of the STN neurons showed a statistically significant increase in both monkeys when comparing clinically effective and ineffective stimulation. Nonetheless, both neural targets may play important roles in the therapeutic mechanisms of STN DBS.

Hyperkinetic states are common in human movement disorders, but their neural basis remains uncertain. One such condition is dyskinesia, a serious adverse effect of medical and surgical treatment for Parkinson's disease (PD). To study this, we used a novel, totally implanted, bidirectional neural interface to obtain multisite long-term recordings. We focus our analysis on two patients with PD who experienced frequent dyskinesia and studied them both at rest and during voluntary movement. We show that dyskinesia is associated with a narrowband gamma oscillation in motor cortex between 60 and 90 Hz, a similar, though weaker, oscillation in subthalamic nucleus, and strong phase coherence between the two. Dyskinesia-related oscillations are minimally affected by voluntary movement. When dyskinesia persists during therapeutic deep brain stimulation (DBS), the peak frequency of this signal shifts to half the stimulation frequency. These findings suggest a circuit-level mechanism for the generation of dyskinesia as well as a promising control signal for closed-loop DBS.

Deep brain stimulation (DBS) represents a powerful clinical technology, but a systematic characterization of the electrical interactions between the electrode and the brain are lacking. The goal of this study was to examine the in vivo changes in DBS electrode impedance that occur after implantation and during clinically-relevant stimulation. Clinical DBS devices typically apply high-frequency voltage-controlled stimulation, and as a result the injected current is directly regulated by the impedance of the electrode-tissue interface. We monitored the impedance of scaled-down clinical DBS electrodes implanted in the thalamus and subthalamic nucleus of a rhesus macaque using electrode impedance spectroscopy (EIS) measurements ranging from 0.5 Hz to 10 kHz. To further characterize our measurements, equivalent circuit models of the electrode-tissue interface were used to quantify the role of various interface components in producing the observed electrode impedance. Following implantation, DBS electrode impedance increased and a semicircular arc was observed in the high frequency range of the EIS measurements, commonly referred to as the tissue component of the impedance. Clinically-relevant stimulation produced a rapid decrease in electrode impedance with extensive changes in the tissue component. These post-operative and stimulation-induced changes in impedance could play an important role in the observed functional effects of voltage-controlled DBS and should be considered during clinical stimulation parameter selection and chronic animal research studies.

Deep brain stimulation (DBS) is an effective treatment for movement disorders, but the mechanisms are unclear. DBS generates inhibition of neurons surrounding the electrode while simultaneously activating the output axons of local neurons. This dual effect does not explain two hallmarks of DBS effectiveness: symptom relief is dependent on using a sufficiently high-stimulation frequency, and clinical effects are analogous to those produced by lesion. The effect of DBS at different frequencies on the output of intrinsically active neurons was studied using computational models. DBS produced frequency-dependent modulation of the variability of neuronal output, and above a critical frequency stimulation resulted in regular output with zero variance. The resulting loss of information offers an explanation for the two hallmarks of DBS effectiveness.

Summary:Chronic electrical stimulation of the brain, known as deep brain stimulation (DBS), has become a preferred surgical treatment for medication-refractory movement disorders. Despite its remarkable clinical success, the therapeutic mechanisms of DBS are still not completely understood, limiting opportunities to improve treatment efficacy and simplify selection of stimulation parameters. This review addresses three questions essential to understanding the mechanisms of DBS. 1) How does DBS affect neuronal tissue in the vicinity of the active electrode or electrodes? 2) How do these changes translate into therapeutic benefit on motor symptoms? 3) How do these effects depend on the particular site of stimulation? Early hypotheses proposed that stimulation inhibited neuronal activity at the site of stimulation, mimicking the outcome of ablative surgeries. Recent studies have challenged that view, suggesting that although somatic activity near the DBS electrode may exhibit substantial inhibition or complex modulation patterns, the output from the stimulated nucleus follows the DBS pulse train by direct axonal excitation. The intrinsic activity is thus replaced by high-frequency activity that is time-locked to the stimulus and more regular in pattern. These changes in firing pattern are thought to prevent transmission of pathologic bursting and oscillatory activity, resulting in the reduction of disease symptoms through compensatory processing of sensorimotor information. Although promising, this theory does not entirely explain why DBS improves motor symptoms at different latencies. Understanding these processes on a physiological level will be critically important if we are to reach the full potential of this powerful tool.

Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease and shows great promise for numerous other disorders. While the fundamental purpose of DBS is to modulate neural activity with electric fields, little is known about the actual voltage distribution generated in the brain by DBS electrodes and as a result it is difficult to accurately predict which brain areas are directly affected by the stimulation. The goal of this study was to characterize the spatial and temporal characteristics of the voltage distribution generated by DBS electrodes. We experimentally recorded voltages around active DBS electrodes in either a saline bath or implanted in the brain of a non-human primate. Recordings were made during voltage-controlled and currentcontrolled stimulation. The experimental findings were compared to volume conductor electric field models of DBS parameterized to match the different experiments. Three factors directly affected the experimental and theoretical voltage measurements: 1) DBS electrode impedance, primarily dictated by a voltage drop at the electrode-electrolyte interface and the conductivity of the tissue medium, 2) capacitive modulation of the stimulus waveform, and 3) inhomogeneity and anisotropy of the tissue medium. While the voltage distribution does not directly predict the neural response to DBS, the results of this study do provide foundational building blocks for understanding the electrical parameters of DBS and characterizing its effects on the nervous system.