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.

Neural recordings in humans using invasive devices can elucidate the circuits underlying brain disorders, but have so far been limited to short recordings from externalized brain leads in a hospital setting or from implanted sensing devices that provide only intermittent, brief streaming of time series data. Here we report the use of an implantable two-way neural interface for wireless, multichannel streaming of field potentials in five patients with Parkinson’s disease for up to 15 months after implantation. Bilateral 4-channel motor cortex and basal ganglia field potentials streamed at home for over 2,600 hours were paired with behavioral data from wearable monitors for the neural decoding of states of inadequate or excessive movement. We validated patient-specific neurophysiological biomarkers during normal daily activities and used those patterns for adaptive deep brain stimulation. This technological approach may be widely applicable to brain disorders treatable by invasive neuromodulation.

The objective of this study was to evaluate proposed electroencephalographic (EEG) biomarkers of Parkinson’s disease (PD) and test their correlation with motor impairment in a new, well-characterized cohort of PD patients and controls. Sixty-four-channel EEG was recorded from 14 patients with rigid-akinetic PD with minimal tremor and from 14 age-matched healthy controls at rest and during voluntary movement. Patients were tested off and on medication during a single session. Recordings were analyzed for phase-amplitude coupling over sensorimotor cortex and for pairwise coherence from all electrode pairs in the recording montage (distributed coherence). Phase-amplitude coupling and distributed coherence were found to be elevated Off compared with On levodopa, and their reduction was correlated with motor improvement. In the Off medication state, phase-amplitude coupling was greater in sensorimotor contacts contralateral to the most affected body part and reduced by voluntary movement. We conclude that phase-amplitude coupling and distributed coherence are cortical biomarkers of the parkinsonian state that are detectable noninvasively and may be useful as objective aids for management of dopaminergic therapy. Several analytic methods may be used for noninvasive measurement of abnormal brain synchronization in PD. Calculation of phase-amplitude coupling requires only a single electrode over motor cortex. NEW & NOTEWORTHY Several EEG biomarkers of the parkinsonian state have been proposed that are related to abnormal cortical synchronization. We report several new findings in this study: correlations of EEG markers of synchronization with specific motor signs of Parkinson’s disease (PD), and demonstration that one of the EEG markers, phase-amplitude coupling, is more elevated over the more clinically affected brain hemisphere. These findings underscore the potential utility of scalp EEG for objective, noninvasive monitoring of medication state in PD.