Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders

Abstract

Deep brain stimulation (DBS) represents one of the major clinical breakthroughs in the age of translational neuroscience. In 1987, Benabid and colleagues demonstrated that high-frequency stimulation can mimic the effects of ablative neurosurgery in Parkinson's disease (PD), while offering two key advantages to previous procedures: adjustability and reversibility. Deep brain stimulation is now an established therapeutic approach that robustly alleviates symptoms in patients with movement disorders, such as Parkinson's disease, essential tremor, and dystonia, who present with inadequate or adverse responses to medication. Currently, stimulation electrodes are implanted in specific target regions of the basal ganglia-thalamic circuit and stimulation pulses are delivered chronically. To achieve optimal therapeutic effect, stimulation frequency, amplitude, and pulse width must be adjusted on a patient-specific basis by a movement disorders specialist. The finding that pathological neural activity can be sampled directly from the target region using the DBS electrode has inspired a novel DBS paradigm: closed-loop adaptive DBS (aDBS). The goal of this strategy is to identify pathological and physiologically normal patterns of neuronal activity that can be used to adapt stimulation parameters to the concurrent therapeutic demand. This review will give detailed insight into potential biomarkers and discuss next-generation strategies, implementing advances in artificial intelligence, to further elevate the therapeutic potential of DBS by capitalizing on its modifiable nature. Development of intelligent aDBS, with an ability to deliver highly personalized treatment regimens and to create symptom-specific therapeutic strategies in real-time, could allow for significant further improvements in the quality of life for movement disorders patients with DBS that ultimately could outperform traditional drug treatment.

Reply to: Pallidal Low‐Frequency Activity in Dystonia and Subthalamic Beta Activity in Parkinson's Disease

“…They conclude that future generations of closed-loop stimulation devices will need to account for multiple frequency bands and their task dependency. We agree with this notion 4 and would like to complement further aspects that require attention when considering the application of closed-loop algorithms. First, recording location matters.…”

Deep brain stimulation for Tourette’s syndrome

“…The classical open-loop system, however, represents a static approach to therapy within an inherently dynamic system [74]. In contrast, responsive or adaptive DBS (aDBS) is designed to function as a 'closed-loop' stimulation device, which can be personalized according to the frequency and duration of a physiologic event or behavioral manifestation [59,[75][76][77][78]. The closed-loop system in which stimulation is dependent on functional neural feedback were initially designed to improve the treatment of epilepsy [79,80].…”

Closed-loop stimulation of the medial septum terminates epileptic seizures

“…Longitudinal, patient specific fine-tunings of detection and stimulus algorithms would be important to ensure long-term effectiveness and safeness of MS Estims. Intelligent DBS approaches utilizing deep learning technology may be effective for realtime classification of brain states to deliver proper stimulus patterns in an on-demand manner (61).…”