A New Implantable Closed-Loop Clinical Neural Interface: First Application in Parkinson’s Disease

Deep brain stimulation (DBS) is used for the treatment of movement disorders, including Parkinson’s disease, dystonia, and essential tremor, and has shown clinical benefits in other brain disorders. A natural path for the improvement of this technique is to continuously observe the stimulation effects on patient symptoms and neurophysiological markers. This requires the evolution of conventional deep brain stimulators to bidirectional interfaces, able to record, process, store, and wirelessly communicate neural signals in a robust and reliable fashion. Here, we present the architecture, design, and first use of an implantable stimulation and sensing interface (AlphaDBSR System) characterized by artifact-free recording and distributed data management protocols. Its application in three patients with Parkinson’s disease (clinical trial n. NCT04681534) is shown as a proof of functioning of a clinically viable implanted brain-computer interface (BCI) for adaptive DBS. Reliable artifact free-recordings, and chronic long-term data and neural signal management are in place.

Download Full-text

Focal Subthalamic Atrophy After Long‐Term Deep Brain Stimulation in Parkinson's Disease

Movement Disorders ◽

10.1002/mds.28653 ◽

2021 ◽

Author(s):

Ellen Gelpi ◽

Christine Haberler ◽

Alexander Micko ◽

Andrea Polt ◽

Andreas Amon ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Deep Brain Stimulation ◽

Brain Stimulation ◽

Deep Brain

Download Full-text

Predicting optimal deep brain stimulation parameters for Parkinson’s disease using functional MRI and machine learning

Nature Communications ◽

10.1038/s41467-021-23311-9 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Alexandre Boutet ◽

Radhika Madhavan ◽

Gavin J. B. Elias ◽

Suresh E. Joel ◽

Robert Gramer ◽

...

Keyword(s):

Machine Learning ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Deep Brain Stimulation ◽

Brain Stimulation ◽

A Priori ◽

Brain Response ◽

Brain Responses ◽

Clinical Benefits ◽

Deep Brain

AbstractCommonly used for Parkinson’s disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.

Download Full-text