Objective: Closed-loop DBS systems require a neural biomarker to responsively turn on stimulation, which in turn requires neurophysiological quantification synchronized to behavior or symptoms. Our goal is to uncover neural biomarkers of disease with high precision to drive closed-loop systems. Thus, methodologies to synchronize brain and behavior are essential.

Background: Closed-loop DBS systems can improved clinical therapy and improve the patients’ quality of life. Still, next generation platforms and analytic approaches to precisely quantify behaviors in humans and link them with simultaneously recorded brain activity therefore is critical for the design of closed-loop DBS systems.

Method: Following few investigational device iterations, today, there are commercially available neurostimulators capable of chronic sensing. But because these devices are fully implanted, synchronizing them with any external device that could quantify behavior or symptoms is very challenging. We have thus carefully implemented methods that can synchronize the implanted device’s signals to wearable inertia and EMG sensors, vicon motion systems, GAITRite walking mats, and audio and video recordings. We call this open-source synchronization platform FROST for Florida Research Open-Source Synchronization Tool. This method gives us finer temporal resolution and therefore better synchronization accuracy across many external devices.

Results: We have been able to synchronize brain signals and behavior in patients populations with Tourette Syndrome, Parkinson’s Disease, and essential tremor and have extracted biomarkers for involuntary tics, freezing of gait and movement intention that leads tremor. We were then able to develop and test closed-loop DBS in all three indications. Synchronization accuracy was vital for these endeavors. Our method gives us finer temporal resolution and therefore better synchronization accuracy across many external devices.

Conclusion: Accurate synchronization of brain signals and behavioral markers of disease symptoms is paramount to identifying neural biomarkers of disease and signals that can turn on stimulation for suppression of these symptoms in a closed-loop manner. We show that this task requires smarter systems than synchronizing time clocks of various devices. Our synchronization tool and methods are publicly available, and its feasibility and accuracy has been shown in three patient populations.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/brain-behavior-quantification-and-synchronization-to-drive-closed-loop-deep-brain-stimulation/