Publications by authors named "Ro'ee Gilron"

Introduction: Invasive recording of neural activity provides valuable insights into Parkinson's disease (PD). Bidirectional sensing devices enable wireless neural data collection during everyday activities, but neural signals during complex outdoor sports remain unexplored.

Methods: We recorded neural data from a 57-year-old PD patient using bilateral implanted pulse generators connected to subthalamic nucleus (STN) and motor cortex leads.

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The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St.

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Parkinson's disease (PD) is a common neurological disorder, with bradykinesia being one of its cardinal features. Objective quantification of bradykinesia using computer vision has the potential to standardise decision-making, for patient treatment and clinical trials, while facilitating remote assessment. We utilised a dataset of part-3 MDS-UPDRS motor assessments, collected at four independent clinical and one research sites on two continents, to build computer-vision-based models capable of inferring the correct severity rating robustly and consistently across all identifiable subgroups of patients.

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The ability of humans to coordinate stereotyped, alternating movements between the two legs during bipedal walking is a complex motor behavior that requires precisely timed activities across multiple nodes of the supraspinal network. Understanding of the neural network dynamics that underlie natural walking in humans is limited. We investigated cortical and subthalamic neural activities during overground walking and evaluated spectral biomarkers to decode the gait cycle in three patients with Parkinson's disease without gait disturbances.

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Biological rhythms pervade physiology and pathophysiology across multiple timescales. Because of the limited sensing and algorithm capabilities of neuromodulation device technology to-date, insight into the influence of these rhythms on the efficacy of bioelectronic medicine has been infeasible. As the development of new devices begins to mitigate previous technology limitations, we propose that future devices should integrate chronobiological considerations in their control structures to maximize the benefits of neuromodulation therapy.

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Article Synopsis
  • DBS Think Tank IX took place from August 25-27, 2021, in Orlando, FL, featuring both in-person U.S. attendees and international participants joining via video conferencing.
  • Founded in 2012, the Think Tank serves as a collaborative space for clinicians, engineers, and researchers to discuss advancements in deep brain stimulation (DBS) technologies and address related logistical and ethical challenges.
  • This year's meeting highlighted the growing application of DBS across various brain disorders, estimating over 230,000 devices implanted globally, with special focus areas including neuromodulation strategies, innovative technologies, neuroethics, and specific applications for pain, epilepsy, and traumatic brain injuries.
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. To provide a design analysis and guidance framework for the implementation of concurrent stimulation and sensing during adaptive deep brain stimulation (aDBS) with particular emphasis on artifact mitigations..

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Deep brain stimulation (DBS) is a plausible therapy for various neuropsychiatric disorders, though continuous tonic stimulation without regard to underlying physiology (open-loop) has had variable success. Recently available DBS devices can sense neural signals which, in turn, can be used to control stimulation in a closed-loop mode. Closed-loop DBS strategies may mitigate many drawbacks of open-loop stimulation and provide more personalized therapy.

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Motor fluctuations in Parkinson's disease are characterized by unpredictability in the timing and duration of dopaminergic therapeutic benefits on symptoms, including bradykinesia and rigidity. These fluctuations significantly impair the quality of life of many Parkinson's patients. However, current clinical evaluation tools are not designed for the continuous, naturalistic (real-world) symptom monitoring needed to optimize clinical therapy to treat fluctuations.

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Adaptive deep brain stimulation (aDBS) is a promising new technology with increasing use in experimental trials to treat a diverse array of indications such as movement disorders (Parkinson's disease, essential tremor), psychiatric disorders (depression, OCD), chronic pain and epilepsy. In many aDBS trials, a neural biomarker of interest is compared with a predefined threshold and stimulation amplitude is adjusted accordingly. Across indications and implant locations, potential biomarkers are greatly influenced by sleep.

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Article Synopsis
  • The text refers to a correction made to the original article identified by the DOI 10.3389/fnhum.2021.644593.
  • The correction aims to address errors or inaccuracies present in the initial publication.
  • It emphasizes the importance of maintaining accuracy in academic research and publication.
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Advances in neuromodulation technologies hold the promise of treating a patient's unique brain network pathology using personalized stimulation patterns. In service of these goals, neuromodulation clinical trials using sensing-enabled devices are routinely generating large multi-modal datasets. However, with the expansion of data acquisition also comes an increasing difficulty to store, manage, and analyze the associated datasets, which integrate complex neural and wearable time-series data with dynamic assessments of patients' symptomatic state.

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Advances in therapeutic neuromodulation devices have enabled concurrent stimulation and electrophysiology in the central nervous system. However, stimulation artifacts often obscure the sensed underlying neural activity. Here, we develop a method, termed Period-based Artifact Reconstruction and Removal Method (PARRM), to remove stimulation artifacts from neural recordings by leveraging the exact period of stimulation to construct and subtract a high-fidelity template of the artifact.

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Gait is a core motor function and is impaired in numerous neurological diseases, including Parkinson's disease (PD). Treatment changes in PD are frequently driven by gait assessments in the clinic, commonly rated as part of the Movement Disorder Society (MDS) Unified PD Rating Scale (UPDRS) assessment (item 3.10).

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Closed-loop neurostimulation is a promising therapy being tested and clinically implemented in a growing number of neurological and psychiatric indications. This therapy is enabled by chronically implanted, bidirectional devices including the Medtronic Summit RC+S system. In order to successfully optimize therapy for patients implanted with these devices, analyses must be conducted offline on the recorded neural data, in order to inform optimal sense and stimulation parameters.

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We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field.

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Neural recordings using invasive devices in humans 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 individuals with Parkinson's disease (PD) for up to 15 months after implantation. Bilateral four-channel motor cortex and basal ganglia field potentials streamed at home for over 2,600 h were paired with behavioral data from wearable monitors for the neural decoding of states of inadequate or excessive movement.

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Sleep disturbances are among the most common nonmotor complications of Parkinson's disease (PD), can present in prodromal stages, and progress with advancing disease. In addition to being a symptom of neurodegeneration, sleep disturbances may also contribute to disease progression. Currently, limited options exist to modulate sleep disturbances in PD.

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Evoked neural activity in sensory regions and perception of sensory stimuli are modulated when the stimuli are the consequence of voluntary movement, as opposed to an external source. It has been suggested that such modulations are due to motor commands that are sent to relevant sensory regions during voluntary movement. However, given the anatomical-functional laterality bias of the motor system, it is plausible that the pattern of such behavioral and neural modulations will also exhibit a similar bias, depending on the effector triggering the stimulus (e.

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The Seventh Annual Deep Brain Stimulation (DBS) Think Tank held on September 8th of 2019 addressed the most current: (1) use and utility of complex neurophysiological signals for development of adaptive neurostimulation to improve clinical outcomes; (2) Advancements in recent neuromodulation techniques to treat neuropsychiatric disorders; (3) New developments in optogenetics and DBS; (4) The use of augmented Virtual reality (VR) and neuromodulation; (5) commercially available technologies; and (6) ethical issues arising in and from research and use of DBS. These advances serve as both "markers of progress" and challenges and opportunities for ongoing address, engagement, and deliberation as we move to improve the functional capabilities and translational value of DBS. It is in this light that these proceedings are presented to inform the field and initiate ongoing discourse.

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The annual deep brain stimulation (DBS) Think Tank aims to create an opportunity for a multidisciplinary discussion in the field of neuromodulation to examine developments, opportunities and challenges in the field. The proceedings of the Sixth Annual Think Tank recapitulate progress in applications of neurotechnology, neurophysiology, and emerging techniques for the treatment of a range of psychiatric and neurological conditions including Parkinson's disease, essential tremor, Tourette syndrome, epilepsy, cognitive disorders, and addiction. Each section of this overview provides insight about the understanding of neuromodulation for specific disease and discusses current challenges and future directions.

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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.

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This perspective provides an overview of how risk can be effectively considered in physiological control loops that strive for semi-to-fully automated operation. The perspective first introduces the motivation, user needs and framework for the design of a physiological closed-loop controller. Then, we discuss specific risk areas and use examples from historical medical devices to illustrate the key concepts.

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Objective: Contemporary deep brain stimulation (DBS) 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.

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