Parag G. Patil

Functional electrical stimulation and brain-machine interfaces for simultaneous control of wrist and finger flexion

Matthew J. Mender, Ayobami L. Ward, Luis Hernan Cubillos, Madison M. Kelberman et autres

Abstract Background Restoring dexterous hand movements in individuals with cervical spinal cord injury requires continuous control of multiple biomechanically linked degrees-of-freedom (DOF). Brain-machine interface (BMI) controlled functional electrical stimulation (FES) is a promising method to restore hand movements. We explored the suitability …

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Exploring Synergies in Brain-Machine Interfaces: Compression vs. Performance

Luis Hernan Cubillos, Madison M. Kelberman, Matthew J. Mender, Aren Hite et autres

Abstract Individuals with severe neurological injuries often rely on assistive technologies, but current methods have limitations in accurately decoding multi-degree-of-freedom (DoF) movements. Intracortical brain-machine interfaces (iBMIs) use neural signals to provide a more natural control method, but currently struggle with higher-DoF movements—something …

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430 Development and Multimodal Validation of the Smallest-Diameter Electrode Intracortical Array to Date in a Large Animal Model for Brain-Computer Interfaces

Jordan Lam, Joseph G. Letner, Miranda G. Copenhaver, Ayobami L. Ward et autres

INTRODUCTION: The 80-µm-diameter Utah electrode array (UEA) has been used for speech (Card et al., NEJM, 2024) and motor brain-computer interfaces (BCI, Willsey et al., Nat Med, 2025), but clinical viability is limited by scarring, neuronal loss, and average lifespan of under …

Long-term Intracortical Neural activity and Kinematics (LINK): An intracortical neural dataset for chronic brain-machine interfaces, neuroscience, and machine learning.

Hisham Temmar, Yixuan Wang, Nina Gill, Nicholas B Mellon et autres

Intracortical brain-machine interfaces (iBMIs) have enabled movement and speech in people living with paralysis by using neural data to decode behaviors in real-time. However, intracortical neural recordings exhibit significant instabilities over time, which poses problems for iBMIs, neuroscience, and machine learning. For …

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ID# 1906959 Percutaneous Implantation and Stimulation Versatility of Thin-Film Paddles – Cadaveric and in vivo Sheep Study

Florenta Aura Kullmann, Maria Porto Cruz, Mary McNeil, Alfonso Chavez et autres

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ID# 1906131 Model-based Analysis of the Physiological Effects of Spinal Cord Stimulation to Treat Chronic Pain

Wutt Hmone T. Kyi, Adrian Porras Laura, Evan R. Rogers, Jessica N. Loechli et autres

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Longitudinal Changes in Sensory Processing and Clinical Outcomes During Spinal Cord and Dorsal Root Ganglion Stimulation to Treat Chronic Pain: A Pilot Study

Evan R. Rogers, Vishwanath Sankarasubramanian, Wutt Hmone T. Kyi, Ehsan Mirzakhalili et autres

Purpose: The analgesic mechanisms and neurophysiological effects of spinal cord stimulation (SCS) and dorsal root ganglion stimulation (DRGS) are poorly understood. In this pilot repeated-measures study, we used quantitative sensory testing (QST) and self-reported questionnaires to investigate the effects of these therapies …

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Enhancing Precision in Chronic Pain Management: A Model-Based Investigation of the Physiological Effects of Spinal Cord Stimulation in a Randomized Controlled Trial

Wutt Hmone T. Kyi, Adrian Porras Laura, Evan R. Rogers, Jessica N. Loechli et autres

Synopsis 800 characters Three million adults in the US suffer from depression that is resistant to treatment with medications.Transcranial Magnetic stimulation (TMS) has emerged as a safe and efficacious treatment option for these patients.While racial and ethnic disparities in the use of …

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Investigating the benefits of artificial neural networks over linear approaches to BMI decoding

Hisham Temmar, Matthew S. Willsey, Joseph T. Costello, Matthew J. Mender et autres

Abstract Objective. Brain–machine interfaces (BMI) aim to restore function to persons living with spinal cord injuries by ‘decoding’ neural signals into behavior. Recently, nonlinear BMI decoders have outperformed previous state-of-the-art linear decoders, but few studies have investigated what specific improvements these nonlinear …

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Ventral STN stimulation is associated with improved axial motor outcomes in Parkinson’s disease

Madison K. Butler, Asra Askari, Brandon J. Zhu, Kara J. Wyant et autres

Subthalamic nucleus (STN) deep brain stimulation (DBS) is well-established for improving appendicular motor signs but its effect on axial motor signs is less clear. Additionally, the location of active electrode contact within the STN has been shown to differentially affect motor outcomes. …

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Enhancement of gait improvement in Parkinson disease with anterior subthalamic nucleus deep brain stimulation

Kelvin L. Chou, Parag G. Patil, Karlo A. Malaga

OBJECTIVE: Subthalamic nucleus (STN) deep brain stimulation (DBS) alleviates the motor symptoms of Parkinson disease (PD). However, a generalized targeting approach may lead to suboptimal outcomes for patients with diverse symptoms. Volume of tissue activation (VTA) modeling can be used to compute …

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Trigeminal Neuralgia: Disease Characterization and Prediction of Response to Surgical Intervention

Jordan Lam, Tejas Sankar, Raymond F. Sekula, Patrick B. Senatus et autres

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