A5006331850- EEG and Brain-Computer Interfaces
- Neuroscience and Neural Engineering
- Neural dynamics and brain function
- Muscle activation and electromyography studies
- Functional Brain Connectivity Studies
- Human Pose and Action Recognition
- Gaussian Processes and Bayesian Inference
- Neural Networks and Applications
- Gaze Tracking and Assistive Technology
- Neuroscience and Neuropharmacology Research
- Neuroscience, Education and Cognitive Function
- Fault Detection and Control Systems
- Advanced Sensor and Energy Harvesting Materials
- Conducting polymers and applications
- Advanced Memory and Neural Computing
Columbia University
2019-2021
Columbia University Irving Medical Center
2019-2021
University of Michigan
2015-2018
Hope College
2010
Loss of even part the upper limb is a devastating injury. In order to fully restore natural function when lacking sufficient residual musculature, it necessary record directly from peripheral nerves. However, current approaches must make trade-offs between signal quality and longevity which limit their clinical potential. To address this issue, we have developed regenerative nerve interface (RPNI) tested its use in non-human primates.The RPNI consists small, autologous partial muscle graft...
Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding finger movements in rhesus macaques.
Objective. We characterized electrode stability over twelve weeks of impedance and neural recording data from four chronically-implanted Utah arrays in two rhesus macaques, investigated the effects glial scarring interface interactions at site on signal quality using a computational model. Approach. A finite-element model array microelectrode tissue was coupled with multi-compartmental neuron to quantify encapsulation thickness, resistivity, resistivity waveform amplitude. The then...
Brain-Machine Interfaces (BMIs) have shown great potential for generating prosthetic control signals. Translating BMIs into the clinic requires fully implantable, wireless systems; however, current solutions high power requirements which limit their usability. Lowering this consumption typically limits system to a single neural modality, or signal type, and thus relatively small clinical market. Here, we address both of these issues by investigating use in narrow frequency band as decoding...
Brain-machine interfaces (BMIs) for reaching have enjoyed continued performance improvements, yet there remains significant need BMIs that control other movement classes. Recent scientific findings suggest the intrinsic covariance structure of neural activity depends strongly on class, potentially necessitating different decode algorithms across To address this possibility, we developed a self-motion BMI based cortical as monkeys cycled hand-held pedal to progress along virtual track. Unlike...
Challenges in improving the performance of dexterous upper-limb brain-machine interfaces (BMIs) have prompted renewed interest quantifying amount and type sensory information naturally encoded primary motor cortex (M1). Previous single unit studies monkeys showed M1 is responsive to tactile stimulation, as well passive active movement limbs. However, recent work this area has focused primarily on proprioception. Here we examined instead how somatosensation hand fingers represented M1.We...
Abstract Brain-machine interfaces (BMIs) for reaching have enjoyed continued performance improvements, yet there remains significant need BMIs that control other movement classes. Recent scientific findings suggest the intrinsic covariance structure of neural activity depends strongly on class, potentially necessitating different decode algorithms across To address this, we developed a self-motion BMI based cortical as monkeys performed non-reaching arm movements: cycling hand-held pedal to...
As AI systems become increasingly powerful, the need for safe has more pressing. Humans are an attractive model safety: as only known agents capable of general intelligence, they perform robustly even under conditions that deviate significantly from prior experiences, explore world safely, understand pragmatics, and can cooperate to meet their intrinsic goals. Intelligence, when coupled with cooperation safety mechanisms, drive sustained progress well-being. These properties a function...
Gaussian processes are the leading class of distributions on random functions, but they suffer from well known issues including difficulty scaling and inflexibility with respect to certain shape constraints (such as nonnegativity). Here we propose Deep Random Splines, a flexible functions obtained by transforming noise through deep neural network whose output parameters spline. Unlike processes, Splines allow us readily enforce while inheriting richness tractability generative models. We...
Abstract Nitrous oxide (N 2 O) is a hypnotic gas with antidepressant and psychedelic properties at subanesthetic concentrations. Despite long-standing clinical use, there insufficient understanding of its effect on neural dynamics cortical processing, which important for mechanistic therapeutic effects. We administered (70%), inhaled N O studied the dynamic changes spiking rate, spectral content, somatosensory information representation in primary motor cortex (M1) two male rhesus macaques...