A5077360715- EEG and Brain-Computer Interfaces
- Motor Control and Adaptation
- Neural dynamics and brain function
- Action Observation and Synchronization
- Muscle activation and electromyography studies
- Advanced Memory and Neural Computing
- Neuroscience and Neural Engineering
- Cutaneous Melanoma Detection and Management
- Tactile and Sensory Interactions
- Behavioral and Psychological Studies
- Child and Animal Learning Development
- Functional Brain Connectivity Studies
- Sport Psychology and Performance
- AI in cancer detection
- Transcranial Magnetic Stimulation Studies
- Optical Coherence Tomography Applications
- Interactive and Immersive Displays
- Animal Vocal Communication and Behavior
- Dermatologic Treatments and Research
- Robotic Locomotion and Control
- Advanced Sensor and Energy Harvesting Materials
- Neuroscience and Music Perception
- Neuroscience, Education and Cognitive Function
- Balance, Gait, and Falls Prevention
- Bat Biology and Ecology Studies
University of Pittsburgh
2019-2025
Johns Hopkins University
2023-2024
Northern Arizona University
2023-2024
Center for the Neural Basis of Cognition
2023-2024
Northeastern University
2023-2024
University of Cambridge
2023-2024
Northwestern University
2017-2022
Neuroscience Institute
2019
McCormick (United States)
2017
University of Illinois Urbana-Champaign
2011
We report classes of electronic systems that achieve thicknesses, effective elastic moduli, bending stiffnesses, and areal mass densities matched to the epidermis. Unlike traditional wafer-based technologies, laminating such devices onto skin leads conformal contact adequate adhesion based on van der Waals interactions alone, in a manner is mechanically invisible user. describe incorporating electrophysiological, temperature, strain sensors, as well transistors, light-emitting diodes,...
Abstract Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern which are versatile and easy to use, have potential significantly improve performance. This tutorial describes how effectively apply these algorithms for typical problems. We provide descriptions, best practices, code applying common methods, including networks gradient boosting. also detailed comparisons performance various methods at task spiking...
The spiking activity of populations cortical neurons is well described by the dynamics a small number population-wide covariance patterns, whose activation we refer to as ‘latent dynamics’. These latent are largely driven same correlated synaptic currents across circuit that determine generation local field potentials (LFPs). Yet, relationship between and LFPs remains unexplored. Here, characterised this for three different regions primate sensorimotor cortex during reaching. correlation was...
Neuroscience has long focused on finding encoding models that effectively ask "what predicts neural spiking?" and generalized linear (GLMs) are a typical approach. It is often unknown how much of explainable activity captured, or missed, when fitting model. Here we compared the predictive performance simple to three leading machine learning methods: feedforward networks, gradient boosted trees (using XGBoost), stacked ensembles combine predictions several methods. We predicted spike counts...
Proprioception, the sense of body position, movement, and associated forces, remains poorly understood, despite its critical role in movement. Most studies area 2, a proprioceptive somatosensory cortex, have simply compared neurons' activities to movement hand through space. Using motion tracking, we sought elaborate this relationship by characterizing how 2 activity relates whole arm movements. We found that whole-arm model, unlike classic models, successfully predicted features neural...
Mapping the relationship between neural activity and motor behavior is a central aim of sensorimotor neuroscience neurotechnology. While most progress to this end has relied on restricting complexity, advent foundation models instead proposes integrating breadth data as an alternate avenue for broadly advancing downstream modeling. We quantify premise decoding from intracortical microelectrode data, pretraining autoregressive Transformer 2000 hours population spiking paired with diverse...
Advances in neural recording present increasing opportunities to study activity unprecedented detail. Latent variable models (LVMs) are promising tools for analyzing this rich across diverse systems and behaviors, as LVMs do not depend on known relationships between the external experimental variables. However, progress with neuronal population is currently impeded by a lack of standardization, resulting methods being developed compared an ad hoc manner. To coordinate these modeling efforts,...
Abstract Animals rapidly adapt their movements to external perturbations, a process paralleled by changes in neural activity the motor cortex. Experimental studies suggest that these originate from altered inputs (H input ) rather than local connectivity ), as covariance is largely preserved during adaptation. Since measuring synaptic vivo remains very challenging, we used modular recurrent network qualitatively test this interpretation. As expected, H resulted small and covariance....
Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern which are versatile and easy to use, have potential significantly improve performance. This tutorial describes how effectively apply these algorithms for typical problems. We provide descriptions, best practices, code applying common methods, including networks gradient boosting. also detailed comparisons performance various methods at task spiking activity motor...
Abstract Large-scale recordings of neural activity are providing new opportunities to study network-level dynamics. However, the sheer volume data and its dynamical complexity critical barriers uncovering interpreting these Deep learning methods a promising approach due their ability uncover meaningful relationships from large, complex, noisy datasets. When applied high-D spiking motor cortex (M1) during stereotyped behaviors, they offer improvements in dynamics relation subjects’ behaviors...
While the response properties of neurons in somatosensory nerves and anterior parietal cortex have been extensively studied, little is known about encoding tactile proprioceptive information cuneate nucleus (CN) or external (ECN), first recipients upper limb afferent signals. The major challenge characterizing neural coding CN/ECN has to record from these tiny, difficult-to-access brain stem structures. Most previous investigations CN carried out decerebrate anesthetized animals, thereby...
Abstract Neuroscience has long focused on finding encoding models that effectively ask “what predicts neural spiking?” and generalized linear (GLMs) are a typical approach. It is often unknown how much of explainable activity captured, or missed, when fitting GLM. Here we compared the predictive performance GLMs to three leading machine learning methods: feedforward networks, gradient boosted trees (using XGBoost), stacked ensembles combine predictions several methods. We predicted spike...
Semitranslucency, defined as a smooth, jelly-like area with varied, near-skin-tone color, can indicate diagnosis of basal cell carcinoma (BCC) high specificity. This study sought to analyze potential areas semitranslucency histogram-derived texture and color measures discriminate BCC from non-semitranslucent in non-BCC skin lesions.For 210 dermoscopy images, the 42 BCCs comparable smoothness 168 non-BCCs were selected manually. Six six applied semitranslucent images.Receiver operating...
Somatosensation is composed of two distinct modalities: touch, arising from sensors in the skin, and proprioception, resulting primarily muscles, combined with these same cutaneous sensors. In contrast to wealth information about we know surprisingly little nature signals giving rise proprioception at cortical level. Here investigate use Artificial Neural Networks (ANNs) model relationship between firing rates single neurons somatosensory cortex (S1) several types kinematic variables related...
Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective subject employing? This challenge particularly acute in animal behavior because we cannot ask or instruct use a particular strategy. study presents three-pronged approach an animal’s from behavior. First, both monkeys performed virtual balancing task for strategies could be utilized....
Abstract The most prominent role of motor cortex is generating patterns neural activity that lead to movement, but it also active when we simply imagine movements in the absence actual output. Despite decades behavioral and imaging studies, unknown how specific temporal dynamics within during covert imagery relate those execution. Here recorded intracortical from two people with residual wrist function following incomplete spinal cord injury as they performed both imagined isometric...
Proprioception, the sense of limb position and motion, arises from individual muscle receptors. An important question is how where in neuroaxis our high level "extrinsic" movement originates. In 1990s, a series papers detailed properties neurons dorsal spinocerebellar tract (DSCT) cat. Despite their direct projections sensory receptors, it appeared that half these had consistent, high-level tuning to paw rather than joint angles (or lengths). These results suggested many DSCT compute lower...