Byron M. Yu focuses on Neuroscience, Premotor cortex, Stimulus, Electrophysiology and Nerve net. His Neuroscience study incorporates themes from Control algorithm and Dimensionality reduction. His Stimulus study frequently draws connections to adjacent fields such as Posterior parietal cortex.
His work in Electrophysiology tackles topics such as Motor cortex which are related to areas like Biological neural network. His work deals with themes such as Neurophysiology, Sensory system, Primary motor cortex, Visualization and Rendering, which intersect with Nerve net. His Neural variability research includes themes of Cerebral cortex, Wakefulness, Visual perception and CATS.
His primary areas of investigation include Neuroscience, Artificial intelligence, Brain–computer interface, Pattern recognition and Neural activity. In his study, he carries out multidisciplinary Neuroscience and Premotor cortex research. Byron M. Yu combines subjects such as Machine learning, Neurophysiology, Decoding methods and Computer vision with his study of Artificial intelligence.
His research integrates issues of Kalman filter, Cursor and Motor control in his study of Brain–computer interface. In his work, Poisson distribution is strongly intertwined with Estimator, which is a subfield of Pattern recognition. His study in Stimulus is interdisciplinary in nature, drawing from both Cerebral cortex, Visual perception, Wakefulness and Posterior parietal cortex.
Neuroscience, Neural activity, Sensory system, Artificial intelligence and Stimulus are his primary areas of study. Byron M. Yu regularly links together related areas like Dimensionality reduction in his Neuroscience studies. He interconnects Cognitive science, Brain–computer interface and Set in the investigation of issues within Neural activity.
His Brain–computer interface research integrates issues from Cursor, Computer vision, User intent and Primary motor cortex. His Sensory system study combines topics in areas such as Robotic arm, Human–computer interaction and Neural decoding. Byron M. Yu works mostly in the field of Artificial intelligence, limiting it down to concerns involving Pattern recognition and, occasionally, Statistic and Redundancy.
His main research concerns Neuroscience, Dimensionality reduction, Brain–computer interface, Neural activity and Motor cortex. His studies in Neuroscience integrate themes in fields like Network model and Pairwise comparison. Byron M. Yu combines topics linked to Curse of dimensionality with his work on Dimensionality reduction.
His Primary motor cortex research extends to Brain–computer interface, which is thematically connected. Byron M. Yu focuses mostly in the field of Primary motor cortex, narrowing it down to topics relating to Pattern recognition and, in certain cases, Motor control. His research in Motor control intersects with topics in Artificial neural network and Artificial intelligence.
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Stimulus onset quenches neural variability: a widespread cortical phenomenon
Mark M. Churchland;Byron M. Yu;Byron M. Yu;John P. Cunningham;Leo P. Sugrue;Leo P. Sugrue.
Nature Neuroscience (2010)
A high-performance brain–computer interface
Gopal Santhanam;Stephen I. Ryu;Byron M. Yu;Afsheen Afshar.
Dimensionality reduction for large-scale neural recordings.
John P Cunningham;Byron M Yu.
Nature Neuroscience (2014)
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity
Byron M Yu;John P Cunningham;Gopal Santhanam;Stephen I. Ryu.
neural information processing systems (2008)
Neural constraints on learning
Patrick T. Sadtler;Kristin M. Quick;Matthew D. Golub;Steven M. Chase.
A high-performance neural prosthesis enabled by control algorithm design
Vikash Gilja;Paul Nuyujukian;Cindy A Chestek;John P Cunningham;John P Cunningham.
Nature Neuroscience (2012)
Neural Variability in Premotor Cortex Provides a Signature of Motor Preparation
Mark M. Churchland;Byron M. Yu;Stephen I. Ryu;Gopal Santhanam.
The Journal of Neuroscience (2006)
Empirical models of spiking in neural populations
Jakob H Macke;Lars Buesing;John P Cunningham;Byron M Yu.
neural information processing systems (2011)
Single-Trial Neural Correlates of Arm Movement Preparation
Afsheen Afshar;Gopal Santhanam;Byron M. Yu;Byron M. Yu;Stephen I. Ryu;Stephen I. Ryu.
Techniques for extracting single-trial activity patterns from large-scale neural recordings
Mark M Churchland;Byron M Yu;Byron M Yu;Maneesh Sahani;Krishna V Shenoy.
Current Opinion in Neurobiology (2007)
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