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IEEE Transactions on Haptics|October 15, 2016
Encoding and Decoding of Multi-Channel ICMS in Macaque Somatosensory CortexMaria C Dadarlat, Philip N SabesNature Neuroscience|November 25, 2014
A learning-based approach to artificial sensory feedback leads to optimal integrationMaria C Dadarlat, Joseph E O'Doherty, Philip N SabesProgress in Brain Research|July 12, 2011
Sensory integration for reaching: models of optimality in the context of behavior and the underlying neural circuitsPhilip N SabesJournal of Neurophysiology|January 5, 2007
Calibration of visually guided reaching is driven by error-corrective learning and internal dynamicsSen Cheng, Philip N SabesThe Journal of Neuroscience : the Official Journal of the Society for Neuroscience|July 8, 2011
How each movement changes the next: an experimental and theoretical study of fast adaptive priors in reachingTimothy Verstynen, Philip N SabesNeural Computation|February 24, 2006
Modeling sensorimotor learning with linear dynamical systemsSen Cheng, Philip N SabesNature Neuroscience|March 29, 2005
Flexible strategies for sensory integration during motor planningSamuel J Sober, Philip N SabesThe Journal of Neuroscience : the Official Journal of the Society for Neuroscience|August 9, 2003
Multisensory integration during motor planningSamuel J Sober, Philip N SabesNature Neuroscience|July 15, 2009
Sensory transformations and the use of multiple reference frames for reach planningLeah M M McGuire, Philip N SabesProceedings of the National Academy of Sciences of the United States of America|February 27, 2026
Integration of learned artificial sensation with vision during freely moving navigationSamuel J Senneka, Maria C DadarlatPageof 4