Deep reinforcement learning (RL) methods have driven impressive advances in artificial intelligence in recent years, exceeding human performance in domains ranging from Atari to Go to no-limit poker. This progress has drawn the attention of cognitive scientists interested in understanding human learning. However, the concern has been raised that deep RL may be too sample-inefficient […]
Published on April 17, 2019
NeuroMeasure: A Software Package for Quantification of Cortical Motor Maps Using Frameless Stereotaxic Transcranial Magnetic Stimulation Usman M. Arshad1, Gary W. Thickbroom2, Josh Silverstein2, K. Zoe Tsagaris2, Amy Kuceyeski3, Kathleen Friel4,5, Taiza E. G. Santos6 and Dylan J. Edwards7,8* 1Biomedical Engineering Department, The City College of New York, New York, NY, United States 2Burke Neurological […]
Published on April 16, 2019
On the Relationship Between Muscle Synergies and Redundant Degrees of Freedom in Musculoskeletal Systems Reza Sharif Razavian*, Borna Ghannadi and John McPhee Motion Research Group, Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada It has been suggested that the human nervous system controls motions in the task (or operational) space. However, little […]
Published on April 16, 2019