Data from: Energy exchanges at contact events guide sensorimotor integration across intermodal delaysAli Farshchian, Alessandra Sciutti, Assaf Pressman, Ilana Nisky & Ferdinando A Mussa-Ivaldi
The brain must consider the arm's inertia to predict the arm's movements elicited by commands impressed upon the muscles. Here, we present evidence suggesting that the integration of sensory information leading to the representation of the arm's inertia does not take place continuously in time but only at discrete transient events, in which kinetic energy is exchanged between the arm and the environment. We used a visuomotor delay to induce cross-modal variations in state feedback...
Data from: Evidence for a time-invariant phase variable in human ankle controlRobert D. Gregg, Elliott J. Rouse, Levi J. Hargrove & Jonathon W. Sensinger
Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-dependent feedback to accommodate perturbations. Two popular theories have been proposed for the underlying embodiment of phase in the human pattern generator: a time-dependent internal representation or a time-invariant feedback representation (i.e., reflex mechanisms). In either case the neuromuscular system must update or represent the phase of locomotor patterns based on the system state, which can include measurements of hundreds...
Data from: I meant to do that: determining the intentions of action in the face of disturbancesJustin R. Horowitz, James L. Patton, Justin Horowitz & James Patton
Our actions often do not match our intentions when there are external disturbances such as turbulence. We derived a novel modeling approach for determining this motor intent from targeted reaching motions that are disturbed by an unexpected force. First, we demonstrated how to mathematically invert both feedforward (predictive) and feedback controls to obtain an intended trajectory. We next examined the model’s sensitivity to a realistic range of parameter uncertainties, and found that the expected inaccuracy...
Data from: Adaptation to random and systematic errors: Comparison of amputee and non-amputee control interfaces with varying levels of process noiseReva E. Johnson, Konrad P. Kording, Levi J. Hargrove & Jonathon W. Sensinger
The objective of this study was to understand how people adapt to errors when using a myoelectric control interface. We compared adaptation across 1) non-amputee subjects using joint angle, joint torque, and myoelectric control interfaces, and 2) amputee subjects using myoelectric control interfaces with residual and intact limbs (five total control interface conditions). We measured trial-by-trial adaptation to self-generated errors and random perturbations during a virtual, single degree-of-freedom task with two levels of feedback uncertainty,...
Rehabilitation Institute of Chicago4
University of New Brunswick2
University of Illinois at Chicago1
Massachusetts Institute of Technology1
Italian Institute of Technology1
The University of Texas at Dallas1
Ben-Gurion University of the Negev1