title: Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model.
abstract: Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement ("jump") consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation.
authors.affiliation: German Primate Center, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany;
authors.forename: Stephanie
authors.initials: S
authors.lastname: Westendorff
authors.affiliation: German Primate Center, Göttingen, Germany;
authors.forename: Shenbing
authors.initials: S
authors.lastname: Kuang
authors.affiliation: German Primate Center, Göttingen, Germany;
authors.forename: Bahareh
authors.initials: B
authors.lastname: Taghizadeh
authors.affiliation: Department of Biomedical Engineering and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer Sheva, Israel; and Department of Neuroscience, Erasmus Medical College, Rotterdam, The Netherlands.
authors.forename: Opher
authors.initials: O
authors.lastname: Donchin
authors.affiliation: German Primate Center, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; agail@gwdg.de.
authors.forename: Alexander
authors.initials: A
authors.lastname: Gail
mesh_terms: D000328:Adult; D003198:Computer Simulation; D056228:Feedback, Sensory / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D009048:Motor Skills / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D066191:Sensorimotor Cortex / Q000502:physiology*; D055815:Young Adult
keywords: asymmetry; generalization pattern; neural network model; reach adaptation; target jump