title: Enhanced crosslimb transfer of force-field learning for dynamics that are identical in extrinsic and joint-based coordinates for both limbs.
abstract: Humans are able to adapt their motor commands to make accurate movements in novel sensorimotor environments, such as when wielding tools that alter limb dynamics. However, it is unclear to what extent sensorimotor representations, obtained through experience with one limb, are available to the opposite, untrained limb and in which form they are available. Here, we compared crosslimb transfer of force-field compensation after participants adapted to a velocity-dependent curl field, oriented either in the sagittal or the transverse plane. Due to the mirror symmetry of the limbs, the force field had identical effects for both limbs in joint and extrinsic coordinates in the sagittal plane but conflicting joint-based effects in the transverse plane. The degree of force-field compensation exhibited by the opposite arm in probe trials immediately after initial learning was significantly greater after sagittal (26 ± 5%) than transverse plane adaptation (9 ± 4%; P < 0.001), irrespective of whether participants learned initially with the left or the right arm or via abrupt or gradual exposure to the force field. Thus transfer was impaired when the orientation of imposed dynamics conflicted in intrinsic coordinates for the two limbs. The data reveal that neural representations of novel dynamics are only partially available to the opposite limb, since transfer is incomplete even when force-field perturbation is spatially compatible for the two limbs, according to both intrinsic and extrinsic coordinates.
authors.affiliation: Centre for Sensorimotor Performance, School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, Australia; timothy.carroll@uq.edu.au.
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Carroll
authors.affiliation: Centre for Sensorimotor Performance, School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, Australia; Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Centre National de la Recherche Scientifique Unité Mixte de Recherche 5287, Université de Bordeaux, France;
authors.forename: Aymar
authors.initials: A
authors.lastname: de Rugy
authors.affiliation: School of Computing and Mathematics, Plymouth University, Plymouth, United Kingdom; and.
authors.forename: Ian S
authors.initials: IS
authors.lastname: Howard
authors.affiliation: Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
authors.forename: James N
authors.initials: JN
authors.lastname: Ingram
authors.affiliation: Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Wolpert
mesh_terms: D000222:Adaptation, Physiological; D000328:Adult; D001132:Arm / Q000502:physiology*; D001696:Biomechanical Phenomena; D056228:Feedback, Sensory / Q000502:physiology; D005260:Female; D007839:Functional Laterality; D006801:Humans; D007596:Joints / Q000502:physiology; D007858:Learning / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D011597:Psychomotor Performance; D055815:Young Adult
keywords: coordinate frame; interlimb transfer; motor learning; sensorimotor adaptation