title: Optimal visuotactile integration for velocity discrimination of self-hand movements.
abstract: Illusory hand movements can be elicited by a textured disk or a visual pattern rotating under one's hand, while proprioceptive inputs convey immobility information (Blanchard C, Roll R, Roll JP, Kavounoudias A. PLoS One 8: e62475, 2013). Here, we investigated whether visuotactile integration can optimize velocity discrimination of illusory hand movements in line with Bayesian predictions. We induced illusory movements in 15 volunteers by visual and/or tactile stimulation delivered at six angular velocities. Participants had to compare hand illusion velocities with a 5°/s hand reference movement in an alternative forced choice paradigm. Results showed that the discrimination threshold decreased in the visuotactile condition compared with unimodal (visual or tactile) conditions, reflecting better bimodal discrimination. The perceptual strength (gain) of the illusions also increased: the stimulation required to give rise to a 5°/s illusory movement was slower in the visuotactile condition compared with each of the two unimodal conditions. The maximum likelihood estimation model satisfactorily predicted the improved discrimination threshold but not the increase in gain. When we added a zero-centered prior, reflecting immobility information, the Bayesian model did actually predict the gain increase but systematically overestimated it. Interestingly, the predicted gains better fit the visuotactile performances when a proprioceptive noise was generated by covibrating antagonist wrist muscles. These findings show that kinesthetic information of visual and tactile origins is optimally integrated to improve velocity discrimination of self-hand movements. However, a Bayesian model alone could not fully describe the illusory phenomenon pointing to the crucial importance of the omnipresent muscle proprioceptive cues with respect to other sensory cues for kinesthesia.
authors.affiliation: LNIA UMR 7260, Aix Marseille Université-Centre National de la Recherche Scientifique (CNRS), Marseille, France; LPNC UMR 5105, Université Savoie Mont Blanc-CNRS, Chambéry, France;
authors.forename: M
authors.initials: M
authors.lastname: Chancel
authors.affiliation: School of Psychology, University of Nottingham, Nottingham, United Kingdom; and.
authors.forename: C
authors.initials: C
authors.lastname: Blanchard
authors.affiliation: LPNC UMR 5105, Université Savoie Mont Blanc-CNRS, Chambéry, France;
authors.forename: M
authors.initials: M
authors.lastname: Guerraz
authors.affiliation: INT UMR 7289, Aix Marseille Université-CNRS, Marseille, France.
authors.forename: A
authors.initials: A
authors.lastname: Montagnini
authors.affiliation: LNIA UMR 7260, Aix Marseille Université-Centre National de la Recherche Scientifique (CNRS), Marseille, France; Anne.Kavounoudias@univ-amu.fr.
authors.forename: A
authors.initials: A
authors.lastname: Kavounoudias
keywords: Bayesian modeling; illusions; kinesthesia; multisensory integration; muscle proprioception