This file was created by the Typo3 extension sevenpack version 0.7.14 --- Timezone: CEST Creation date: 2013-05-24 Creation time: 07-01-26 --- Number of references 6 article 4965 Journal of Vision 2008 4 8 4:20 1-19 Rapid reaching to a target is generally accurate, but also contains random and systematic error. Random errors result from noise in visual measurement, motor planning, and reach execution. Systematic error results from systematic changes in the mapping between the visual estimate of target location and the motor command necessary to reach the target (e.g. new spectacles, muscular fatigue). Humans maintain accurate reaching by recalibrating the visuomotor system, but no widely accepted computational model of the process exists. Given certain boundary conditions, a statistically optimal solution is a Kalman filter. We compared human to Kalman-filter behavior to determine how humans take into account the statistical properties of errors and the reliability with which those errors can be measured. For most conditions, human and Kalman-filter behavior was similar: Increasing measurement uncertainty caused similar decreases in recalibration rate; directionally asymmetric uncertainty caused different rates in differ ent directions; more variation in systematic error increased recalibration rate. However, behavior differed in one respect: Inserting random error by perturbing feedback position causes slower adaptation in Kalman filters, but had no effect in humans. This difference may be due to how biological systems remain responsive to changes in environmental statistics. We discuss the implications of this work. http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de Research Group Ernst http://journalofvision.org/8/4/20/ Biologische Kybernetik Max-Planck-Gesellschaft en 10.1167/8.4.20 jburgeJBurge marcMOErnst martybanksMSBanks article 3785 Journal of Vision 2005 12 5 11 1013-1023 The nervous system often combines visual and haptic information about object properties such that the combined estimate is more precise than with vision or haptics alone. We examined how the system determines when to combine the signals. Presumably, signals should not be combined when they come from different objects. The likelihood that signals come from different objects is highly correlated with the spatial separation between the signals, so we asked how the spatial separation between visual and haptic signals affects their combination. To do this, we first created conditions for each observer in which the effect of combination—the increase in discrimination precision with two modalities relative to performance with one modality—should be maximal. Then under these conditions we presented visual and haptic stimuli separated by different spatial distances and compared human performance with predictions of a model that combined signals optimally. We found that discrimination precision was essentially optimal when the signals came from the same location, and that discrimination precision was poorer when the signals came from different locations. Thus, the mechanism of visual-haptic combination is specialized for signals that coincide in space. http://www.kyb.tuebingen.mpg.de/fileadmin/user_upload/files/publications/JOV-00052-2005_in_press_[0].pdf http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de Department Bülthoff Research Group Ernst http://journalofvision.org/5/11/7/ Biologische Kybernetik Max-Planck-Gesellschaft en 10.1167/5.11.7 SGepshtein jburgeJBurge marcMOErnst martybanksMBanks poster 3545 Journal of Vision 2005 9 5 8 871 The visuomotor system recalibrates when visual and motor maps are in conflict, bringing the maps back into correspondence. For recalibration to occur, a conflict has to be detected. Ernst and Endreß (VSS '04) showed that the rate of recalibration in a one-dimensional visually guided pointing task depends on the uncertainty of the feedback: faster recalibration with less uncertainty. In the present work, we examined two-dimensional recalibration and how the form of visual feedback affects it. Subjects pointed with an unseen hand to a brief visual target. Visual feedback was given indicating where the point landed. We introduced a constant conflict between pointing and feedback location and examined the changes in pointing as the subject adapted. We asked whether differential vertical and horizontal uncertainty in the visual feedback affects recalibration rate differentially, or whether rate is determined by the total uncertainty. We also varied feedback uncertainty in two ways. (1) We blurred the visual feedback, thereby reducing its localizability; in this condition, uncertainty could be determined on-line from one feedback stimulus. (2) We introduced random trial-by-trial perturbations in the feedback; in this condition, uncertainty had to be learned over time. In both cases, the distributions determining the vertical and horizontal uncertainties were 2D Gaussians. Adaptation profiles (changes over time in the point location relative to the visual feedback) changed only in response to changes in localizability. Recalibration was slowest in the direction of greatest uncertainty when uncertainty was due to blur, but rate was unaffected by trial-by-trial variation. This means that subjects do not estimate uncertainty over time in order to adjust reaching. Rather, they adjust trial by trial based mostly on feedback from the previous trial. http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de Department Bülthoff Research Group Ernst http://www.journalofvision.org/content/5/8/871.abstract Biologische Kybernetik Max-Planck-Gesellschaft Sarasota, FL, USA Fifth Annual Meeting of the Vision Sciences Society (VSS 2005) en 10.1167/5.8.871 jburgeJBurge marcMOErnst martybanksMBanks poster 3542 Perception 2005 8 34 ECVP Abstract Supplement 245-246 The sensorimotor system recalibrates when the visual and motor maps are in conflict, bringing the maps back into correspondence. We investigated the rate at which this recalibration occurs. The Kalman filter is a reasonable statistical model for describing visuomotor adaptation. It predicts that the rate of adaptation is dependent on the reliability of the feedback signal. It also predicts that random trial-to-trial perturbation of the feedback signal should have little or no effect on the adaptation rate. We tested these predictions using a pointing task. Subjects pointed with the unseen hand to a brief visual target. Visual feedback was then provided to indicate where the pointing movement had landed. During the experiment, we introduced a constant conflict between the pointing and feedback locations, and we examined the changes in pointing as the subject adapted. From the change in pointing position over trials we determined the adaptation rate. In experiment 1, we tested whether the reliability of the feedback affected adaptation rate by blurring the visual feedback and thereby reducing its localisability. Six levels of blur were used and spatial discrimination measurements confirmed that the blur was effective in altering stimulus localisability. We also constructed a Kalman filter model of the task. We found that adaptation rates of the filter and of the subjects decreased when blur was increased (ie with less reliable feedback). In experiment 2, the reliability of the visual feedback signal was manipulated by randomly perturbing the feedback signal on a trial-by-trial basis. Again, in good agreement with the prediction of the Kalman filter, we found no significant effect on adaptation rate as we manipulated the amount of perturbation. Taken together, these results provide evidence that human visuomotor adaptation behaviour is well modeled by a Kalman filter that uses weighted information from previous trials, including the reliability of the information, to update the visuomotor map. http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de Department Bülthoff Research Group Ernst http://www.perceptionweb.com/abstract.cgi?id=v050541 http://ecvp2005.neuralcorrelate.com/ Biologische Kybernetik Max-Planck-Gesellschaft A Coruña, Spain 28th European Conference on Visual Perception en marcMOErnst jburgeJBurge martybanksMBanks poster 2928 Journal of Vision 2004 8 4 8 140 Recent work showed that humans combine visual and haptic information about object size in a way that approaches statistical optimality: The precision of combined estimates is higher than with vision or touch alone (Ernst & Banks, 2002; Gepshtein & Banks, 2003). If the brain combines the visual and haptic signals optimally when they appear to come from the same object, the precision of combination should be greater when the signals originate from the same location in space. We examined this by varying the spatial offset between the visual and haptic stimuli. In a 2-IFC procedure, each interval contained visual and haptic stimuli, spatially superimposed or separated by up to 10 cm. The visual stimuli were random-dot stereograms of two parallel surfaces; the haptic stimuli were two parallel surfaces created by force-feedback devices. Observers indicated the interval containing the greater perceived inter-surface distance. The increase in precision with two cues as opposed to one cue should be greatest when visual and haptic weights are equal, so we equated the weights for each observer by finding the surface slant at which vision and haptics were equally precise (Gepshtein & Banks, 2003). We found that inter-modality, just-noticeable differences (JND) for object size grew as a function of spatial separation between the visual and haptic stimuli. With no separation, JNDs were close to optimal. With large separations, JNDs worsened. We examined whether this effect of spatial coincidence is affected by scene layout; for example, when the lack of coincidence is “explained” by occlusion of the haptic stimulus. http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de Department Bülthoff Research Group Ernst http://www.journalofvision.org/4/8/140/ Biologische Kybernetik Max-Planck-Gesellschaft Sarasota, FL, USA Fourth Annual Meeting of the Vision Sciences Society (VSS 2004) en 10.1167/4.8.140 SGepshtein jburgeJBurge martybanksMSBanks marcMOErnst conference ErnstBB2005 2005 6 6 15 The visuomotor system recalibrates when visual and motor maps are in conflict, bringing the maps back into correspondence. For recalibration to occur, a conflict has to be detected. Here we investigate the effect of signal reliability on the rate of recalibration. In a first study we showed that the rate of recalibration in a one-dimensional visually guided pointing task depends on the uncertainty of the feedback: faster recalibration with less uncertainty. We further also examined two-dimensional recalibration and how the specific form of visual feedback affects it. Subjects pointed with an unseen hand to a brief visual target. Visual feedback was given indicating where the point landed. We introduced a constant incongruity between pointing (tactual) and feedback (visual) location and examined the changes in pointing as the subject recalibrated. With this task we asked whether differential vertical and horizontal uncertainty in the visual feedback affects recalibration rate differentially, or whether rate is determined by the total uncertainty. We also varied feedback uncertainty in two ways. (1) We blurred the visual feedback, thereby reducing its localizability; in this condition, uncertainty could be determined on-line from one feedback stimulus. (2) We introduced random trial-by-trial perturbations in the feedback; in this condition, uncertainty had to be learned over time. In both cases, the distributions determining the vertical and horizontal uncertainties were 2D Gaussians. Recalibration profiles (changes over time in the point location relative to the visual feedback) changed only in response to changes in localizability. Recalibration was slowest in the direction of greatest uncertainty when uncertainty was due to blur, but rate was unaffected by trial-by-trial variation. This means that subjects do not estimate uncertainty over time in order to adjust reaching. Rather, they adjust trial by trial based mostly on feedback from the previous trial. http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de http://www.kyb.tuebingen.mpg.de Research Group Ernst Department Bülthoff Abstract Talk http://imrf.mcmaster.ca/IMRF/2005/viewabstract.php?id=11 Trento, Italy 6th International Multisensory Research Forum (IMRF 2005) marcMOErnst jburgeJBurge martybanksMSBanks