Effect of visuomotor-map uncertainty on visuomotor adaptation

Vision and proprioception contribute to generating hand movement. If a conflict between the visual and proprioceptive feedback of hand position is given, reaching movement is disturbed initially but recovers after training. Although previous studies have predominantly investigated the adaptive change in the motor output, it is unclear whether the contributions of visual and proprioceptive feedback controls to the reaching movement are modified by visuomotor adaptation. To investigate this, we focused on the change in proprioceptive feedback control associated with visuomotor adaptation. After the adaptation to gradually introduce visuomotor rotation, the hand reached the shifted position of the visual target to move the cursor to the visual target correctly. When the cursor feedback was occasionally eliminated (probe trial), the end point of the hand movement was biased in the visual-target direction, while the movement was initiated in the adapted direction, suggesting the incomplete adaptation of proprioceptive feedback control. Moreover, after the learning of uncertain visuomotor rotation, in which the rotation angle was randomly fluctuated on a trial-by-trial basis, the end-point bias in the probe trial increased, but the initial movement direction was not affected, suggesting a reduction in the adaptation level of proprioceptive feedback control. These results suggest that the change in the relative contribution of visual and proprioceptive feedback controls to the reaching movement in response to the visuomotor-map uncertainty is involved in visuomotor adaptation, whereas feedforward control might adapt in a manner different from that of the feedback control.     

Common processing constraints for visuomotor and visual mental rotations

Naive human subjects were tested in three different tasks: (1) a visuomotor mental rotation task, in which the subjects were instructed to move a cursor at a given angle from a stimulus direction; (2) a visual mental rotation task, in which the subjects had to decide whether a displayed letter was normal or mirror image regardless of its orientation in the plane of presentation; and (3) a visuomotor memory scanning task, in which a list of two to five stimuli directions were presented sequentially and then one of the stimuli (test stimulus), except the last one, was presented again. Subjects were instructed to move a cursor in the direction of the stimulus that followed the test stimulus in the previous sequence. The processing rate of each subject in each task was estimated using the linear relation between the response time and the angle (mental rotation tasks) or the list length (memory scanning task). We found that the processing rates in the mental rotation tasks were significantly correlated but that neither correlated significantly with the processing rate in the memory scanning task. These results suggest that visuomotor and visual mental rotations share common processing constraints that cannot be ascribed to general mental processing performances. Correspondence to: A.P. Georgopoulos, Brain Sciences Center     

Contributions of online visual feedback to the learning and generalization of novel finger coordination patterns

We explored how people learn new ways to move objects through space using neuromuscular control signals having more degrees of freedom than needed to unambiguously specify object location. Subjects wore an instrumented glove that recorded finger motions. A linear transformation matrix projected joint angle signals (a high-dimensional control vector) onto a two-dimensional cursor position on a video monitor. We assessed how visual information influences learning and generalization of novel finger coordination patterns as subjects practiced using hand gestures to manipulate cursor location. Three groups of test subjects practiced moving a visible cursor between different sets of screen targets. The hand-to-screen transformation was designed such that the different sets of targets (which we called implicit spatial cues) varied in how informative they were about the gestures to be learned. A separate control group practiced gesturing with explicit cues (pictures of desired gestures) without ongoing cursor feedback. Another control group received implicit spatial cueing and feedback only of final cursor position. We found that test subjects and subjects provided with explicit cues could learn to produce desired gestures, although training efficacy decreased as the amount of task-relevant feedback decreased. Although both control groups learned to associate screen targets with specific gestures, only subjects provided with online feedback of cursor motion learned to generalize in a manner consistent with the internal representation of an inverse hand-to-screen mapping. These findings suggest that spatial learning and generalization require dynamic feedback of object motion in response to control signal changes; static information regarding geometric relationships between controller and endpoint configurations does not suffice.     

Learning a visuomotor rotation: simultaneous visual and proprioceptive information is crucial for visuomotor remapping

Visuomotor adaptation is mediated by errors between intended and sensory-detected arm positions. However, it is not clear whether visual-based errors that are shown during the course of motion lead to qualitatively different or more efficient adaptation than errors shown after movement. For instance, continuous visual feedback mediates online error corrections, which may facilitate or inhibit the adaptation process. We addressed this question by manipulating the timing of visual error information and task instructions during a visuomotor adaptation task. Subjects were exposed to a visuomotor rotation, during which they received continuous visual feedback (CF) of hand position with instructions to correct or not correct online errors, or knowledge-of-results (KR), provided as a static hand-path at the end of each trial. Our results showed that all groups improved performance with practice, and that online error corrections were inconsequential to the adaptation process. However, in contrast to the CF groups, the KR group showed relatively small reductions in mean error with practice, increased inter-trial variability during rotation exposure, and more limited generalization across target distances and workspace. Further, although the KR group showed improved performance with practice, after-effects were minimal when the rotation was removed. These findings suggest that simultaneous visual and proprioceptive information is critical in altering neural representations of visuomotor maps, although delayed error information may elicit compensatory strategies to offset perturbations.     

How the lack of visuomotor feedback affects even the early stages of goal-directed pointing movements

Pointing movements made with a hidden cursor from the center of gaze to a stationary, visible target overshot the actual target location. The systematic error decreased when the final cursor location from the previous trial was shown, which likely led to the creation of an internal sensorimotor model of movement. However, the putative model had a short memory, and could not substitute for on-line visuomotor feedback on subsequent trials. Contrary to common belief, the effect of a lack of visuomotor feedback was seen even in the early acceleration stage of the movement trajectory. Unchecked in the absence of visual monitoring, the acceleration stage of the movement lasted longer, as was evidenced by the significantly larger value of the peak cursor speed. Moreover, the speed peaked much later in the course of the movement. Speed declined more rapidly thereafter. Consequently, the delayed deceleration stage lasted far less than the acceleration stage. In the absence of visual feedback, the shift rightward in time of the peak speed position (PSP) in relation to total movement duration and other changes in the trajectory imply that visual feedback must play a significant role in determining when acceleration ceases (d V/d t=0), and argue against the traditional notion that visuomotor feedback is unavailable until the later stages of movement. Moreover, our data suggest that non-visual modalities, e.g., proprioception, may be too slow to make up for the absence of vision.     

Influence of disturbances on the control of PC-mouse,goal-directed arm movements

This study concerns the influence of visuomotor rotating disturbance on motion dynamics and brain activity. It involves using a PC-mouse and introducing a predefined bias angle between the direction of motion of the mouse pointer and that of the screen cursor. Subjects were asked to execute three different tasks, designed to study the effect of visuomotor rotation on direction control, extent control or the two together. During each task, mouse movement, screen cursor movement and electroencephalograph (EEG) signals were recorded. An algorithm was used to detect and discard EEG signals contaminated by artifacts. Movement performance indexes and brain activity are used to evaluate motion control, tracking ability, learning and control. The results suggest the direction control is planned before the movement and controlled by an adaptive control while extent control is controlled by a real-time feedback. The measurements also confirm that increased motion and/or brain activity occur for bias angles in the ranges ±(90–120°) for both direction and extension controls. After-effects when changing the angle of visual rotation have been seen to be proportional to the variation in the adaptation angle.     

Real-time error detection but not error correction drives automatic visuomotor adaptation

We investigated the role of visual feedback of task performance in visuomotor adaptation. Participants produced novel two degrees of freedom movements (elbow flexion–extension, forearm pronation–supination) to move a cursor towards visual targets. Following trials with no rotation, participants were exposed to a 60° visuomotor rotation, before returning to the non-rotated condition. A colour cue on each trial permitted identification of the rotated/non-rotated contexts. Participants could not see their arm but received continuous and concurrent visual feedback (CF) of a cursor representing limb position or post-trial visual feedback (PF) representing the movement trajectory. Separate groups of participants who received CF were instructed that online modifications of their movements either were, or were not, permissible as a means of improving performance. Feedforward-mediated performance improvements occurred for both CF and PF groups in the rotated environment. Furthermore, for CF participants this adaptation occurred regardless of whether feedback modifications of motor commands were permissible. Upon re-exposure to the non-rotated environment participants in the CF, but not PF, groups exhibited post-training aftereffects, manifested as greater angular deviations from a straight initial trajectory, with respect to the pre-rotation trials. Accordingly, the nature of the performance improvements that occurred was dependent upon the timing of the visual feedback of task performance. Continuous visual feedback of task performance during task execution appears critical in realising automatic visuomotor adaptation through a recalibration of the visuomotor mapping that transforms visual inputs into appropriate motor commands.     

Visual target separation determines the extent of generalisation between opposing visuomotor rotations

Here we investigated the influence of angular separation between visual and motor targets on concurrent adaptation to two opposing visuomotor rotations. We inferred the extent of generalisation between opposing visuomotor rotations at individual target locations based on whether interference (negative transfer) was present. Our main finding was that dual adaptation occurred to opposing visuomotor rotations when each was associated with different visual targets but shared a common motor target. Dual adaptation could have been achieved either within a single sensorimotor map (i.e. with different mappings associated with different ranges of visual input), or by forming two different internal models (the selection of which would be based on contextual information provided by target location). In the present case, the pattern of generalisation was dependent on the relative position of the visual targets associated with each rotation. Visual targets nearest the workspace of the opposing visuomotor rotation exhibited the most interference (i.e. generalisation). When the minimum angular separation between visual targets was increased, the extent of interference was reduced. These results suggest that the separation in the range of sensory inputs is the critical requirement to support dual adaptation within a single sensorimotor mapping.     

Differentiating between two models of motor lateralization

This study was designed to differentiate between two models of motor lateralization: "feedback corrections" and dynamic dominance. Whereas the feedback correction hypothesis suggests that handedness reflects a dominant hemisphere advantage for visual-mediated correction processes, dynamic dominance proposes that each hemisphere has become specialized for distinct aspects of control. This model suggests that the dominant hemisphere is specialized for controlling task dynamics, as required for coordinating efficient trajectories, and the nondominant hemisphere is specialized for controlling limb impedance, as required for maintaining stable postures. To differentiate between these two models, we examined whether visuomotor corrections are mediated differently for the nondominant and dominant arms. Participants performed targeted reaches in a virtual reality environment in which visuomotor rotations occurred in two directions that elicited corrections with different coordination requirements. The feedback correction model predicts a dominant arm advantage for the timing and accuracy of corrections in both directions. Dynamic dominance predicts that correction timing and accuracy will be similar for both arms, but that interlimb differences in the quality of corrections will depend on the coordination requirements, and thus, direction of corrections. Our results indicated that correction time and accuracy did not depend on arm. However, correction quality, as reflected by trajectory curvature, depended on both arm and rotation direction. Nondominant trajectories were systematically more curvilinear than dominant trajectories for corrections with the highest coordination requirement. These results support the dynamic dominance hypothesis.     

Differential influence of vision and proprioception on control of movement distance

The purpose of this study was to investigate the contribution of proprioceptive and visual information about initial limb position in controlling the distance of rapid, single-joint reaching movements. Using a virtual reality environment, we systematically changed the relationship between actual and visually displayed hand position as subjects’ positioned a cursor within a start circle. No visual feedback was given during the movement. Subjects reached two visual targets (115 and 125° elbow angle) from four start locations (90, 95, 100, and 105° elbow angle) under four mismatch conditions (0, 5, 10, or 15°). A 2×4×4 ANOVA enabled us to ask whether the subjects controlled the movement distance in accord with the virtual, or the actual hand location. Our results indicate that the movement distance was mainly controlled according to the virtual start location. Whereas distance modification was most extensive for the closer target, analysis of acceleration profiles revealed that, regardless of target position, visual information about start location determined the initial peak in tangential hand acceleration. Peak acceleration scaled with peak velocity and movement distance, a phenomenon termed “pulse-height” control. In contrast, proprioceptive information about actual hand location determined the duration of acceleration, which also scaled with peak velocity and movement distance, a phenomenon termed “pulse-width” control. Because pulse-height and pulse-width mechanisms reflect movement planning and sensory-based corrective processes, respectively, our current findings indicate that vision is used primarily for planning movement distance, while proprioception is used primarily for online corrections during rapid, unseen movements toward visual targets.     

Behavioral and neural correlates of visuomotor adaptation observed through a brain-computer interface in primary motor cortex

Brain-computer interfaces (BCIs) provide a defined link between neural activity and devices, allowing a detailed study of the neural adaptive responses generating behavioral output. We trained monkeys to perform two-dimensional center-out movements of a computer cursor using a BCI. We then applied a perturbation by randomly selecting a subset of the recorded units and rotating their directional contributions to cursor movement by a consistent angle. Globally, this perturbation mimics a visuomotor transformation, and in the first part of this article we characterize the psychophysical indications of motor adaptation and compare them with known results from adaptation of natural reaching movements. Locally, however, only a subset of the neurons in the population actually contributes to error, allowing us to probe for signatures of neural adaptation that might be specific to the subset of neurons we perturbed. One compensation strategy would be to selectively adapt the subset of cells responsible for the error. An alternate strategy would be to globally adapt the entire population to correct the error. Using a recently developed mathematical technique that allows us to differentiate these two mechanisms, we found evidence of both strategies in the neural responses. The dominant strategy we observed was global, accounting for ～86% of the total error reduction. The remaining 14% came from local changes in the tuning functions of the perturbed units. Interestingly, these local changes were specific to the details of the applied rotation: in particular, changes in the depth of tuning were only observed when the percentage of perturbed cells was small. These results imply that there may be constraints on the network's adaptive capabilities, at least for perturbations lasting only a few hundreds of trials.     

Body-centered visuomotor adaptation

Previous research has shown that humans generalize distortions of visuomotor feedback in terms of egocentric rotations. We examined whether these rotations are linked to the orientation of the eyes or of the shoulder of the arm that was used. Subjects moved a hand-held cube between target locations in a sequence of adaptation and test phases. During adaptation phases, subjects received either veridical or distorted visual feedback about the location of the cube. The distortions were changes in azimuth either relative to the eyes or to the shoulder. During test phases subjects received no visual feedback. Test phases were performed either with the arm that was exposed to the distorted feedback or with the unexposed arm. We compared test movement endpoints after distorted feedback with ones after veridical feedback. For the exposed arm, the spatial layout of the changes in endpoints clearly reflected the small differences between a rotation around the shoulder and around the eyes. For the unexposed arm, the changes in endpoints were smaller for both types of distortions and were less consistent with the distortions. Thus although the adaptation closely matches the imposed distortion, it does not appear to be directly linked to the orientation of the eyes or of the exposed arm.     

Online and post-trial feedback differentially affect implicit adaptation to a visuomotor rotation

Multiple motor learning processes can be discriminated in visuomotor rotation paradigms. At least four processes have been proposed: Implicit adaptation updates an internal model based on prediction errors. Model-free reinforcement reinforces actions that achieve task success. Use-dependent learning favors repetition of prior movements, and strategic learning uses explicit knowledge about the task. The current experiment tested whether the processes involved in motor learning differ when visual feedback is altered. Specifically, we hypothesized that online and post-trial feedback would cause different amounts of implicit adaptation. Twenty subjects performed drawing movements to targets under a 45° counterclockwise visuomotor rotation while aiming at a clockwise adjacent target. Subjects received visual feedback via a cursor on a screen. One group saw the cursor throughout the movement (online feedback), while the other only saw the final position after movement execution (post-trial feedback). Both groups initially hit the target by applying the strategy. After 80 trials, subjects with online feedback had drifted in clockwise direction [mean direction error: 15.1° (SD 11.2°)], thus overcompensating the rotation. Subjects with post-trial feedback remained accurate [mean: 0.7° (SD 2.0°), TIME × GROUP: F = 3.926, p = 0.003]. We interpret this overcompensation to reflect implicit adaptation isolated from other mechanisms, because it is driven by prediction error rather than task success (model-free reinforcement) or repetition (use-dependent learning). The current findings extend previous work (e.g., Mazzoni and Krakauer in J Neurosci 26:3642–3645, 2006; Hinder et al. in Exp Brain Res 201:191–207, 2010) and suggest that online feedback promotes more implicit adaptation than does post-trial feedback.     

The role of proprioception and attention in a visuomotor adaptation task

The role of proprioception in the control and adaptation of visuomotor relationships is still unclear. We have studied a deafferented subject, IW, and control subjects in a task in which they used single joint elbow extension to move to a visual target, with visual feedback of the terminal position provided by a cursor displayed in the plane of their movements. We report the differences in movement accuracy between the deafferented subject and controls in the normal task and when challenged with a cognitive load, counting backwards. All subjects were less accurate when counting; this was a small effect for the controls (<10% change) but much greater for the deafferented subject (>60% change). We also examined changes in movement kinematics when the instructed amplitude was altered via a changed gain between final arm position and presentation of the feedback cursor. The deafferented subject maintained temporal movement parameters stable and altered amplitude by scaling force (i.e. changed peak velocity), whereas the controls scaled both movement velocity and duration. Finally, we compared the subjects' adaptation of movement amplitude after a period of exposure to the changed visuomotor gain. The deafferented subject was able to adapt, but his adaptation was severely impaired by the counting task. These results suggest that proprioception is not an absolute requirement for adaptation to occur. Instead, proprioception has a more subtle role to play in the adjustment to visuomotor perturbations. It has an important role in the control of reaching movements, while in the absence of proprioception, attention appears necessary to monitor movements.     

Visuomotor adaptation and generalization with repeated and varied training

Many studies have shown that reaching movements to visual targets can rapidly adapt to altered visual feedback of hand motion (i.e., visuomotor rotation) and generalize to new target directions. This generalization is thought to reflect the acquisition of a neural representation of the novel visuomotor environment that is localized to the particular trained direction. In these studies, participants perform movements to a small number of target locations repeatedly. However, it is unclear whether adaptation and generalization are comparable when target locations are constantly varied and participants reach to visual targets one time only. Here, we compared performance for reaches to a 30° counter-clockwise visuomotor rotation to four targets, spaced 90° apart across four areas of workspace 18 times each (repeated practice (RP)) with one time only reaching movements to 72 targets, spaced 5° apart (varied practice (VP)). For both training groups, participants performed 18 reaches to radial targets (either at the repeated or varied location) in a specific area of the workspace (i.e., one of four quadrants) before reaching in the adjacent workspace. We found that the RP group adapted more completely compared to the VP group. Conversely, the VP group generalized to new target directions more completely when reaching without cursor feedback compared to the RP group. This suggests that RP and VP follow a mainly common pattern of adaptation and generalization represented in the brain, with benefits of faster adaptation with RP and more complete generalization with VP.     

Evidence for an eye-centered spherical representation of the visuomotor map

During visually guided movement, visual coordinates of target location must be transformed into coordinates appropriate for movement. To investigate the representation of this visuomotor coordinate transformation, we examined changes in pointing behavior induced by a local visuomotor remapping. The visual feedback of finger position was limited to one location within the workspace, at which a discrepancy was introduced between the actual and visually perceived finger position. This remapping induced a change in pointing that extended over the entire workspace and was best captured by a spherical coordinate system centered near the eyes.     

Changes in motor cortical activity during visuomotor adaptation

We examined neuronal activity in three motor cortical areas while a rhesus monkey adapted to novel visuomotor transforms. The monkey moved a joystick that controlled a cursor on a video screen. Each trial began with the joystick centered. Next, the cursor appeared in one of eight positions, arranged in a circle around a target stimulus at the center of the screen. To receive reinforcement, the monkey moved the joystick so that the cursor contacted the target continuously for 1s. The video monitor provided continuous visual feedback of both cursor and target position. With those elements of the task constant, we modified the transform between joystick movement and that of the cursor at the beginning of a block of trials. Neuronal activity was studied as the monkey adapted to these novel joystick-cursor transforms. Some novel tasks included spatial transforms such as single-axis inversions, asymmetric double-axis inversions and angular deviations (also known as rotations). Other tasks involved changes in the spatiotemporal pattern and magnitude of joystick movement. As the monkey adapted to various visuomotor tasks, 209 task-related neurons (selected for stable background activity) showed significant changes in their task-related activity: 88 neurons in the primary motor cortex (M1), 32 in the supplementary motor cortex (M2), and 89 in the caudal part of the dorsal premotor cortex (PMdc). Slightly more than half of the sample in each area showed significant changes in the magnitude of activity modulation during adaptation, with the number of increases approximately equaling the number of decreases. These data support the prediction that changes in task-related neuronal activity can be observed in M1 during motor adaptation, but fail to support the hypothesis that M1 and PMdc differ in this regard. When viewed in population averages, motor cortex continued to change its activity for at least dozens of trials after performance reached a plateau. This slow, apparently continuing change in the pattern and magnitude of task-related activity may reflect the initial phases of consolidating the motor memory for preparing and executing visuomotor skills.     

The efficacy of colour cues in facilitating adaptation to opposing visuomotor rotations

We investigated visuomotor adaptation using an isometric, target-acquisition task. Following trials with no rotation, two participant groups were exposed to a random sequence of 30° clockwise (CW) and 60° counter-clockwise (CCW) rotations, with (DUAL-CUE), or without (DUAL-NO CUE), colour cues that enabled each environment (non-rotated, 30° CW and 60° CCW) to be identified. A further three groups experienced only 30° CW trials or only 60° CCW trials (SINGLE rotation groups) in which each visuomotor mapping was again associated with a colour cue. During training, all SINGLE groups reduced angular deviations of the cursor path during the initial portion of the movements, indicating feedforward adaptation. Consistent with the view that the adaptation occurred automatically via recalibration of the visuomotor mapping (Krakauer et al. 1999), post-training aftereffects were observed, despite colour cues that indicated that no rotation was present. For the DUAL-CUE group, angular deviations decreased with training in the 60° trials, but were unchanged in the 30° trials, while for the DUAL-NO CUE group angular deviations decreased for the 60° CW trials but increased for the 30° CW trials. These results suggest that in a dual adaptation paradigm a colour cue can permit delineation of the two environments, with a subsequent change in behaviour resulting in improved performance in at least one of these environments. Increased reaction times within the training block, together with the absence of aftereffects in the post-training period for the DUAL-CUE group suggest an explicit cue-dependent strategy was used in an attempt to compensate for the rotations.     

Visuomotor tracking with delayed visual feedback

A rhesus monkey and five human subjects used a hand-held joystick to track unpredictable continuously moving targets. Both monkey and human respond by making discrete ("step-and-hold") corrections of positional error, at an average frequency of 1.33 and 2.26 movements/second, respectively. By delaying visual feedback of joystick position, we could reduce these frequencies in a predictable manner. These results imply that the primate visuomotor system probably does not operate as a "sampled-data mechanism" governed by an asynchronous clock, but that inevitable delays in visuomotor feedback control determine the frequency of corrective movements.     

Effect of viewing distance and location of the axis of head rotation on the monkey's vestibuloocular reflex. I. Eye movement responses.

1. The vestibuloocular reflex (VOR) stabilizes images on the retina against movements of the head in space. Viewing distance, target eccentricity, and location of the axis of rotation may influence VOR responses because rotation of the head about most axes in space rotates and translates the eyes relative to visual targets. To study the VOR response to combined rotation and translation, monkeys were placed on a rate table and rotated briefly in the dark about a vertical axis that was located in front of or behind the eyes. The monkeys fixated a near or far visual target that was extinguished before the rotation. Eye movements were recorded from both eyes by the use of the search coil technique. 2. Peak eye velocity evoked by the VOR was linearly related to vergence angle for any axis of rotation. The percent change in the VOR with near target viewing relative to far target viewing at a vergence angle of 20 degrees was linearly related to the location of the axis of rotation. Axes located behind the eyes produced positive changes in VOR amplitude, and axes located in front of the eyes produced negative changes in VOR amplitude. An axis of rotation located in the coronal plane containing the centers of rotation of the eyes produced no modification of VOR amplitude. For any axis, the VOR compensated for approximately 90% of the translation of the eye relative to near targets. 3. The initial VOR response was not correct in magnitude but was refined by a series of three temporally delayed corrections of increasing complexity. The earliest VOR-evoked eye movement (10-20 ms after rotation onset) was independent of viewing distance and rotational axis location. In the next 100 ms, eye speed appeared to be sequentially modified three times: within 20 ms by viewing distance; within 30 ms by otolith translation; and within 100 ms by eye translation relative to the visual target. 4. These data suggest a formal model of the VOR consisting of four channels. Channel 1 conveys an unmodified head rotation signal with a pure delay of 10 ms. Channel 2 conveys an angular head velocity signal, modified by viewing distance with a pure delay of 20 ms, but invariant with respect to the location of the axis of rotation. Channel 3 conveys a linear head velocity signal, dependent on the location of the axis of rotation, that is modified by viewing distance with a pure delay of 30 ms.(ABSTRACT TRUNCATED AT 400 WORDS)