Analysis of motor characteristics of reaching movements in children with cerebral palsy.

Studies confirm that children with cerebral palsy (CwCP) have difficulty with simple, everyday movements like reaching for objects. Accurate reaching requires that shoulder and elbow joints are coordinated to move the hand along a smooth path to the desired target location. Here we examined multijoint coordination by comparing reaching performance in the affected and unaffected limbs of CwCP (nine children, six girls and three boys, aged 8-10 years) to reaching performance in the non-dominant and dominant limbs of typically-developing age- and gender-matched control (CTR) children. The hypothesis was that CwCP would show the effects of coordination deficits in both their affected and unaffected limbs. All children performed two sessions (one session with each arm) of speeded reaching movements to three targets arranged to manipulate the required pattern of shoulder and elbow coordination. The movements were tracked with a motion tracker allowing us to assess the following measures: movement distance, duration, and speed, hand-path deviation from linearity, final position accuracy and precision, and measures of shoulder and elbow excursion. We found that CwCP made reaches that covered a greater distance and took more time, that their shoulder and elbow rotations were larger, and that their movements showed greater deviation from linearity than the movements performed by CTR children. Children with CP were also more variable than CTR children on every measure except movement duration. The pattern of shoulder and elbow rotation observed in the CwCP group represents a coordination pattern that is significantly different from the pattern used by CTR children and may represent a greater reliance by CwCP on proximal muscular control systems. The discussion section considers the role that the cortical-spinal system may play in multijoint coordination.

Using a chopping task to compare expert and competent motor memory.

Here, we consider the memory of motor experts using a real-world task-chefs chopping vegetables. We compare expert chefs to competent home cooks, defined as skill enthusiasts or very good performers whose performance experience is narrower than experts. We considered the possibility that competent home cooks' memory for knife skills is organized differently than chefs', and we predicted that their performance will be more vulnerable to interference than experts' in the face of challenges. We used a novel vegetable-chopping task to test the hypothesis that experts are less vulnerable to motor interference than competents. Trained chefs and competent home cooks performed a chopping task in which they were asked to chop a sweet potato into 5-mm wide slices, matching the beat of a metronome (120 beats/min). Following an initial block of trials, each participant was exposed to an altered frequency interference condition and then performed trials of the original task again. Interference was inferred if the second performance of the original task was changed compared with initial performance. Competents' timing and spatial variability were significantly affected by the interference task, but experts' performance was stable. These results support the idea that the vulnerability of motor memory to interference changes with experience, and that in addition to better performance, experts' motor memories are stored and recalled differently than competents'.NEW & NOTEWORTHY From the lab, a comparison of expert chefs to competent home cooks on a defined chopping task shows that vulnerability of motor memory to interference changes with expertise.

A quasi-experimental examination of weight-reducing dehydration practices in collegiate male rowers.

BACKGROUND: Lightweight rowers commonly utilize weight loss techniques over 24-h before competition to achieve the qualifying weight for racing. The objective was to investigate, using a quasi-experimental design, whether changes in weight resulting from dehydration practices are related to changes in proxies of bodily systems involved in rowing and whether these relationships depend on the dehydration technique used. METHODS: Twelve elite male rowers performed a power test, an incremental VO2max test, and a visuomotor battery following: weight loss via thermal exposure, weight loss via fluid abstinence and then thermal exposure, and no weight loss. The total percent body mass change (%BMC), %BMC attributable to thermal exposure, and %BMC attributable to fluid abstinence were used to predict performance variables. RESULTS: Fluid abstinence but not thermal exposure was related to a lower total wattage produced on a incremental VO2max test (b = 4261.51 W/1%BMC, 95%CI = 1502.68-7020.34), lower wattages required to elicit 2 mmol/L (b = 27.84 W/1%BMC, 95%CI = 14.69-40.99) and 4 mmol/L blood lactate (b = 20.45 W/1%BMC, 95%CI = 8.91-31.99), and slower movement time on a visuomotor task (b = -38.06 ms/1%BMC, 95%CI = -62.09--14.03). CONCLUSIONS: Dehydration related weight changes are associated with reductions in some proxies of bodily systems involved in rowing but depend on the dehydration technique used.

Limb position drift results from misalignment of proprioceptive and visual maps.

Previous work (Brown et al., 2003a,b) has shown that limb position drifts when individuals make repetitive movements in the absence of visual feedback. The purpose of this study was to examine whether limb position drift might reflect a misalignment in visual and proprioceptive maps by examining the nature of information used to specify new movements from a drifted limb position. In a virtual reality (VR) environment, participants made continuous movements with their dominant right hand between two targets positioned 15cm apart, paced by a 0.625-Hz metronome. After 5 cycles, cursor feedback of the hand was removed for the next 44 cycles, which induced an average drift in hand position of roughly 5cm. On the 50th cycle, participants were required to move to one of 6 new targets from the drifted hand position. Kinematic analysis indicated that movement direction was unambiguously determined by the visual input marked by the original start position, or the last-seen hand position. Forward dynamics analysis revealed that current limb configuration was used to inform joint torques to produce this parallel direction. For new movement specification, accurate proprioceptive information about the drifted limb position was used, even though it was apparently not available for detecting drift in the first place. Movement distance varied directly with the extent of limb drift, although the differentiation of visual and proprioceptive control of distance could not be analyzed, as our control conditions were not significantly different for this measure. We suggest that movement drift, in the absence of visual feedback during cyclic repetitive movements, reflects a misalignment between largely accurate visual and proprioceptive maps, rather than a weighted fusion of the two modalities.

On the contributions of vision and proprioception to the representation of hand-near targets.

Performance is often improved when targets are presented in space near the hands rather than far from the hands. Performance in hand-near space may be improved because participants can use proprioception from the nearby limb and hand to provide a narrower and more resolute frame of reference. An equally compelling alternative is that targets appearing near the hand fall within the receptive fields of visual-tactile bimodal cells, recruiting them to assist in the visual representation of targets that appear near but not far from the hand. We distinguished between these two alternatives by capitalizing on research showing that vision and proprioception have differential effects on the precision of target representation (van Beers RJ, Sittig AC, Denier van der Gon JJ. Exp Brain Res 122: 367-377, 1998). Participants performed an in-to-center reaching task to an array of central target locations with their right hand, while their left hand rested near (beneath) or far from the target array. Reaching end-point accuracy, variability, time, and speed were assessed. We predicted that if proprioception contributes to the representation of hand-near targets, then error variability in depth will be smaller in the hand-near condition than in the hand-far condition. By contrast, if vision contributes to the representation of hand-near targets, then error variability along the lateral dimension will be smaller in the hand-near than in the hand-far condition. Our results showed that the placement of the hand near the targets reduced end-point error variability along the lateral dimension only. The results suggest that hand-near targets are represented with greater visual resolution than far targets.

Different neural networks are involved in audiovisual speech perception depending on the context.

How are we able to easily and accurately recognize speech sounds despite the lack of acoustic invariance? One proposed solution is the existence of a neural representation of speech syllable perception that transcends its sensory properties. In the present fMRI study, we used two different audiovisual speech contexts both intended to identify brain areas whose levels of activation would be conditioned by the speech percept independent from its sensory source information. We exploited McGurk audiovisual fusion to obtain short oddball sequences of syllables that were either (a) acoustically different but perceived as similar or (b) acoustically identical but perceived as different. We reasoned that, if there is a single network of brain areas representing abstract speech perception, this network would show a reduction of activity when presented with syllables that are acoustically different but perceived as similar and an increase in activity when presented with syllables that are acoustically similar but perceived as distinct. Consistent with the long-standing idea that speech production areas may be involved in speech perception, we found that frontal areas were part of the neural network that showed reduced activity for sequences of perceptually similar syllables. Another network was revealed, however, when focusing on areas that exhibited increased activity for perceptually different but acoustically identical syllables. This alternative network included auditory areas but no left frontal activations. In addition, our findings point to the importance of subcortical structures much less often considered when addressing issues pertaining to perceptual representations.

Global and local processing near the left and right hands.

Visual targets can be processed more quickly and reliably when a hand is placed near the target. Both unimodal and bimodal representations of hands are largely lateralized to the contralateral hemisphere, and since each hemisphere demonstrates specialized cognitive processing, it is possible that targets appearing near the left hand may be processed differently than targets appearing near the right hand. The purpose of this study was to determine whether visual processing near the left and right hands interacts with hemispheric specialization. We presented hierarchical-letter stimuli (e.g., small characters used as local elements to compose large characters at the global level) near the left or right hands separately and instructed participants to discriminate the presence of target letters (X and O) from non-target letters (T and U) at either the global or local levels as quickly as possible. Targets appeared at either the global or local level of the display, at both levels, or were absent from the display; participants made foot-press responses. When discriminating target presence at the global level, participants responded more quickly to stimuli presented near the left hand than near either the right hand or in the no-hand condition. Hand presence did not influence target discrimination at the local level. Our interpretation is that left-hand presence may help participants discriminate global information, a right hemisphere (RH) process, and that the left hand may influence visual processing in a way that is distinct from the right hand.

A brief review of the role of training in near-tool effects.

Research suggests that, like near-hand effects, visual targets appearing near the tip of a hand-held real or virtual tool are treated differently than other targets. This paper reviews neurological and behavioral evidence relevant to near-tool effects and describes how the effect varies with the functional properties of the tool and the knowledge of the participant. In particular, the paper proposes that motor knowledge plays a key role in the appearance of near-tool effects.

The role of motor learning in spatial adaptation near a tool.

Some visual-tactile (bimodal) cells have visual receptive fields (vRFs) that overlap and extend moderately beyond the skin of the hand. Neurophysiological evidence suggests, however, that a vRF will grow to encompass a hand-held tool following active tool use but not after passive holding. Why does active tool use, and not passive holding, lead to spatial adaptation near a tool? We asked whether spatial adaptation could be the result of motor or visual experience with the tool, and we distinguished between these alternatives by isolating motor from visual experience with the tool. Participants learned to use a novel, weighted tool. The active training group received both motor and visual experience with the tool, the passive training group received visual experience with the tool, but no motor experience, and finally, a no-training control group received neither visual nor motor experience using the tool. After training, we used a cueing paradigm to measure how quickly participants detected targets, varying whether the tool was placed near or far from the target display. Only the active training group detected targets more quickly when the tool was placed near, rather than far, from the target display. This effect of tool location was not present for either the passive-training or control groups. These results suggest that motor learning influences how visual space around the tool is represented.

Agency and control for the integration of a virtual tool into the peripersonal space.

Our representation of the peripersonal space is tied to our representation of our bodies. This representation appears to be flexible and it can be updated to include the space in which tools work, particularly when the tool is actively used. One indicator of this update is the increased efficiency with which sensory events near the tool are processed. In the present study we examined the role of visuomotor control in extending peripersonal space to a common virtual tool-a computer mouse cursor. In particular, after participants were exposed to different spatial mappings between movements of the mouse cursor and movements of their hand, participants' performance in a motion-onset detection task was measured, with the mouse cursor as the stimulus. When participants, during exposure, had the ability to move the cursor efficiently and accurately (familiar hand-cursor mapping), they detected motion-onset targets more quickly than when they could not move the cursor at all during exposure (no hand-cursor mapping). Importantly, reversing the spatial correspondence between the movements of the hand and the cursor (unfamiliar hand-cursor mapping) during exposure, which was thought to preserve the ability to move the cursor (ie agency) while weakening the ability to make the movements efficiently and accurately (ie control), eliminated the detection-facilitation effect. These results provide evidence for the possible extension of peripersonal space to frequently used objects in the virtual domain. Importantly, these extensions seem to depend on the participant's knowledge of the dynamic spatial mapping between the acting limb and the visible virtual tool.

Effect of trial order and error magnitude on motor learning by observing.

Watching an actor make reaching movements in a perturbing force field provides the observer with information about how to compensate for that force field. Here we asked two questions about the nature of information provided to the observer. Is it important that the observer learn the difference between errant (curved) movements and goal (straight) movements by watching the actor progress in a relatively orderly fashion from highly curved to straight movements over a series of trials? Or is it sufficient that the observer sees only reaching errors in the force field (FF)? In the first experiment, we found that observers performed better if they observed reaches in a FF that was congruent, rather than incongruent, with the FF used in a later test. Observation-trial order had no effect on performance, suggesting that observers understood the goal in advance and perhaps learned about the force-field by observing movement curvature. Next we asked whether observers learn optimally by observing the actor's mistakes (high-error trials), if they learn by watching the actor perform with expertise in the FF (low-error trials), or if they need to see contrast between errant and goal behavior (a mixture of both high- and low-error trials). We found that observers who watched high-error trials were most affected by observation but that significant learning also occurred if observers watched only some high-error trials. This result suggests that observers learn to adapt their reaching to an unpredictable FF best when they see the actor making mistakes.

fMRI activation during observation of others' reach errors.

When exposed to novel dynamical conditions (e.g., externally imposed forces), neurologically intact subjects easily adjust motor commands on the basis of their own reaching errors. Subjects can also benefit from visual observation of others' kinematic errors. Here, using fMRI, we scanned subjects watching movies depicting another person learning to reach in a novel dynamic environment created by a robotic device. Passive observation of reaching movements (whether or not they were perturbed by the robot) was associated with increased activation in fronto-parietal regions that are normally recruited in active reaching. We found significant clusters in parieto-occipital cortex, intraparietal sulcus, as well as in dorsal premotor cortex. Moreover, it appeared that part of the network that has been shown to be engaged in processing self-generated reach error is also involved in observing reach errors committed by others. Specifically, activity in left intraparietal sulcus and left dorsal premotor cortex, as well as in right cerebellar cortex, was modulated by the amplitude of observed kinematic errors.

Repetitive transcranial magnetic stimulation to the primary motor cortex interferes with motor learning by observing.

Neural representations of novel motor skills can be acquired through visual observation. We used repetitive transcranial magnetic stimulation (rTMS) to test the idea that this "motor learning by observing" is based on engagement of neural processes for learning in the primary motor cortex (M1). Human subjects who observed another person learning to reach in a novel force environment imposed by a robot arm performed better when later tested in the same environment than subjects who observed movements in a different environment. rTMS applied to M1 after observation reduced the beneficial effect of observing congruent forces, and eliminated the detrimental effect of observing incongruent forces. Stimulation of a control site in the frontal cortex had no effect on reaching. Our findings represent the first direct evidence that neural representations of motor skills in M1, a cortical region whose role has been firmly established for active motor learning, also underlie motor learning by observing.

Vision in the palm of your hand.

Here we show that pointing movements made to visual targets projected onto the palm of the hand are more precise and accurate than those made to targets projected onto back of the hand. This advantage may be related to the fact that the number of cortical bimodal neurons coding both visual and tactile stimuli increases with tactile receptor density, which is known to be higher in glabrous than in hairy skin.

A hand in blindsight: hand placement near target improves size perception in the blind visual field.

Bimodal visual-tactile neurons respond to visual and/or tactile stimuli presented near the hands, arms, and face. The strength of bimodal-cell response to a visual stimulus depends on its proximity to the hand. We tested the hypothesis that hand proximity to a visual stimulus would influence unconscious residual vision in the blind field. MB is a 26-year-old man with a dense upper-left quadrantanopia following surgical treatment that severed Meyer's loop, and SB is a 35-year-old man with a dense left hemianopia following childhood meningitis. Testing for "hand-assisted" blindsight in MB allowed us to evaluate whether phenomena related to hand proximity are dependent on information relayed through the optic radiations. We presented target objects of different sizes to the blind fields of these gentlemen, and asked them to estimate target size with their right hand by adjusting thumb-finger distance or reaching and grasping the object. Concurrently, we varied the location of the resting left hand. In the hand-far condition, the left hand rested on their lap, and in the hand-near condition, it was placed just to the left of the target object. In the hand-far condition, both patients showed no scaling of either size-estimation aperture (SEA) or peak grip aperture (PGA) to object size. In the hand-near condition, however, both PGA and SEA were scaled to object size. Additional studies of MB suggest that hand proximity effects cannot be attributed solely to changes in spatial attention. These results imply that if bimodal cells are recruited when the hand is placed nearby the visual target, they must receive information from cortical areas that do not depend on the integrity of the optic radiations.

Motor force field learning influences visual processing of target motion.

There are reciprocal connections between visual and motor areas of the cerebral cortex. Although recent studies have provided intriguing new insights, in comparison with volume of research on the visual control of movement, relatively little is known about how movement influences vision. The motor system is perfectly suited to learn about environmental forces. Does environmental force information, learned by the motor system, influence visual processing? Here, we show that learning to compensate for a force applied to the hand influenced how participants predicted target motion for interception. Ss trained in one of three constant force fields by making reaching movements while holding a robotic manipulandum. The robot applied forces in a null [null force field (NFF)], leftward [leftward force field (LFF)], or [rightward force field (RFF)] direction. Training was followed immediately with an interception task. The target accelerated from left to right and Ss's task was to stab it. When viewing time was optimal for prediction, the RFF group initiated their responses earlier and hit more targets, and the LFF group initiated their responses later and hit fewer targets, than the NFF group. In follow-up experiments, we show that motor learning is necessary, and we rule out the possibility that explicit force direction information drives how Ss altered their predictions of visual motion. Environmental force information, acquired by motor learning, influenced how the motion of nearby visual targets was predicted.

Peripheral vision for perception and action.

Anatomical and physiological evidence suggests that vision-for-perception and vision-for-action may be differently sensitive to increasingly peripheral stimuli, and to stimuli in the upper and lower visual fields (VF). We asked participants to fixate one of 24 randomly presented LED arranged radially in eight directions and at three eccentricities around a central target location. One of two (small, large) target objects was presented briefly, and participants responded in two ways. For the action task, they reached for and grasped the target. For the perception task, they estimated target height by adjusting thumb-finger separation. In a final set of trials for each task, participants knew that target size would remain constant. We found that peak aperture increased with eccentricity for grasping, but not for perceptual estimations of size. In addition, peak grip aperture, but not size-estimation aperture, was more variable when targets were viewed in the upper as opposed to the lower VF. A second experiment demonstrated that prior knowledge about object size significantly reduced the variability of perceptual estimates, but had no effect on the variability of grip aperture. Overall, these results support the claim that peripheral VF stimuli are processed differently for perception and action. Moreover, they support the idea that the lower VF is specialized for the control of manual prehension. Finally, the effect of prior knowledge about target size on performance substantiates claims that perception is more tightly linked to memory systems than action.

Limb position drift: implications for control of posture and movement.

In the absence of visual feedback, subject reports of hand location tend to drift over time. Such drift has been attributed to a gradual reduction in the usefulness of proprioception to signal limb position. If this account is correct, drift should degrade the accuracy of movement distance and direction over a series of movements made without visual feedback. To test this hypothesis, we asked participants to perform six series of 75 repetitive movements from a visible start location to a visible target, in time with a regular, audible tone. Fingertip position feedback was given by a cursor during the first five trials in the series. Feedback was then removed, and participants were to continue on pace for the next 70 trials. Movements were made in two directions (30 degrees and 120 degrees ) from each of three start locations (initial shoulder angles of 30 degrees, 40 degrees, 50 degrees, and initial elbow angles of 90 degrees ). Over the 70 trials, the start location of each movement drifted, on average, 8 cm away from the initial start location. This drift varied systematically with movement direction, indicating that drift is related to movement production. However, despite these dramatic changes in hand position and joint configuration, movement distance and direction remained relatively constant. Inverse dynamics analysis revealed that movement preservation was accompanied by substantial modification of joint muscle torque. These results suggest that proprioception continues to be a reliable source of limb position information after prolonged time without vision, but that this information is used differently for maintaining limb position and for specifying movement trajectory.

Movement speed effects on limb position drift.

Previous research has shown that even when limb position drifts considerably during continuous blind performance, the topological and metrical properties of generated hand paths remain remarkably invariant. We tested two possible accounts of this intriguing effect. According to one hypothesis, position drift is due to degradation of limb-position information. This hypothesis predicted that drift of static hand positions at movement reversals should not depend on movement speed. According to the other hypothesis, position drift is due to degradation of movement information. This hypothesis predicted that drift of static hand positions at movement reversals should vary with movement speed. We tested these two hypotheses by varying the required movement speed when normal human adults performed back-and-forth manual positioning movements in the absence of visual feedback. Movement distance and direction were well preserved even though hand positions between movements drifted considerably. In accord with the movement error hypothesis, but not in accord with the position hypothesis, the rate at which hand positions drifted depended on movement speed. The data are consistent with the idea that hand position, which defines the origin of the trajectory control coordinate system, and movement trajectory are controlled by distinct neural mechanisms.