Martha Flanders

Early stages in a sensorimotor transformation

We present a model for several early stages of the sensorimotor transformations involved in targeted arm movement. In psychophysical experiments, human subjects pointed to the remembered locations of randomly placed targets in three-dimensional space. They made consistent errors in distance, and from these errors stages in the sensorimotor transformation were deduced. When subjects attempted to move the right index finger to a virtual target they consistently undershot the distance of the more distal targets. Other experiments indicated that the error was in the sensorimotor transformation rather than in the perception of distance. The error was most consistent when evaluated using a spherical coordinate system based at the right shoulder, indicating that the neural representation of target parameters is transformed from a retinocentric representation to a shoulder-centered representation. According to the model, the error in distance results from the neural implementation of a linear approximation in the algorithm to transform shoulder-centered target parameters into a set of arm orientations appropriate for placing the finger on the target. The transformation to final arm orientations places visually derived information into a frame of reference where it can readily be combined with kinesthetically derived information about initial arm orientations. The combination of these representations of initial and final arm orientations could give rise to the representation of movement direction recorded in the motor cortex by Georgopoulos and his colleagues. Later stages, such as the transformation from kinematic (position) to dynamic (force) parameters, or to levels of muscle activation, are beyond the scope of the present model.

Anticipatory and sequential motor control in piano playing

Pianists were asked to play short excerpts from several pieces on an electronic keyboard. In each piece, there were two phrases whose first few notes were played identically with the right hand. Thereafter, the two phrases were played differently. The aim of the investigation was to ascertain whether or not hand and finger kinematics diverged prior to the depression of the last common note. Such a divergence would imply an anticipatory modification of sequential movements of the hand, akin to the phenomenon of coarticulation in speech. The lack of such a divergence would imply a strictly serial organization of movement sequences with one hand, as was found previously to be the case for typing. The time at which each key was depressed and released and the speed with which the key was depressed was recorded via a MIDI interface to a laboratory computer. The motion of the right wrist and of the fingers of the right hand was recorded optoelectronically. Piano playing can invoke anticipatory modifications of hand and finger kinematics. The time at which two patterns of movements diverged varied considerably from piece to piece. Playing an ascending scale with the requirement of a “thumb-under” maneuver could evoke an anticipatory modification as much as 500 ms in advance of the last common note. In another piece, keypresses appeared to be executed in a strict serial ordering and a third piece gave results intermediate between these two extremes. We interpret the results to suggest that a strict serial execution of a movement sequence is favored as long as this is compatible with the demands of the task.

Sensory control of target acquisition

Recent research has expanded our understanding of how the nervous system uses visual and kinesthetic input to move the arm to a target. In this review, we present data to show how the nervous system can rapidly use sensory input to control impending or ongoing motor activity. We contrast visual control with kinesthetic control to show how these two sources of sensory input are used to control parameters of motor command such as amplitude and direction, to trigger the motor commands, and then to correct errors in trajectory. Despite many differences in the organization of the visual and the kinesthetic sensory systems, the nervous system appears to process these two types of sensory input similarly.

Flexibility and Repeatability of Finger Movements During Typing: Analysis of Multiple Degrees of Freedom

The kinematics of the hand and fingers were studied during various keystrokes in typing. These movements were defined by 17 degrees of freedom of motion, and methods were developed to identify simplifying strategies inthe execution of the task. Most of the analysis was restrictedto the 11 degrees of freedom of the fingers, neglecting thumband wrist motion. Temporal characteristics of the motion weredefined by computing principal components, and it was found thatonly a few (two to four) principal components were needed tocharacterize motion of each of the degrees of freedom.Hierarchical relationships among patterns within and betweendifferent degrees of freedom were identified using clusteranalysis. There was a considerable amount of consistency eachtime a given keystroke was executed by a subject, and thisrepeatability may imply a reduction in the number of degrees offreedom independently controlled by the nervous system. However,there also appears to be considerable flexibility in thecoordination of the many joints of the hand when examined acrossdifferent keys and across different subjects.

Basic features of phasic activation for reaching in vertical planes

The purpose of this study was to fully characterize the timing and intensity of the phasic portion of the electromyographic (EMG) waveform for reaching movements in vertical planes. Electromyographic activity was simultaneously recorded from nine superficial elbow and/or shoulder muscles while human subjects made rapid arm movements. Hand paths comprised 20 directions in a sagittal plane and 20 directions in a frontal plane. In order to focus on the more phasic aspects of muscle activation, estimates of postural EMG activity were subtracted from the EMG traces recorded during rapid reaches. These postural estimates were obtained from activity recorded during very slow reaches to the same targets. After subtraction of this postural activity, agonist or antagonist burst patterns were often observed in the phasic EMG traces. For nearly all muscles and all subjects, the relation between phasic EMG intensity and movement direction was a function with multiple peaks. For all muscles, the timing of phasic EMG bursts varied as a function of movement direction: the data from each muscle exhibited a gradual temporal shift of activity over a certain range of directions. This gradual temporal shift has no obvious correspondence to the mechanical requirements of the task and might represent a neuromuscular control strategy in which burst timing contributes to the specification of movement direction.

Coarticulation in Fluent Fingerspelling

In speech, the phenomenon of coarticulation (differentiation of phoneme production depending on the preceding or following phonemes) suggests an organization of movement sequences that is not strictly serial. In the skeletal motor system, however, evidence for comparable fluency has been lacking. Thus the present study was designed to quantify coarticulation in the hand movement sequences of sign language interpreters engaged in fingerspelling. Records of 17 measured joint angles were subjected to discriminant and correlation analyses to determine to what extent and in what manner the hand shape for a particular letter was influenced by the hand shapes for the preceding or the following letters. Substantial evidence of coarticulation was found, revealing both forward and reverse influences across letters. These influences could be further categorized as assimilation (tending to reduce the differences between sequential hand shapes) or dissimilation (tending to emphasize the differences between sequential hand shapes). The proximal interphalangeal (PIP) joints of the index and middle fingers tended to show dissimilation, whereas at the same time (i.e., during the spelling of the same letters) the joints of the wrist and thumb tended to show assimilation. The index and middle finger PIP joints have been shown previously to be among the most important joints for computer recognition of the 26 letter shapes, and therefore the dissimilation may have served to enhance visual discrimination. The simultaneous occurrence of dissimilation in some joints and assimilation in others demonstrates an unprecedented level of parallel control of individual joint rotations in an essentially serial task.

Directional Tuning of Single Motor Units

The directional activity of whole muscles has been shown to be broadly and often multimodally tuned, raising the question of how this tuning is subserved at the level of single motor units (SMUs). Previously defined rules of SMU activation would predict that units of the same muscle (or at least of the same neuromuscular compartment) are activated homogeneously with activity peaks in the same “best” direction(s). In the present study, the best directions of SMUs in human biceps (both heads) and deltoid (anterior, medial, and posterior portions) were determined by measuring the firing rate and threshold force of units for recruitment during isometric force ramps in many different directions. For all muscles studied, neighboring motor units could have significantly different best directions, suggesting that each muscle receives multiple directional commands. Furthermore, 17% of the units sampled clearly had a second-best direction, consistent with a convergence of different directional commands onto the same motoneuron. The best directions of the units changed gradually with location in the muscle. Best directions did not cluster into separate groups, thus, not supporting the existence of clearly distinguished neuromuscular compartments. Instead, the results reveal a more gradually distributed activation of the biceps and deltoid motoneuron pools. A model is proposed in which the central control mechanism optimizes the fulfillment of the continuously changing directional force requirements of a movement by gradually recruiting and derecruiting those units ideally suited for the production of the required force vector at any given time.

Reaching beyond reach

Abstract The analysis of errors in two-joint reaching movements has provided clues about sensorimotor processing algorithms. The present study extends this focus to situations where the head, trunk, and legs join with the arm to help reach targets placed slightly beyond arm’s length. Subjects reached accurately to touch ”real targets” or reached to the remembered locations of ”virtual targets” (i.e., targets removed at the start of the reach). Subjects made large errors in the virtual-target condition and these errors were analyzed with the aim of revealing the implications for whole-body coordination. Subjects were found to rotate the head less in the virtual-target condition (when compared with accurate movements to real targets). This resulted in a more limited range of head postures, and the final head angles at the end of the movements were geometrically related to the incorrect hand locations, perhaps accounting for some portion of the errors. This suggests that head-eye-hand coordination plays an important role in the organization of these movements and leads to the hypothesis that a representation of current gaze direction may serve as a reference signal for arm motor control.

Hand kinematics of piano playing.

Dexterous use of the hand represents a sophisticated sensorimotor function. In behaviors such as playing the piano, it can involve strong temporal and spatial constraints. The purpose of this study was to determine fundamental patterns of covariation of motion across joints and digits of the human hand. Joint motion was recorded while 5 expert pianists played 30 excerpts from musical pieces, which featured ∼50 different tone sequences and fingering. Principal component analysis and cluster analysis using an expectation-maximization algorithm revealed that joint velocities could be categorized into several patterns, which help to simplify the description of the movements of the multiple degrees of freedom of the hand. For the thumb keystroke, two distinct patterns of joint movement covariation emerged and they depended on the spatiotemporal patterns of the task. For example, the thumb-under maneuver was clearly separated into two clusters based on the direction of hand translation along the keyboard. While the pattern of the thumb joint velocities differed between these clusters, the motions at the metacarpo-phalangeal and proximal-phalangeal joints of the four fingers were more consistent. For a keystroke executed with one of the fingers, there were three distinct patterns of joint rotations, across which motion at the striking finger was fairly consistent, but motion of the other fingers was more variable. Furthermore, the amount of movement spillover of the striking finger to the adjacent fingers was small irrespective of the finger used for the keystroke. These findings describe an unparalleled amount of independent motion of the fingers.

Biological constraints simplify the recognition of hand shapes

This study sought to identify constraints that might lead to a concise system of recognizing fingerspelling hand shapes. Previous studies of grasping suggested that hand shape is controlled using combinations of a small number of neuromuscular synergies, but fingerspelling shapes appear to be more highly individuated and, therefore, might require a larger number of degrees of freedom. Static hand postures of the American Sign Language manual alphabet were recorded by measuring 17 joint angles. Principal components (PCs) analysis was compared to the use of subsets of individual variables (i.e., joint angles) for reduction in degrees of freedom. The first four PCs were similar across subjects. Classification using weightings from these four components was 86.6% accurate, while classification using four individual variables was 88.5% accurate (thumb abduction, as well as flexion at the index and middle finger proximal interphalangeal joints and the ring finger metacarpalphalangeal joint). When chosen for each subject, particular four-variable subsets yielded correct rates above 95%. This superior performance of variable subsets over PC weighting vectors suggests that the reduction in degrees of freedom is due to biomechanical and neuromuscular constraints rather than synergistic control. Thus, in future application to dynamic fingerspelling, reasonable recognition accuracy might be achieved with a significant reduction in both computational and measured degrees of freedom.