The Influence of Dopaminergic Striatal Innervation on Upper Limb Locomotor Synergies

To determine the role of striatal dopaminergic innervation on upper limb synergies during walking, we measured arm kinematics in 13 subjects with Parkinson disease. Patients were recruited according to several inclusion criteria to represent the best possible in vivo model of dopaminergic denervation. Of relevance, we included only subjects with normal spatio-temporal parameters of the stride and gait speed to avoid an impairment of upper limbs locomotor synergies as a consequence of gait impairment per se. Dopaminergic innervation of the striatum was measured by FP-CIT and SPECT. All patients showed a reduction of gait-associated arms movement. No linear correlation was found between arm ROM reduction and contralateral dopaminergic putaminal innervation loss. Still, a partition analysis revealed a 80% chance of reduced arm ROM when putaminal dopamine content loss was >47%. A significant correlation was described between the asymmetry indices of the swinging of the two arms and dopaminergic striatal innervation. When arm ROM was reduced, we found a positive correlation between upper-lower limb phase shift modulation (at different gait velocities) and striatal dopaminergic innervation. These findings are preliminary evidence that dopaminergic striatal tone plays a modulatory role in upper-limb locomotor synergies and upper-lower limb coupling while walking at different velocities.     

Use of Self-Selected Postures to Regulate Multi-Joint Stiffness During Unconstrained Tasks

Background

The human motor system is highly redundant, having more kinematic degrees of freedom than necessary to complete a given task. Understanding how kinematic redundancies are utilized in different tasks remains a fundamental question in motor control. One possibility is that they can be used to tune the mechanical properties of a limb to the specific requirements of a task. For example, many tasks such as tool usage compromise arm stability along specific directions. These tasks only can be completed if the nervous system adapts the mechanical properties of the arm such that the arm, coupled to the tool, remains stable. The purpose of this study was to determine if posture selection is a critical component of endpoint stiffness regulation during unconstrained tasks.

Methodology/Principal Findings

Three-dimensional (3D) estimates of endpoint stiffness were used to quantify limb mechanics. Most previous studies examining endpoint stiffness adaptation were completed in 2D using constrained postures to maintain a non-redundant mapping between joint angles and hand location. Our hypothesis was that during unconstrained conditions, subjects would select arm postures that matched endpoint stiffness to the functional requirements of the task. The hypothesis was tested during endpoint tracking tasks in which subjects interacted with unstable haptic environments, simulated using a 3D robotic manipulator. We found that arm posture had a significant effect on endpoint tracking accuracy and that subjects selected postures that improved tracking performance. For environments in which arm posture had a large effect on tracking accuracy, the self-selected postures oriented the direction of maximal endpoint stiffness towards the direction of the unstable haptic environment.

Conclusions/Significance

These results demonstrate how changes in arm posture can have a dramatic effect on task performance and suggest that postural selection is a fundamental mechanism by which kinematic redundancies can be exploited to regulate arm stiffness in unconstrained tasks.     

Functional muscle synergies constrain force production during postural tasks

We recently demonstrated that a set of five functional muscle synergies were sufficient to characterize both hindlimb muscle activity and active forces during automatic postural responses in cats standing at multiple postural configurations. This characterization depended critically upon the assumption that the endpoint force vector (synergy force vector) produced by the activation of each muscle synergy rotated with the limb axis as the hindlimb posture varied in the sagittal plane. Here, we used a detailed, 3D static model of the hindlimb to confirm that this assumption is biomechanically plausible: as we varied the model posture, simulated synergy force vectors rotated monotonically with the limb axis in the parasagittal plane (r2=0.94+/-0.08). We then tested whether a neural strategy of using these five functional muscle synergies provides the same force-generating capability as controlling each of the 31 muscles individually. We compared feasible force sets (FFSs) from the model with and without a muscle synergy organization. FFS volumes were significantly reduced with the muscle synergy organization (F=1556.01, p<0.01), and as posture varied, the synergy-limited FFSs changed in shape, consistent with changes in experimentally measured active forces. In contrast, nominal FFS shapes were invariant with posture, reinforcing prior findings that postural forces cannot be predicted by hindlimb biomechanics alone. We propose that an internal model for postural force generation may coordinate functional muscle synergies that are invariant in intrinsic limb coordinates, and this reduced-dimension control scheme reduces the set of forces available for postural control.     

Coordinate Representations for Interference Reduction in Motor Learning

When opposing force fields are presented alternately or randomly across trials for identical reaching movements, subjects learn neither force field, a behavior termed ‘interference’. Studies have shown that a small difference in the endpoint posture of the limb reduces this interference. However, any difference in the limb’s endpoint location typically changes the hand position, joint angles and the hand orientation making it ambiguous as to which of these changes underlies the ability to learn dynamics that normally interfere. Here we examine the extent to which each of these three possible coordinate systems—Cartesian hand position, shoulder and elbow joint angles, or hand orientation—underlies the reduction in interference. Subjects performed goal-directed reaching movements in five different limb configurations designed so that different pairs of these configurations involved a change in only one coordinate system. By specifically assigning clockwise and counter-clockwise force fields to the configurations we could create three different conditions in which the direction of the force field could only be uniquely distinguished in one of the three coordinate systems. We examined the ability to learn the two fields based on each of the coordinate systems. The largest reduction of interference was observed when the field direction was linked to the hand orientation with smaller reductions in the other two conditions. This result demonstrates that the strongest reduction in interference occurred with changes in the hand orientation, suggesting that hand orientation may have a privileged role in reducing motor interference for changes in the endpoint posture of the limb.     

Residual Upper Arm Motor Function Primes Innervation of Paretic Forearm Muscles in Chronic Stroke after Brain-Machine Interface (BMI) Training

Background

Abnormal upper arm-forearm muscle synergies after stroke are poorly understood. We investigated whether upper arm function primes paralyzed forearm muscles in chronic stroke patients after Brain-Machine Interface (BMI)-based rehabilitation. Shaping upper arm-forearm muscle synergies may support individualized motor rehabilitation strategies.

Methods

Thirty-two chronic stroke patients with no active finger extensions were randomly assigned to experimental or sham groups and underwent daily BMI training followed by physiotherapy during four weeks. BMI sessions included desynchronization of ipsilesional brain activity and a robotic orthosis to move the paretic limb (experimental group, n = 16). In the sham group (n = 16) orthosis movements were random. Motor function was evaluated with electromyography (EMG) of forearm extensors, and upper arm and hand Fugl-Meyer assessment (FMA) scores. Patients performed distinct upper arm (e.g., shoulder flexion) and hand movements (finger extensions). Forearm EMG activity significantly higher during upper arm movements as compared to finger extensions was considered facilitation of forearm EMG activity. Intraclass correlation coefficient (ICC) was used to test inter-session reliability of facilitation of forearm EMG activity.

Results

Facilitation of forearm EMG activity ICC ranges from 0.52 to 0.83, indicating fair to high reliability before intervention in both limbs. Facilitation of forearm muscles is higher in the paretic as compared to the healthy limb (p<0.001). Upper arm FMA scores predict facilitation of forearm muscles after intervention in both groups (significant correlations ranged from R = 0.752, p = 0.002 to R = 0.779, p = 0.001), but only in the experimental group upper arm FMA scores predict changes in facilitation of forearm muscles after intervention (R = 0.709, p = 0.002; R = 0.827, p<0.001).

Conclusions

Residual upper arm motor function primes recruitment of paralyzed forearm muscles in chronic stroke patients and predicts changes in their recruitment after BMI training. This study suggests that changes in upper arm-forearm synergies contribute to stroke motor recovery, and provides candidacy guidelines for similar BMI-based clinical practice.     

Maintaining Homeostasis by Decision-Making

Living organisms need to maintain energetic homeostasis. For many species, this implies taking actions with delayed consequences. For example, humans may have to decide between foraging for high-calorie but hard-to-get, and low-calorie but easy-to-get food, under threat of starvation. Homeostatic principles prescribe decisions that maximize the probability of sustaining appropriate energy levels across the entire foraging trajectory. Here, predictions from biological principles contrast with predictions from economic decision-making models based on maximizing the utility of the endpoint outcome of a choice. To empirically arbitrate between the predictions of biological and economic models for individual human decision-making, we devised a virtual foraging task in which players chose repeatedly between two foraging environments, lost energy by the passage of time, and gained energy probabilistically according to the statistics of the environment they chose. Reaching zero energy was framed as starvation. We used the mathematics of random walks to derive endpoint outcome distributions of the choices. This also furnished equivalent lotteries, presented in a purely economic, casino-like frame, in which starvation corresponded to winning nothing. Bayesian model comparison showed that—in both the foraging and the casino frames—participants’ choices depended jointly on the probability of starvation and the expected endpoint value of the outcome, but could not be explained by economic models based on combinations of statistical moments or on rank-dependent utility. This implies that under precisely defined constraints biological principles are better suited to explain human decision-making than economic models based on endpoint utility maximization.     

Barrels XII - Proceedings

Spinalized frogs were microstimulated in the intermediate grey layers of the lumbar spinal cord; the forces evoked in the hindlimb were measured at several limb positions. The data were expressed as force fields. After the collection of many force fields, the dorsal roots were cut with the stimulating electrode in place, and the position-dependent stimulation-evoked forces were again measured repeatedly. We found that the position-dependent pattern of evoked forces—the force fields—did not change after the dorsal roots were cut. In other words, the postcut evoked forces pointed in the same direction as the precut evoked forces. This result was predicted and confirmed by the muscle activations (EMGs): Before and after the dorsal roots were cut, the same muscles were activated in the same proportions. In all limb positions, the rank ordering of the muscle activations remained fixed. The stimulation needed to evoke forces was increased by deafferentation, and there were subtle changes in the force magnitudes that were consistent with a linearization of the muscle stiffness by the afferents. We conclude that the microstimulation activated specific muscle synergies that resulted in limb forces pointing toward a particular posture. The patterns of evoked forces were predominantly attributable to feedforward activation of these muscle synergies.     

Challenges and new approaches to proving the existence of muscle synergies of neural origin

Muscle coordination studies repeatedly show low-dimensionality of muscle activations for a wide variety of motor tasks. The basis vectors of this low-dimensional subspace, termed muscle synergies, are hypothesized to reflect neurally-established functional muscle groupings that simplify body control. However, the muscle synergy hypothesis has been notoriously difficult to prove or falsify. We use cadaveric experiments and computational models to perform a crucial thought experiment and develop an alternative explanation of how muscle synergies could be observed without the nervous system having controlled muscles in groups. We first show that the biomechanics of the limb constrains musculotendon length changes to a low-dimensional subspace across all possible movement directions. We then show that a modest assumption--that each muscle is independently instructed to resist length change--leads to the result that electromyographic (EMG) synergies will arise without the need to conclude that they are a product of neural coupling among muscles. Finally, we show that there are dimensionality-reducing constraints in the isometric production of force in a variety of directions, but that these constraints are more easily controlled for, suggesting new experimental directions. These counter-examples to current thinking clearly show how experimenters could adequately control for the constraints described here when designing experiments to test for muscle synergies--but, to the best of our knowledge, this has not yet been done.     

Impedance characteristics of a neuromusculoskeletal model of the human arm I. Posture control

The mechanical impedance of neuromusculoskeletal models of the human arm is studied in this paper. The model analysis provides a better understanding of the contributions of possible intrinsic and reflexive components of arm impedance, makes clear the limitations of second-order mass-viscosity-stiffness models and reveals possible task effects on the impedance. The musculoskeletal model describes planar movements of the upper arm and forearm, which are moved by six lumped muscles with nonlinear dynamics. The motor control system is represented by a neural network which combines feedforward and feedback control. It is optimized for the control of movements or for posture control in the presence of external forces. The achieved impedance characteristics depend on the conditions during the learning process. In particular, the impedance is adapted in a suitable way to the frequency content and direction of external forces acting on the hand during an isometric task. The impedance characteristics of a model, which is optimized for movement control, are similar to experimental data in the literature. The achieved stiffness is, to a large extent, reflexively determined whereas the approximated viscosity is primarily due to intrinsic attributes. It is argued that usually applied Hill-type muscle models do not properly represent intrinsic muscle stiffness. Received: 14 October 1997 / Accepted in revised form: 18 May 1999     

Transcranial Direct Current Stimulation Improves Ipsilateral Selective Muscle Activation in a Frequency Dependent Manner

Failure to suppress antagonist muscles can lead to movement dysfunction, such as the abnormal muscle synergies often seen in the upper limb after stroke. A neurophysiological surrogate of upper limb synergies, the selectivity ratio (SR), can be determined from the ratio of biceps brachii (BB) motor evoked potentials to transcranial magnetic stimulation prior to forearm pronation versus elbow flexion. Surprisingly, cathodal transcranial direct current stimulation (c-TDCS) over ipsilateral primary motor cortex (M1) reduces (i.e. improves) the SR in healthy adults, and chronic stroke patients. The ability to suppress antagonist muscles may be exacerbated at high movement rates. The aim of the present study was to investigate whether the selective muscle activation of the biceps brachii (BB) is dependent on altering frequency demands, and whether the c-tDCS improvement of SR is dependent on task frequency. Seventeen healthy participants performed repetitive isometric elbow flexion and forearm pronation at three rates, before and after c-tDCS or sham delivered to ipsilateral left M1. Ipsilateral c-tDCS improved the SR in a frequency dependent manner by selectively suppressing BB antagonist excitability. Our findings confirm that c-tDCS is an effective tool for improving selective muscle activation, and provide novel evidence for its efficacy at rates of movement where it is most likely to benefit task performance.     

Beyond Muscles Stiffness: Importance of State-Estimation to Account for Very Fast Motor Corrections

Feedback delays are a major challenge for any controlled process, and yet we are able to easily control limb movements with speed and grace. A popular hypothesis suggests that the brain largely mitigates the impact of feedback delays (∼50 ms) by regulating the limb intrinsic visco-elastic properties (or impedance) with muscle co-contraction, which generates forces proportional to changes in joint angle and velocity with zero delay. Although attractive, this hypothesis is often based on estimates of limb impedance that include neural feedback, and therefore describe the entire motor system. In addition, this approach does not systematically take into account that muscles exhibit high intrinsic impedance only for small perturbations (short-range impedance). As a consequence, it remains unclear how the nervous system handles large perturbations, as well as disturbances encountered during movement when short-range impedance cannot contribute. We address this issue by comparing feedback responses to load pulses applied to the elbow of human subjects with theoretical simulations. After validating the model parameters, we show that the ability of humans to generate fast and accurate corrective movements is compatible with a control strategy based on state estimation. We also highlight the merits of delay-uncompensated robust control, which can mitigate the impact of internal model errors, but at the cost of slowing feedback corrections. We speculate that the puzzling observation of presynaptic inhibition of peripheral afferents in the spinal cord at movement onset helps to counter the destabilizing transition from high muscle impedance during posture to low muscle impedance during movement.     

Limb Dominance Results from Asymmetries in Predictive and Impedance Control Mechanisms

Handedness is a pronounced feature of human motor behavior, yet the underlying neural mechanisms remain unclear. We hypothesize that motor lateralization results from asymmetries in predictive control of task dynamics and in control of limb impedance. To test this hypothesis, we present an experiment with two different force field environments, a field with a predictable magnitude that varies with the square of velocity, and a field with a less predictable magnitude that varies linearly with velocity. These fields were designed to be compatible with controllers that are specialized in predicting limb and task dynamics, and modulating position and velocity dependent impedance, respectively. Because the velocity square field does not change the form of the equations of motion for the reaching arm, we reasoned that a forward dynamic-type controller should perform well in this field, while control of linear damping and stiffness terms should be less effective. In contrast, the unpredictable linear field should be most compatible with impedance control, but incompatible with predictive dynamics control. We measured steady state final position accuracy and 3 trajectory features during exposure to these fields: Mean squared jerk, Straightness, and Movement time. Our results confirmed that each arm made straighter, smoother, and quicker movements in its compatible field. Both arms showed similar final position accuracies, which were achieved using more extensive corrective sub-movements when either arm performed in its incompatible field. Finally, each arm showed limited adaptation to its incompatible field. Analysis of the dependence of trajectory errors on field magnitude suggested that dominant arm adaptation occurred by prediction of the mean field, thus exploiting predictive mechanisms for adaptation to the unpredictable field. Overall, our results support the hypothesis that motor lateralization reflects asymmetries in specific motor control mechanisms associated with predictive control of limb and task dynamics, and modulation of limb impedance.     

Influence of locomotion speed on biomechanical subtask and muscle synergy

This paper investigates the relationship of biomechanical subtasks, and muscle synergies with various locomotion speeds. Ground reaction force (GRF) of eight healthy subjects is measured synchronously by force plates of treadmill at five different speeds ranging from 0.5 m/s to 1.5 m/s. Four basic biomechanical subtasks, body support, propulsion, swing, and heel strike preparation, are identified according to GRF. Meanwhile, electromyography (EMG) data, used to extract muscle synergies, are collected from lower limb muscles. EMG signals are segmented periodically based on GRF with the heel strike as the split points. Variability accounted for (VAF) is applied to determine the number of muscle synergies. We find that four muscle synergies can be extracted in all five situations by non-negative matrix factorization (NMF). Furthermore, the four muscle synergies and biomechanical subtasks keep invariant as the walking speed changes.     

Representation of movements and muscles within the primate precentral motor cortex: historical and current perspectives

A major problem with the study of the control of movement and posture is to determine how specific brain areas contribute to the selection of those particular muscle patterns that underlie a coordinated movement. With this problem in mind, a selective review is presented of mapping studies of the primate motor cortex, whose results bear on the question of how the spatial organization of cortical efferent cells might contribute to the production of organized muscle synergies. More recent findings are also summarized, which appear to resolve previous controversies on the question of whether movements or muscles are the primary units of motor cortex organization. These same findings suggest also a form of spatial organization within the primate precentral gyrus that would allow spatially simple afferent inputs to evoke the muscle synergies that are necessary for a variety of simple movements of the arm and hand.     

Reduction of neuromuscular redundancy for postural force generation using an intrinsic stability criterion

Postural control requires the coordination of multiple muscles to achieve both endpoint force production and postural stability. Multiple muscle activation patterns can produce the required force for standing, but the mechanical stability associated with any given pattern may vary, and has implications for the degree of delayed neural feedback necessary for postural stability. We hypothesized that muscular redundancy is reduced when muscle activation patterns are chosen with respect to intrinsic musculoskeletal stability as well as endpoint force production. We used a three-dimensional musculoskeletal model of the cat hindlimb with 31 muscles to determine the possible contributions of intrinsic muscle properties to limb stability during isometric force generation. Using dynamic stability analysis we demonstrate that within the large set of activation patterns that satisfy the force requirement for posture, only a reduced subset produce a mechanically stable limb configuration. Greater stability in the frontal-plane suggests that neural control mechanisms are more highly active for sagittal-plane and for ankle joint control. Even when the limb was unstable, the time-constants of instability were sufficiently great to allow long-latency neural feedback mechanisms to intervene, which may be preferential for movements requiring maneuverability versus stability. Local joint stiffness of muscles was determined by the stabilizing or destabilizing effects of moment-arm versus joint angle relationships. By preferentially activating muscles with high local stiffness, muscle activation patterns with feedforward stabilizing properties could be selected. Such a strategy may increase intrinsic postural stability without co-contraction, and may be useful criteria in the force-sharing problem.     

Constraints and variation in food web link-species space

Predicting food web structure in future climates is a pressing goal of ecology. These predictions may be impossible without a solid understanding of the factors that structure current food webs. The most fundamental aspect of food web structure—the relationship between the number of links and species—is still poorly understood. Some species interactions may be physically or physiologically ‘forbidden''—like consumption by non-consumer species—with possible consequences for food web structure. We show that accounting for these ‘forbidden interactions'' constrains the feasible link-species space, in tight agreement with empirical data. Rather than following one particular scaling relationship, food webs are distributed throughout this space according to shared biotic and abiotic features. Our study provides new insights into the long-standing question of which factors determine this fundamental aspect of food web structure.     

Impedance imaging in upper arm fractures

We used the Aberdeen impedance imaging system to drive a constant current of 1 mA on a 10 kHz sine wave into the upper arm encircled by an elastic belt of 16 equi-spaced strip electrodes. The system was used to examine a normal upper arm, an upper arm with a recent humeral fracture and an upper arm with a clinically united fracture. We approximated the human upper arm to a circular cylinder and assumed bilateral symmetry of normal human limbs. We measured transverse limb resistivity ratios and reconstructed static two-dimensional images of the spatial distribution of log(resistivity) by the equipotential back projection technique using a homogeneous muscle equivalent saline reference. Our results indicate that impedance osteography provides unique information about the changing electrical characteristics at the fracture site. This information could prove a useful adjunct to clinical and radiological tests for fracture union.     

Local Adaptation of Bitter Taste and Ecological Speciation in a Wild Mammal

Sensory systems are attractive evolutionary models to address how organisms adapt to local environments that can cause ecological speciation. However, tests of these evolutionary models have focused on visual, auditory, and olfactory senses. Here, we show local adaptation of bitter taste receptor genes in two neighboring populations of a wild mammal—the blind mole rat Spalax galili—that show ecological speciation in divergent soil environments. We found that basalt-type bitter receptors showed higher response intensity and sensitivity compared with chalk-type ones using both genetic and cell-based functional analyses. Such functional changes could help animals adapted to basalt soil select plants with less bitterness from diverse local foods, whereas a weaker reception to bitter taste may allow consumption of a greater range of plants for animals inhabiting chalk soil with a scarcity of food supply. Our study shows divergent selection on food resources through local adaptation of bitter receptors, and suggests that taste plays an important yet underappreciated role in speciation.     

Preventing Zika Virus Infection during Pregnancy Using a Seasonal Window of Opportunity for Conception

It has come to light that Zika virus (ZIKV) infection during pregnancy can result in trans-placental transmission to the fetus along with fetal death, congenital microcephaly, and/or Central Nervous System (CNS) malformations. There are projected to be >9,200,000 births annually in countries with ongoing ZIKV transmission. In response to the ZIKV threat, the World Health Organization (WHO) is strategically targeting prevention of infection in pregnant women and funding contraception in epidemic regions. I propose that the damaging effects of ZIKV can be reduced using a seasonal window of opportunity for conception that may minimize maternal exposure. Like other acute viral infections—including the related flavivirus, dengue virus (DENV)—the transmission of ZIKV is anticipated to be seasonal. By seasonally planning pregnancy, this aspect of pathogen ecology can be leveraged to align sensitive periods of gestation with the low-transmission season.     

Optimal Workloop Energetics of Muscle-Actuated Systems: An Impedance Matching View

Integrative approaches to studying the coupled dynamics of skeletal muscles with their loads while under neural control have focused largely on questions pertaining to the postural and dynamical stability of animals and humans. Prior studies have focused on how the central nervous system actively modulates muscle mechanical impedance to generate and stabilize motion and posture. However, the question of whether muscle impedance properties can be neurally modulated to create favorable mechanical energetics, particularly in the context of periodic tasks, remains open. Through muscle stiffness tuning, we hypothesize that a pair of antagonist muscles acting against a common load may produce significantly more power synergistically than individually when impedance matching conditions are met between muscle and load. Since neurally modulated muscle stiffness contributes to the coupled muscle-load stiffness, we further anticipate that power-optimal oscillation frequencies will occur at frequencies greater than the natural frequency of the load. These hypotheses were evaluated computationally by applying optimal control methods to a bilinear muscle model, and also evaluated through in vitro measurements on frog Plantaris longus muscles acting individually and in pairs upon a mass-spring-damper load. We find a 7-fold increase in mechanical power when antagonist muscles act synergistically compared to individually at a frequency higher than the load natural frequency. These observed behaviors are interpreted in the context of resonance tuning and the engineering notion of impedance matching. These findings suggest that the central nervous system can adopt strategies to harness inherent muscle impedance in relation to external loads to attain favorable mechanical energetics.