A robotic model to investigate human motor control

The role of the mechanical properties of the neuromuscular system in motor control has been investigated for a long time in both human and animal subjects, mainly through the application of mechanical perturbations to the limb during natural movements and the observation of its corrective responses. These methods have provided a wealth of insight into how the central nervous system controls the limb. They suffer, however, from the fact that it is almost impossible to separate the active and passive components of the measured arm stiffness and that the measurement may themselves alter the stiffness characteristic of the arm. As a complement to these analyses, the implementation of a given neuroscientific hypothesis on a real mechanical system could overcome these measurement artifact and provide a tool that is, under full control of the experimenter, able to replicate the relevant functional features of the human arm. In this article, we introduce the NEURARM platform, a robotic arm intended to test hypotheses on the human motor control system. As such, NEURARM satisfies two key requirements. First, its kinematic parameters and inertia are similar to that of the human arm. Second, NEURARM mimics the main physical features of the human actuation system, specifically, the use of tendons to transfer force, the presence of antagonistic muscle pairs, the passive elasticity of muscles in the absence of any neural feedback and the non-linear elastic behaviour. This article presents the design and characterization of the NEURARM actuation system. The resulting mechanical behaviour, which has been tested in joint and Cartesian space under static and dynamic conditions, proves that the NEURARM platform can be exploited as a robotic model of the human arm, and could thus represent a powerful tool for neuroscience investigations.     

RFID-enhanced multi-agent based control for a machining system

Recent research on highly distributed control methods for complex systems have produced a series of philosophies based on negotiation, that bring together process engineering with computer science. Among these control philosophies, the ones based on multi-agent systems (MAS) have become especially relevant. Furthermore, among a number of MAS implementations, those that use different types of agents at different conceptual/managerial levels are commonly applied. However, these MAS models have the drawback of an excessive dependence on up-to-date information about the products and other elements that move within the system. A new technology has come out that can help solve this problem: radio-frequency identification enhanced information management systems (RFID-IMS). One of these is Auto-ID/EPCglobal technology. This paper shows how a MAS model can be used for controlling a machining system incorporating RFID-IMS technology. The resulting system becomes an RFID-enhanced intelligent manufacturing system (RFID-IMS II).     

A model for the hierarchical structure of the human epidermal cornified cell envelope

The epidermal cornified cell envelope (CE) is a 15 nm thick layer of highly insoluble protein that is assembled on the intracellular surface of the cell membrane during terminal differentiation, and comprises about 10% of the mass of the cornified dead layers of the tissue. The CE consists of a complex amalgam of several known proteins that are crosslinked by isodipeptide bonds formed by the action of transglutaminases, but little is known about their order of accretion during CE assembly, or how they are crosslinked. In this paper, CEs purified from human foreskin epidermis were examined by immunogold electron microscopy before and after digestion with proteases.The mass fractions of the proteins remaining in CE remnants during digestion were estimated from the amino acid compositions by mathematical modelling. Together, the data support a new model for the complex hierachical structure of the CE. The cytoplasmic surface of intact purified CEs consists of filaggrin, loricrin, SPRs and keratin intermediate filaments. The bulk of the CE consists of a mixture of loricrin (75%) and SPRs (5%). Following removal of most of these, the novel protein elafin is exposed, which contributes about 6% of CE mass. The protein material on the inner CE 'core' adjacent or attached to the lipid envelope consists of cystatin alpha (5%), involucrin (2%), keratin filaments (3%) and possibly other as yet unidentified protein(s)(2-5%). This model supports but considerably extends an earlier extant hypotheis for CE structure, and thus provides the basis for further detailed biochemical and ultra-structural studies.     

Two-phase model of the basal ganglia: implications for discontinuous control of the motor system

In this article, I point out that simple one-phase models of the role of the basal ganglia in action selection have a problem. Furthermore, I suggest a solution with major implications for the organization of the action-selection and motor systems. In current models, the striatum evaluates multiple potential actions by adding biases based on previous conditioning. These biases may arise in both the direct (bias for) and indirect (bias against) pathways. Together, these biases influence which action is ultimately chosen. For efficient conditioning to occur, a positive outcome must selectively strengthen the striatal bias for the chosen action (via a dopaminergic mechanism). This is problematic, however, because all potential action choices have influenced firing patterns in striatal cells during the selection process; it is therefore unclear how the synapses that represent the chosen plan could be selectively strengthened. I suggest a simple solution in which the striatum has two functional phases. In the first phase, the basal ganglia provide biases for multiple potential actions (using both the direct and indirect pathways), leading to the choice of a single action in the cortex. In the second phase, an efference copy of the chosen action is sent to the striatum, where it contributes to the establishment of the eligibility trace for that action. This trace, when acted on by subsequent dopaminergic reinforcement, leads to specific strengthening of the bias only for the chosen action. Consistent with this model, recordings show post-choice imposition onto the striatum of signals corresponding to the chosen action. The existence of dual phases of basal ganglia function implies that decisions about action choice are sent to the motor system in a discontinuous manner. This would not be problematic if the motor system also operated discontinuously. I will review evidence suggesting that this is the case, notably that action is organized by approximately 10 Hz oscillations.     

Feed-forward control of a redundant motor system

We describe a model of feed-forward control of a redundant motor system and validate it using, as examples, tasks of multi-finger force production. The model assumes the existence of two input signals at an upper level of the control hierarchy, related and unrelated to a task variable. Knowledge of the Jacobian of the system is assumed at the level of generation of elemental variables (variables at the level of effectors). Variance at the level of elemental variables is considered as the sum of two components, related and unrelated to variability in the task variable. An index of stabilization of the task variable is similarly introduced as to how it was done in several studies using the framework of the uncontrolled manifold hypothesis. Several phenomena have been simulated including data point distributions corresponding to presence and absence of force-stabilizing synergies in two-finger tasks, changes in synergies with practice, and changes in synergy indices in preparation to a fast action. The model is discussed in comparison to other models of control of multi-element systems based on feedback processes. It shows that patterns of structured variability in the space of elemental variables can result from feed-forward processes. Relations of the model to the equilibrium-point hypothesis are also discussed.     

Spinal motor control system incorporates an internal model of limb dynamics

The existence and utilization of an internal representation of the controlled object is one of the most important features of the functioning of neural motor control systems. This study demonstrates that this property already exists at the level of the spinal motor control system (SMCS), which is capable of generating motor patterns for reflex rhythmic movements, such as locomotion and scratching, without the aid of the peripheral afferent feedback, but substantially modifies the generated activity in response to peripheral afferent stimuli. The SMCS is presented as an optimal control system whose optimality requires that it incorporate an internal model (IM) of the controlled object's dynamics. A novel functional mechanism for the integration of peripheral sensory signals with the corresponding predictive output from the IM, the summation of information precision (SIP) is proposed. In contrast to other models in which the correction of the internal representation of the controlled object's state is based on the calculation of a mismatch between the internal and external information sources, the SIP mechanism merges the information from these sources in order to optimize the precision of the controlled object's state estimate. It is demonstrated, based on scratching in decerebrate cats as an example of the spinal control of goal-directed movements, that the results of computer modeling agree with the experimental observations related to the SMCS's reactions to phasic and tonic peripheral afferent stimuli. It is also shown that the functional requirements imposed by the mathematical model of the SMCS comply with the current knowledge about the related properties of spinal neuronal circuitry. The crucial role of the spinal presynaptic inhibition mechanism in the neuronal implementation of SIP is elucidated. Important differences between the IM and a state predictor employed for compensating for a neural reflex time delay are discussed. Received: 8 February 2000 / Accepted: 24 March 2000     

A hierarchical goal-seeking model of the control of breathing

A model of the overall control of the breathing pattern is presented. The model has the structure of a two-level optimization problem where the lower level criteria determine the shape of the airflow during inspiration and expiration and the higher level criterion determines the values of the other control variables. The model's general formulation makes it possible to obtain predictions of far greater accuracy than before because the previous restrictive assumptions have been avoided by increasing the number of independent control variables. In this model the control variables are the inspiratory time, expiratory time, duration of the end expiratory pause, change in the end expiratory lung volume, the dead space volume, the tidal volume, and the airflow pattern during the cycle. The model's optimization problem has clear and unique minima with respect to each control variable over a wide range of parameter values. Thus the model can be used to predict the effects of various environmental changes.     

A human motor control perspective to multiple manipulator modelling

This paper describes the aspects involved in modelling a multi-robot system from a human motor control perspective. The human motor control system has a hierarchical and decentralised structure, and building a control system for a multi-robot system that attains human features would require a decomposable model. Decomposition of a complex robotic system is difficult due to the interactions between the subsystems, so these have to be first separated before the system is modelled. The proposed method of separating the interconnections is applied with the aid of fuzzy modelling to derive a fully decomposable model of two manipulator robots handling a common object.     

Model-based hierarchical reinforcement learning and human action control

Recent work has reawakened interest in goal-directed or ‘model-based’ choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour.     

Non-linear stimulus-response behavior of the human stance control system is predicted by optimization of a system with sensory and motor noise

We developed a theory of human stance control that predicted (1) how subjects re-weight their utilization of proprioceptive and graviceptive orientation information in experiments where eyes closed stance was perturbed by surface-tilt stimuli with different amplitudes, (2) the experimentally observed increase in body sway variability (i.e. the “remnant” body sway that could not be attributed to the stimulus) with increasing surface-tilt amplitude, (3) neural controller feedback gains that determine the amount of corrective torque generated in relation to sensory cues signaling body orientation, and (4) the magnitude and structure of spontaneous body sway. Responses to surface-tilt perturbations with different amplitudes were interpreted using a feedback control model to determine control parameters and changes in these parameters with stimulus amplitude. Different combinations of internal sensory and/or motor noise sources were added to the model to identify the properties of noise sources that were able to account for the experimental remnant sway characteristics. Various behavioral criteria were investigated to determine if optimization of these criteria could predict the identified model parameters and amplitude-dependent parameter changes. Robust findings were that remnant sway characteristics were best predicted by models that included both sensory and motor noise, the graviceptive noise magnitude was about ten times larger than the proprioceptive noise, and noise sources with signal-dependent properties provided better explanations of remnant sway. Overall results indicate that humans dynamically weight sensory system contributions to stance control and tune their corrective responses to minimize the energetic effects of sensory noise and external stimuli.     

Neural control of human motor development

It has been possible to expand considerably our understanding of human motor development by making a detailed analysis of various types of movement and muscular activation patterns during different stages of development. Alterations in development subsequent to the appearance of brain lesions have enabled valuable information to be collected about the underlying neural mechanisms, in addition to new information concerning the pathophysiology of cerebral palsy. Studies on the development of the corticospinal system indicate that plastic changes can take place after perinatal brain damage.     

Generation of variants of a motor act in a modular and hierarchical motor network

BACKGROUND: Most motor systems can generate a variety of behaviors, including categorically different behaviors and variants of a single motor act within the same behavioral category. Previous work indicated that many pattern-generating interneuronal networks may have a modular organization and that distinct categories of behaviors can be generated through flexible combinations of a small number of modules or building blocks. However, it is unclear whether and how a small number of modules could possibly generate a large number of variants of one behavior. RESULTS: We show that the modular feeding motor network of Aplysia mediates variations in protraction duration in biting-like programs. Two descending commands are active during biting behavior and trigger biting-like responses in a semiintact preparation. In the isolated CNS, when activated alone, the two commands produce biting-like programs of either long or short protraction duration by acting specifically on two modules that have opposite effects on protraction duration. More importantly, when coactivated at different frequencies, the two commands produce biting programs with an intermediate protraction duration. CONCLUSIONS: It was previously hypothesized that behavioral variants may be produced by combining different activity levels of multiple descending commands. Our data provide direct evidence for such a scheme and show how it is implemented in a modularly organized network. Thus, within a modular and hierarchical architecture, in addition to generating different categories of behavior, a small number of modules also efficiently implements variants of a single behavior.     

Visualization of early chromosome condensation: a hierarchical folding, axial glue model of chromosome structure

Current models of mitotic chromosome structure are based largely on the examination of maximally condensed metaphase chromosomes. Here, we test these models by correlating the distribution of two scaffold components with the appearance of prophase chromosome folding intermediates. We confirm an axial distribution of topoisomerase IIalpha and the condensin subunit, structural maintenance of chromosomes 2 (SMC2), in unextracted metaphase chromosomes, with SMC2 localizing to a 150-200-nm-diameter central core. In contrast to predictions of radial loop/scaffold models, this axial distribution does not appear until late prophase, after formation of uniformly condensed middle prophase chromosomes. Instead, SMC2 associates throughout early and middle prophase chromatids, frequently forming foci over the chromosome exterior. Early prophase condensation occurs through folding of large-scale chromatin fibers into condensed masses. These resolve into linear, 200-300-nm-diameter middle prophase chromatids that double in diameter by late prophase. We propose a unified model of chromosome structure in which hierarchical levels of chromatin folding are stabilized late in mitosis by an axial "glue."     

Zebrafish: a model system for the study of human disease

The zebrafish (Danio rerio) is a powerful model organism for the study of vertebrate biology, being well suited to both developmental and genetic analysis. Large-scale genetic screens have identified hundreds of mutant phenotypes, many of which resemble human clinical disorders. The creation of critical genetic reagents, coupled with the rapid progress of the zebrafish genome initiative directed by the National Institutes of Health, are bringing this model system to its full potential for the study of vertebrate biology, physiology and human disease.     

Myelin as longitudinal conductor: a multi-layered model of the myelinated human motor nerve fibre

 The myelin sheath is normally regarded as an electrical insulator. Low values of radial conductance and capacitance have been measured, and in electrical models of myelinated axons the contribution of longitudinal conduction within the sheath has been ignored. According to X-ray diffraction studies, however, myelin sheaths comprise alternate lipid and aqueous layers, and the latter may be expected to have a low resistivity. We propose a new model of myelinated axons in which the aqueous layers within the myelin provide appreciable longitudinal and radial conductance, the latter via a spiral pathway. We have investigated the likely contribution of these conductive paths within the myelin to the electrical properties of a human motor nerve fibre by computer simulation, representing the myelin sheath as a series of interconnecting parallel lamellae. With this new model, action potential conduction has been simulated along a 20-node cable, and the electrotonic responses to 100-ms depolarizing and hyperpolarizing current pulses have been simulated for a uniformly polarized fibre. We have found that the hypothesis of a longitudinally conducting myelin sheath improves our previous model in two ways: it is no longer necessary to make implausible assumptions about the resistivity or width of the periaxonal space to simulate realistic electrotonus, and the conduction velocity is appreciably faster (by 8.6%). Received: 19 April 1999 / Accepted in revised form: 11 September 2000     

DUM neurons in locust flight: a model system for amine-mediated peripheral adjustments to the requirements of a central motor program

In both vertebrates and invertebrates, multiple effects of biogenic amines on neuromuscular transmission, muscle contraction kinetics and metabolism have been described. Nevertheless, it is not yet known whether and how these different effects work in concert during the performance of a specific behavior. In the locust flight system, the biogenic amine octopamine is released as a neurohormone into the haemolymph, and also delivered directly onto specific target muscles by individually identified dorsal unpaired median neurons. Determining the connectivity of these neurons and their activation during behavior, we show for the first time that different types of dorsal unpaired median neurons are differentially connected to certain components of the flight circuitry. During flight, all types of pterothoracic dorsal unpaired median neurons innervating flight muscles receive inhibitory inputs from tegula proprioceptive afferents and from the central flight circuitry, whereas all other types of dorsal unpaired median neurons are excited by wind-sensitive pathways and by the central pattern generator. Considering the results of other studies which investigated metabolic effects of octopamine, we propose a model in which the differential activation of dorsal unpaired median neurons during flight may lead to an adequately controlled release or removal of octopamine to adjust metabolic processes to the requirements of a specific motor program. Accepted: 24 February 1999