Separate representations of dynamics in rhythmic and discrete movements: evidence from motor learning.

Rhythmic and discrete arm movements occur ubiquitously in everyday life, and there is a debate as to whether these two classes of movements arise from the same or different underlying neural mechanisms. Here we examine interference in a motor-learning paradigm to test whether rhythmic and discrete movements employ at least partially separate neural representations. Subjects were required to make circular movements of their right hand while they were exposed to a velocity-dependent force field that perturbed the circularity of the movement path. The direction of the force-field perturbation reversed at the end of each block of 20 revolutions. When subjects made only rhythmic or only discrete circular movements, interference was observed when switching between the two opposing force fields. However, when subjects alternated between blocks of rhythmic and discrete movements, such that each was uniquely associated with one of the perturbation directions, interference was significantly reduced. Only in this case did subjects learn to corepresent the two opposing perturbations, suggesting that different neural resources were employed for the two movement types. Our results provide further evidence that rhythmic and discrete movements employ at least partially separate control mechanisms in the motor system.

Dem analysis of soil-pipeline interaction in sand under lateral and upward movements at deep embedment

The soil-pipeline interactions under lateral and upward pipe movements in sand are investigated using DEM analysis. The simulations are performed for both medium and dense sand conditions at different embedment ratios of up to 60. The comparison of peak dimensionless forces from the DEM and earlier FEM analyses shows that, for medium sand, both methods show similar peak dimensionless forces. For dense sand, the DEM analysis gives more gradual transition of shallow to deep failure mechanisms than the FEM analysis and the peak dimensionless forces at very deep depth are higher in the DEM analysis than in the FEM analysis. Comparison of the deformation mechanism suggests that this is due to the differences in soil movements around the pipe associated with its particulate nature. The DEM analysis provides supplementary data of the soil-pipeline interaction in sand at deep embedment condition.

Virulent Salmonella enterica infections can be exacerbated by concomitant infection of the host with a live attenuated S. enterica vaccine via Toll-like receptor 4-dependent interleukin-10 production with the involvement of both TRIF and MyD88.

During systemic disease in mice, Salmonella enterica grows intracellularly within discrete foci of infection in the spleen and liver. In concomitant infections, foci containing different S. enterica strains are spatially separated. We have investigated whether functional interactions between bacterial populations within the same host can occur despite the known spatial separation of the foci and independence of growth of salmonellae residing in different foci. In this study we have demonstrated that bacterial numbers of virulent S. enterica serovar Typhimurium C5 strain in mouse tissues can be increased by the presence of the attenuated aroA S. Typhimurium SL3261 vaccine strain in the same tissue. Disease exacerbation does not require simultaneous coinjection of the attenuated bacteria. SL3261 can be administered up to 48 hr after or 24 hr before the administration of C5 and still determine higher tissue numbers of the virulent bacteria. This indicates that intravenous administration of a S. enterica vaccine strain could potentially exacerbate an established infection with wild-type bacteria. These data also suggest that the severity of an infection with a virulent S. enterica strain can be increased by the prior administration of a live attenuated vaccine strain if infection occurs within 48 hr of vaccination. Exacerbation of the growth of C5 requires Toll-like receptor 4-dependent interleukin-10 production with the involvement of both Toll/interleukin-1 receptor-domain-containing adaptor inducing interferon-beta and myeloid differentiation factor 88.

Statistics of natural movements are reflected in motor errors.

Humans use their arms to engage in a wide variety of motor tasks during everyday life. However, little is known about the statistics of these natural arm movements. Studies of the sensory system have shown that the statistics of sensory inputs are key to determining sensory processing. We hypothesized that the statistics of natural everyday movements may, in a similar way, influence motor performance as measured in laboratory-based tasks. We developed a portable motion-tracking system that could be worn by subjects as they went about their daily routine outside of a laboratory setting. We found that the well-documented symmetry bias is reflected in the relative incidence of movements made during everyday tasks. Specifically, symmetric and antisymmetric movements are predominant at low frequencies, whereas only symmetric movements are predominant at high frequencies. Moreover, the statistics of natural movements, that is, their relative incidence, correlated with subjects' performance on a laboratory-based phase-tracking task. These results provide a link between natural movement statistics and motor performance and confirm that the symmetry bias documented in laboratory studies is a natural feature of human movement.

Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG.

In the field of motor control, two hypotheses have been controversial: whether the brain acquires internal models that generate accurate motor commands, or whether the brain avoids this by using the viscoelasticity of musculoskeletal system. Recent observations on relatively low stiffness during trained movements support the existence of internal models. However, no study has revealed the decrease in viscoelasticity associated with learning that would imply improvement of internal models as well as synergy between the two hypothetical mechanisms. Previously observed decreases in electromyogram (EMG) might have other explanations, such as trajectory modifications that reduce joint torques. To circumvent such complications, we required strict trajectory control and examined only successful trials having identical trajectory and torque profiles. Subjects were asked to perform a hand movement in unison with a target moving along a specified and unusual trajectory, with shoulder and elbow in the horizontal plane at the shoulder level. To evaluate joint viscoelasticity during the learning of this movement, we proposed an index of muscle co-contraction around the joint (IMCJ). The IMCJ was defined as the summation of the absolute values of antagonistic muscle torques around the joint and computed from the linear relation between surface EMG and joint torque. The IMCJ during isometric contraction, as well as during movements, was confirmed to correlate well with joint stiffness estimated using the conventional method, i.e., applying mechanical perturbations. Accordingly, the IMCJ during the learning of the movement was computed for each joint of each trial using estimated EMG-torque relationship. At the same time, the performance error for each trial was specified as the root mean square of the distance between the target and hand at each time step over the entire trajectory. The time-series data of IMCJ and performance error were decomposed into long-term components that showed decreases in IMCJ in accordance with learning with little change in the trajectory and short-term interactions between the IMCJ and performance error. A cross-correlation analysis and impulse responses both suggested that higher IMCJs follow poor performances, and lower IMCJs follow good performances within a few successive trials. Our results support the hypothesis that viscoelasticity contributes more when internal models are inaccurate, while internal models contribute more after the completion of learning. It is demonstrated that the CNS regulates viscoelasticity on a short- and long-term basis depending on performance error and finally acquires smooth and accurate movements while maintaining stability during the entire learning process.

Cell shape changes indicate a role for extrinsic tensile forces in Drosophila germ-band extension.

Drosophila germ-band extension (GBE) is an example of the convergence and extension movements that elongate and narrow embryonic tissues. To understand the collective cell behaviours underlying tissue morphogenesis, we have continuously quantified cell intercalation and cell shape change during GBE. We show that the fast, early phase of GBE depends on cell shape change in addition to cell intercalation. In antero-posterior patterning mutants such as those for the gap gene Krüppel, defective polarized cell intercalation is compensated for by an increase in antero-posterior cell elongation, such that the initial rate of extension remains the same. Spatio-temporal patterns of cell behaviours indicate that an antero-posterior tensile force deforms the germ band, causing the cells to change shape passively. The rate of antero-posterior cell elongation is reduced in twist mutant embryos, which lack mesoderm. We propose that cell shape change contributing to germ-band extension is a passive response to mechanical forces caused by the invaginating mesoderm.

Human muscle spindles act as forward sensory models.

Modern theories of motor control incorporate forward models that combine sensory information and motor commands to predict future sensory states. Such models circumvent unavoidable neural delays associated with on-line feedback control. Here we show that signals in human muscle spindle afferents during unconstrained wrist and finger movements predict future kinematic states of their parent muscle. Specifically, we show that the discharges of type Ia afferents are best correlated with the velocity of length changes in their parent muscles approximately 100-160 ms in the future and that their discharges vary depending on motor sequences in a way that cannot be explained by the state of their parent muscle alone. We therefore conclude that muscle spindles can act as "forward sensory models": they are affected both by the current state of their parent muscle and by efferent (fusimotor) control, and their discharges represent future kinematic states. If this conjecture is correct, then sensorimotor learning implies learning how to control not only the skeletal muscles but also the fusimotor system.

Distributed optical fiber strain sensing in a secant piled wall

An optical fiber strain sensing technique, based on Brillouin Optical Time Domain Reflectometry (BOTDR), was used to obtain the full deformation profile of a secant pile wall during construction of an adjacent basement in London. Details of the installation of sensors as well as data processing are described. By installing optical fiber down opposite sides of the pile, the distributed strain profiles obtained can be used to give both the axial and lateral movements along the pile. Measurements obtained from the BOTDR were found in good agreement with inclinometer data from the adjacent piles. The relative merits of the two different techniques are discussed. © 2007 ASCE.

Supporting excavations in clay - From analysis to decision-making

Finite Element Analysis (FEA) is used to calibrate a decision-making tool based on an extension of the Mobilized Strength Design (MSD) method which permits the designer an extremely simple method of predicting ground displacements during construction. This newly extended MSD approach accommodates a number of issues which are important in underground construction between in-situ walls, including: alternative base heave mechanisms suitable either for wide excavations in relatively shallow soft clay strata, or narrow excavations in relatively deep soft strata; the influence of support system stiffness in relation to the sequence of propping of the wall; and the capability of dealing with stratified ground. These developments should make it possible for a design engineer to take informed decisions on the relationship between prop spacing and ground movements, or the influence of wall stiffness, or on the need for and influence of a jet-grouted base slab, for example, without having to conduct project-specific FEA. © 2009 Taylor & Francis Group.

Visuomotor feedback gains upregulate during the learning of novel dynamics.

At an early stage of learning novel dynamics, changes in muscle activity are mainly due to corrective feedback responses. These feedback contributions to the overall motor command are gradually reduced as feedforward control is learned. The temporary increased use of feedback could arise simply from the large errors in early learning with either unaltered gains or even slightly downregulated gains, or from an upregulation of the feedback gains when feedforward prediction is insufficient. We therefore investigated whether the sensorimotor control system alters feedback gains during adaptation to a novel force field generated by a robotic manipulandum. To probe the feedback gains throughout learning, we measured the magnitude of involuntary rapid visuomotor responses to rapid shifts in the visual location of the hand during reaching movements. We found large increases in the magnitude of the rapid visuomotor response whenever the dynamics changed: both when the force field was first presented, and when it was removed. We confirmed that these changes in feedback gain are not simply a byproduct of the change in background load, by demonstrating that this rapid visuomotor response is not load sensitive. Our results suggest that when the sensorimotor control system experiences errors, it increases the gain of the visuomotor feedback pathways to deal with the unexpected disturbances until the feedforward controller learns the appropriate dynamics. We suggest that these feedback gains are upregulated with increased uncertainty in the knowledge of the dynamics to counteract any errors or disturbances and ensure accurate and skillful movements.

A technology roadmap of assistive technologies for dementia care in Japan.

The number of elderly people in Japan is growing, which raises the issue of dementia, as the probability of becoming cognitively impaired increases with age. There is an increasing need for caregivers, who are well-trained, experienced and can pay special attention to the needs of people with dementia. Technology can play an important role in helping such people and their caregivers. A lack of mutual understanding between caregivers and researchers regarding the appropriate uses of assistive technologies is another problem. A vision of person-centred care based on the use of information and communication technology to maintain residents' autonomy and continuity in their lives is presented. Based on this vision, a roadmap and a list of challenges to realizing assistive technologies have been developed. The roadmap facilitates mutual understanding between caregivers and researchers, resulting in appropriate technologies to enhance the quality of life of people with dementia.

Twitching in sensorimotor development from sleeping rats to robots.

It is still not known how the 'rudimentary' movements of fetuses and infants are transformed into the coordinated, flexible and adaptive movements of adults. In addressing this important issue, we consider a behavior that has been perennially viewed as a functionless by-product of a dreaming brain: the jerky limb movements called myoclonic twitches. Recent work has identified the neural mechanisms that produce twitching as well as those that convey sensory feedback from twitching limbs to the spinal cord and brain. In turn, these mechanistic insights have helped inspire new ideas about the functional roles that twitching might play in the self-organization of spinal and supraspinal sensorimotor circuits. Striking support for these ideas is coming from the field of developmental robotics: when twitches are mimicked in robot models of the musculoskeletal system, the basic neural circuitry undergoes self-organization. Mutually inspired biological and synthetic approaches promise not only to produce better robots, but also to solve fundamental problems concerning the developmental origins of sensorimotor maps in the spinal cord and brain.