Neuromotor Noise, Error Tolerance and Velocity-Dependent Costs in Skilled Performance

In motor tasks with redundancy neuromotor noise can lead to variations in execution while achieving relative invariance in the result. The present study examined whether humans find solutions that are tolerant to intrinsic noise. Using a throwing task in a virtual set-up where an infinite set of angle and velocity combinations at ball release yield throwing accuracy, our computational approach permitted quantitative predictions about solution strategies that are tolerant to noise. Based on a mathematical model of the task expected results were computed and provided predictions about error-tolerant strategies (Hypothesis 1). As strategies can take on a large range of velocities, a second hypothesis was that subjects select strategies that minimize velocity at release to avoid costs associated with signal- or velocity-dependent noise or higher energy demands (Hypothesis 2). Two experiments with different target constellations tested these two hypotheses. Results of Experiment 1 showed that subjects chose solutions with high error-tolerance, although these solutions also had relatively low velocity. These two benefits seemed to outweigh that for many subjects these solutions were close to a high-penalty area, i.e. they were risky. Experiment 2 dissociated the two hypotheses. Results showed that individuals were consistent with Hypothesis 1 although their solutions were distributed over a range of velocities. Additional analyses revealed that a velocity-dependent increase in variability was absent, probably due to the presence of a solution manifold that channeled variability in a task-specific manner. Hence, the general acceptance of signal-dependent noise may need some qualification. These findings have significance for the fundamental understanding of how the central nervous system deals with its inherent neuromotor noise

A Neurodynamic Account of Spontaneous Behaviour

The current article suggests that deterministic chaos self-organized in cortical dynamics could be responsible for the generation of spontaneous action sequences. Recently, various psychological observations have suggested that humans and primates can learn to extract statistical structures hidden in perceptual sequences experienced during active environmental interactions. Although it has been suggested that such statistical structures involve chunking or compositional primitives, their neuronal implementations in brains have not yet been clarified. Therefore, to reconstruct the phenomena, synthetic neuro-robotics experiments were conducted by using a neural network model, which is characterized by a generative model with intentional states and its multiple timescales dynamics. The experimental results showed that the robot successfully learned to imitate tutored behavioral sequence patterns by extracting the underlying transition probability among primitive actions. An analysis revealed that a set of primitive action patterns was embedded in the fast dynamics part, and the chaotic dynamics of spontaneously sequencing these action primitive patterns was structured in the slow dynamics part, provided that the timescale was adequately set for each part. It was also shown that self-organization of this type of functional hierarchy ensured robust action generation by the robot in its interactions with a noisy environment. This article discusses the correspondence of the synthetic experiments with the known hierarchy of the prefrontal cortex, the supplementary motor area, and the primary motor cortex for action generation. We speculate that deterministic dynamical structures organized in the prefrontal cortex could be essential because they can account for the generation of both intentional behaviors of fixed action sequences and spontaneous behaviors of pseudo-stochastic action sequences by the same mechanism

Distinct Timing Mechanisms Produce Discrete and Continuous Movements

The differentiation of discrete and continuous movement is one of the pillars of motor behavior classification. Discrete movements have a definite beginning and end, whereas continuous movements do not have such discriminable end points. In the past decade there has been vigorous debate whether this classification implies different control processes. This debate up until the present has been empirically based. Here, we present an unambiguous non-empirical classification based on theorems in dynamical system theory that sets discrete and continuous movements apart. Through computational simulations of representative modes of each class and topological analysis of the flow in state space, we show that distinct control mechanisms underwrite discrete and fast rhythmic movements. In particular, we demonstrate that discrete movements require a time keeper while fast rhythmic movements do not. We validate our computational findings experimentally using a behavioral paradigm in which human participants performed finger flexion-extension movements at various movement paces and under different instructions. Our results demonstrate that the human motor system employs different timing control mechanisms (presumably via differential recruitment of neural subsystems) to accomplish varying behavioral functions such as speed constraints

Constraints on perception of information from obstacles during foot clearance in people with chronic stroke

The aim of this study was to examine effects of different types of task constraints on coupling of perception and action in people with chronic stroke when crossing obstacles during a walking task. Ten participants with hemiplegic chronic stroke volunteered to walk over a static obstacle under two distinct task constraints: simple and dual task. Under simple task constraints, without specific instructions, participants walked at their preferred speed and crossed over an obstacle. Under dual task constraints the same individuals were required to subtract numbers whilst walking. Under both distinct task constraints, we examined emergent values of foot distance when clearing a static obstacle in both affected and unaffected legs, measured by a 3D motion tracking system. Principal Component Analysis was used to quantify task performance and discriminant analysis was used to compare gait performance between task constraints. Results suggested that patients, regardless of affected body side, demonstrated differences in perception of distance information from the obstacle, which constrained gait differences in initial swing, mid-swing and crossing phases. Further, dual task constraints, rather than hemiplegic body side, was a significant discriminator in patients' perceptions of distance and height information to the obstacle. These findings suggested how performance of additional cognitive tasks might constrain perception of information from an obstacle in people with chronic stroke during different phases of obstacle crossing, and thus may impair their adaptive ability to successfully manoeuvre around objects

Training dual-task walking in community-dwelling adults within 1 year of stroke: A protocol for a single-blind randomized controlled trial

Background: Community ambulation is a highly complex skill requiring the ability to adapt to increased environmental complexity and perform multiple tasks simultaneously. After stroke, individuals demonstrate a diminished ability to perform dual-tasks. Current evidence suggests that conventional rehabilitation does not adequately address gait-related dual-task impairments after stroke, which may be contributing to low levels of participation and physical inactivity in community-dwelling stroke survivors. The objective of this study is to investigate the efficacy of dual-task gait training in community-dwelling adults within 1 year of stroke. Specifically, we will compare the effects of dual-task gait training and single-task gait training on cognitive-motor interference during walking at preferred speed and at fastest comfortable speed (Aim 1), locomotor control during obstacle negotiation (Aim 2), and spontaneous physical activity (Aim 3). Methods/design: This single-blind randomized controlled trial will involve 44 individuals within 12 months of stroke. Following baseline evaluation, participants will be randomly allocated to single- or dual-task gait training. Both groups will receive 12, 30-minute sessions provided one-on-one over 4–6 weeks in an outpatient therapy setting. Single-task gait training involves practice of gait activities incorporating motor relearning principles. Dual-task gait training involves an identical gait training protocol; the critical difference being that the dual-task gait training group will practice the gait activities while simultaneously performing a cognitive task for 75% of the repetitions. Blinded assessors will measure outcomes at baseline, post-intervention, and 6 months after completion of the intervention. The primary outcome measure will be dual-task effects on gait speed and cognition during unobstructed walking. Secondary outcomes include spatiotemporal and kinetic gait parameters during unobstructed single- and dual-task walking at preferred and fastest comfortable walking speeds, gait parameters during high and low obstacle crossing, spontaneous physical activity, executive function, lower extremity motor function, Timed Up and Go, balance self-efficacy, number of falls, and stroke-related disability. Hypotheses for each aim will be tested using an intention-to-treat analysis with repeated measures ANOVA design. Discussion: This trial will provide evidence to help clinicians make decisions about the types of activities to include in rehabilitation to improve dual-task walking after stroke

Synchrony of hand-foot coupled movements: is it attained by mutual feedback entrainment or by independent linkage of each limb to a common rhythm generator?

BACKGROUND: Synchrony of coupled oscillations of ipsilateral hand and foot may be achieved by controlling the interlimb phase difference through a crossed kinaesthetic feedback between the two limbs, or by an independent linkage of each limb cycle to a common clock signal. These alternative models may be experimentally challenged by comparing the behaviour of the two limbs when they oscillate following an external time giver, either alone or coupled together. RESULTS: Ten subjects oscillated their right hand and foot both alone and coupled (iso- or antidirectionally), paced by a metronome. Wrist and ankle angular position and Electromyograms (EMG) from the respective flexor and extensor muscles were recorded. Three phase delays were measured: i) the clk-mov delay, between the clock (metronome beat) and the oscillation peak; ii) the neur (neural) delay, between the clock and the motoneurone excitatory input, as inferred from the EMG onset; and iii) the mech (mechanical) delay between the EMG onset and the corresponding point of the limb oscillation. During uncoupled oscillations (0.4 Hz to 3.0 Hz), the mech delay increased from -7° to -111° (hand) and from -4° to -83° (foot). In contrast, the clk-mov delay remained constant and close to zero in either limb since a progressive advance of the motoneurone activation on the pacing beat (neur advance) compensated for the increasing mech delay. Adding an inertial load to either extremity induced a frequency dependent increase of the limb mechanical delay that could not be completely compensated by the increase of the neural phase advance, resulting in a frequency dependent increment of clk-mov delay of the hampered limb. When limb oscillations were iso- or antidirectionally coupled, either in the loaded or unloaded condition, the three delays did not significantly change with respect to values measured when limbs were moved separately. CONCLUSION: The absence of any significant effect of limb coupling on the measured delays suggests that during hand-foot oscillations, both iso- and antidirectionally coupled, each limb is synchronised to the common rhythm generator by a "private" position control, with no need for a crossed feedback interaction between limbs

Complex Processes from Dynamical Architectures with Time-Scale Hierarchy

The idea that complex motor, perceptual, and cognitive behaviors are composed of smaller units, which are somehow brought into a meaningful relation, permeates the biological and life sciences. However, no principled framework defining the constituent elementary processes has been developed to this date. Consequently, functional configurations (or architectures) relating elementary processes and external influences are mostly piecemeal formulations suitable to particular instances only. Here, we develop a general dynamical framework for distinct functional architectures characterized by the time-scale separation of their constituents and evaluate their efficiency. Thereto, we build on the (phase) flow of a system, which prescribes the temporal evolution of its state variables. The phase flow topology allows for the unambiguous classification of qualitatively distinct processes, which we consider to represent the functional units or modes within the dynamical architecture. Using the example of a composite movement we illustrate how different architectures can be characterized by their degree of time scale separation between the internal elements of the architecture (i.e. the functional modes) and external interventions. We reveal a tradeoff of the interactions between internal and external influences, which offers a theoretical justification for the efficient composition of complex processes out of non-trivial elementary processes or functional modes

A Compact Representation of Drawing Movements with Sequences of Parabolic Primitives

Some studies suggest that complex arm movements in humans and monkeys may optimize several objective functions, while others claim that arm movements satisfy geometric constraints and are composed of elementary components. However, the ability to unify different constraints has remained an open question. The criterion for a maximally smooth (minimizing jerk) motion is satisfied for parabolic trajectories having constant equi-affine speed, which thus comply with the geometric constraint known as the two-thirds power law. Here we empirically test the hypothesis that parabolic segments provide a compact representation of spontaneous drawing movements. Monkey scribblings performed during a period of practice were recorded. Practiced hand paths could be approximated well by relatively long parabolic segments. Following practice, the orientations and spatial locations of the fitted parabolic segments could be drawn from only 2–4 clusters, and there was less discrepancy between the fitted parabolic segments and the executed paths. This enabled us to show that well-practiced spontaneous scribbling movements can be represented as sequences (“words”) of a small number of elementary parabolic primitives (“letters”). A movement primitive can be defined as a movement entity that cannot be intentionally stopped before its completion. We found that in a well-trained monkey a movement was usually decelerated after receiving a reward, but it stopped only after the completion of a sequence composed of several parabolic segments. Piece-wise parabolic segments can be generated by applying affine geometric transformations to a single parabolic template. Thus, complex movements might be constructed by applying sequences of suitable geometric transformations to a few templates. Our findings therefore suggest that the motor system aims at achieving more parsimonious internal representations through practice, that parabolas serve as geometric primitives and that non-Euclidean variables are employed in internal movement representations (due to the special role of parabolas in equi-affine geometry)