Muscle redundancy is greatly reduced by the spatiotemporal nature of neuromuscular control.

Animals must control numerous muscles to produce forces and movements with their limbs. Current theories of motor optimization and synergistic control are predicated on the assumption that there are multiple highly diverse feasible activations for any motor task ("muscle redundancy"). Here, we demonstrate that the dimensionality of the neuromuscular control problem is greatly reduced when adding the temporal constraints inherent to any sequence of motor commands: the physiological time constants for muscle activation-contraction dynamics. We used a seven-muscle model of a human finger to fully characterize the seven-dimensional polytope of all possible motor commands that can produce fingertip force vector in any direction in 3D, in alignment with the core models of Feasibility Theory. For a given sequence of seven force vectors lasting 300 ms, a novel single-step extended linear program finds the 49-dimensional polytope of all possible motor commands that can produce the sequence of forces. We find that muscle redundancy is severely reduced when the temporal limits on muscle activation-contraction dynamics are added. For example, allowing a generous ±12% change in muscle activation within 50 ms allows visiting only ∼7% of the feasible activation space in the next time step. By considering that every motor command conditions future commands, we find that the motor-control landscape is much more highly structured and spatially constrained than previously recognized. We discuss how this challenges traditional computational and conceptual theories of motor control and neurorehabilitation for which muscle redundancy is a foundational assumption.

Temporal control of muscle synergies is linked with alpha-band neural drive.

KEY POINTS: It is theorized that the nervous system controls groups of muscles together as functional units, or 'synergies', resulting in correlated electromyographic (EMG) signals among muscles. However, such correlation does not necessarily imply group-level neural control. Oscillatory synchronization (coherence) among EMG signals implies neural coupling, but it is not clear how this relates to control of muscle synergies. EMG was recorded from seven arm muscles of 10 adult participants rotating an upper limb ergometer, and EMG-EMG coherence, EMG amplitude correlations and their relationship with each other were characterized. A novel method to derive multi-muscle synergies from EMG-EMG coherence is presented and these are compared with classically defined synergies. Coherent alpha-band (8-16 Hz) drive was strongest among muscles whose gross activity levels are well correlated within a given task. The cross-muscle distribution and temporal modulation of coherent alpha-band drive suggests a possible role in the neural coordination/monitoring of synergies. ABSTRACT: During movement, groups of muscles may be controlled together by the nervous system as an adaptable functional entity, or 'synergy'. The rules governing when (or if) this occurs during voluntary behaviour in humans are not well understood, at least in part because synergies are usually defined by correlated patterns of muscle activity without regard for the underlying structure of their neural control. In this study, we investigated the extent to which comodulation of muscle output (i.e. correlation of electromyographic (EMG) amplitudes) implies that muscles share intermuscular neural input (assessed via EMG-EMG coherence analysis). We first examined this relationship among pairs of upper limb muscles engaged in an arm cycling task. We then applied a novel multidimensional EMG-EMG coherence analysis allowing synergies to be characterized on the basis of shared neural drive. We found that alpha-band coherence (8-16 Hz) is related to the degree to which overall muscle activity levels correlate over time. The extension of this coherence analysis to describe the cross-muscle distribution and temporal modulation of alpha-band drive revealed a close match to the temporal and structural features of traditionally defined muscle synergies. Interestingly, the coherence-derived neural drive was inversely associated with, and preceded, changes in EMG amplitudes by ∼200 ms. Our novel characterization of how alpha-band neural drive is dynamically distributed among muscles is a fundamental step forward in understanding the neural origins and correlates of muscle synergies.

Autonomous Functional Movements in a Tendon-Driven Limb via Limited Experience.

Robots will become ubiquitously useful only when they can use few attempts to teach themselves to perform different tasks, even with complex bodies and in dynamical environments. Vertebrates, in fact, use sparse trial-and-error to learn multiple tasks despite their intricate tendon-driven anatomies-which are particularly hard to control because they are simultaneously nonlinear, under-determined, and over-determined. We demonstrate-for the first time in simulation and hardware-how a model-free, open-loop approach allows few-shot autonomous learning to produce effective movements in a 3-tendon 2-joint limb. We use a short period of motor babbling (to create an initial inverse map) followed by building functional habits by reinforcing high-reward behavior and refinements of the inverse map in a movement's neighborhood. This biologically-plausible algorithm, which we call G2P (General-to-Particular), can potentially enable quick, robust and versatile adaptation in robots as well as shed light on the foundations of the enviable functional versatility of organisms.

Feasibility Theory Reconciles and Informs Alternative Approaches to Neuromuscular Control.

We present Feasibility Theory, a conceptual and computational framework to unify today's theories of neuromuscular control. We begin by describing how the musculoskeletal anatomy of the limb, the need to control individual tendons, and the physics of a motor task uniquely specify the family of all valid muscle activations that accomplish it (its 'feasible activation space'). For our example of producing static force with a finger driven by seven muscles, computational geometry characterizes-in a complete way-the structure of feasible activation spaces as 3-dimensional polytopes embedded in 7-D. The feasible activation space for a given task is the landscape where all neuromuscular learning, control, and performance must occur. This approach unifies current theories of neuromuscular control because the structure of feasible activation spaces can be separately approximated as either low-dimensional basis functions (synergies), high-dimensional joint probability distributions (Bayesian priors), or fitness landscapes (to optimize cost functions).

Eye Histology and Ganglion Cell Topography of Northern Elephant Seals (Mirounga angustirostris).

Northern elephant seals are one of the deepest diving marine mammals. As northern elephant seals often reach the bathypelagic zone, it is usually assumed that their eyes possess evolutionary adaptations that provide better ability to see in dim or scotopic environments. The purpose of this study was to carefully describe anatomical and histological traits of the eye that may improve light sensitivity. Northern elephant seals have large, somewhat elliptical eyes, with equatorial and anteroposterior diameters of 5.03 and 4.4 cm, respectively. The cornea is large in diameter and the lens is completely spherical. The iris has pronounced constrictor and dilator muscles, whereas the ciliary muscle is notably less developed. The tapetum lucidum is more prominent than in other pinnipeds, making up about 63% of retinal thickness in the posterior aspect of the globe. Within the retina, the pigmented epithelium lacks pigment except for the region close to the ora serrata. Parts of the photoreceptor and outer nuclear layers are folded. Although the photoreceptor layer is composed predominantly of rods, cone photoreceptors were also observed. Cells within the retinal ganglion cell layer are arranged in a single level. Ganglion cells reach their maximum density (∼1,300 cells per mm(2) ) dorsal to the optic disc, whereas the periphery of the retina is sparsely populated (<100 cells per mm(2) ). All above mentioned features are consistent with the predicted evolutionary adaptations to the photic environment of the bathypelagic zone. Anat Rec, 299:798-805, 2016. © 2016 Wiley Periodicals, Inc.

Retinal topography maps in R: new tools for the analysis and visualization of spatial retinal data.

Retinal topography maps are a widely used tool in vision science, neuroscience, and visual ecology, providing an informative visualization of the spatial distribution of cell densities across the retinal hemisphere. Here, we introduce Retina, an R package for computational mapping, inspection of topographic model fits, and generation of average maps. Functions in Retina take cell count data obtained from retinal wholemounts using stereology software. Accurate visualizations and comparisons between different eyes have been difficult in the past, because of deformation and incisions of retinal wholemounts. We account for these issues by incorporation of the R package Retistruct, which results in a retrodeformation of the wholemount into a hemispherical shape, similar to the original eyecup. The maps are generated by thin plate splines, after the data were transformed into a two-dimensional space with an azimuthal equidistant plot projection. Retina users can compute retinal topography maps independent of stereology software choice and assess model fits with a variety of diagnostic plots. Functionality of Retina also includes species average maps, an essential feature for interspecific analyses. The Retina package will facilitate rigorous comparative studies in visual ecology by providing a robust quantitative approach to generate retinal topography maps.