Multidimensional cerebellar computations for flexible kinematic control of movements

Both the environment and our body keep changing dynamically. Hence, ensuring movement precision requires adaptation to multiple demands occurring simultaneously. Here we show that the cerebellum performs the necessary multi-dimensional computations for the flexible control of different movement parameters depending on the prevailing context. This conclusion is based on the identification of a manifold-like activity in both mossy fibers (MF, network input) and Purkinje cells (PC, output), recorded from monkeys performing a saccade task. Unlike MFs, the properties of PC manifolds developed selective representations of individual movement parameters. Error feedback-driven climbing fiber input modulated the PC manifolds to predict specific, error type-dependent changes in subsequent actions. Furthermore, a feed-forward network model that simulated MF-to-PC transformations revealed that amplification and restructuring of the lesser variability in the MF activity is a pivotal circuit mechanism. Therefore, flexible control of movement by the cerebellum crucially depends on its capacity for multi-dimensional computations.

Design and Analysis of a Novel Double-Stator Double-Rotor Motor Drive System for In-Wheel Direct Drive of Electric Vehicles

In-wheel direct drive (IWDD) of electric vehicles (EVs), which simplifies the transmission system and facilitates flexible control of vehicle dynamics, has evolved considerably in the EV sector. This paper proposes a novel double-stator double-rotor motor (DSDRM) with a bidirectional flux modulation effect for in-wheel direct drive of EVs. With the proposed special design, a synthetic-slot structure with synthetic materials containing copper and permanent magnets (PMs) in the slots of the motor is ingeniously employed, and the outer and inner rotors are mechanically connected together as a single rotor, making its mechanical structure less complicated than those of two-rotor machines. The main work of this paper involves the design, analysis, construction, and testing of the proposed machine. The DSDRM with a synthetic-slot structure was demonstrated to be feasible by finite element analysis (FEA), prototype fabrication, and experimental results. In addition, vehicle layout with DSDRM is presented and verified by the vehicle road test experiment. Thus, the DSDRM with the synthetic-slot structure can be used as a hub motor for in-wheel direct drive of EVs.

Ferroelectric domain-wall logic units

The electronic conductivities of ferroelectric domain walls have been extensively explored over the past decade for potential nanoelectronic applications. However, the realization of logic devices based on ferroelectric domain walls requires reliable and flexible control of the domain-wall configuration and conduction path. Here, we demonstrate electric-field-controlled stable and repeatable on-and-off switching of conductive domain walls within topologically confined vertex domains naturally formed in self-assembled ferroelectric nano-islands. Using a combination of piezoresponse force microscopy, conductive atomic force microscopy, and phase-field simulations, we show that on-off switching is accomplished through reversible transformations between charged and neutral domain walls via electric-field-controlled domain-wall reconfiguration. By analogy to logic processing, we propose programmable logic gates (such as NOT, OR, AND and their derivatives) and logic circuits (such as fan-out) based on reconfigurable conductive domain walls. Our work provides a potentially viable platform for programmable all-electric logic based on a ferroelectric domain-wall network with low energy consumption.

Cortical and thalamic influences on striatal involvement in instructed, serial reversal learning; implications for the organisation of flexible behaviour.

Cognitive flexibility is essential for enabling an individual to respond adaptively to changes in their environment. Evidence from human and animal research suggests that the control of cognitive flexibility is dependent on an array of neural architecture. Cortico-basal ganglia circuits have long been implicated in cognitive flexibility. In particular, the role of the striatum is pivotal, acting as an integrative hub for inputs from the prefrontal cortex and thalamus, and modulation by dopamine and acetylcholine. Striatal cholinergic modulation has been implicated in the flexible control of behaviour, driven by input from the centromedian-parafascicular nuclei of the thalamus. However, the role of this system in humans is not clearly defined as much of the current literature is based on animal work. Here, we aim to investigate the roles corticostriatal and thalamostriatal connectivity in serial reversal learning. Functional connectivity between the left centromedian-parafascicular nuclei and the associative dorsal striatum was significantly increased for negative feedback compared to positive feedback. Similar differences in functional connectivity were observed for the right lateral orbitofrontal cortex, but these were localised to when participants switched to using an alternate response strategy following reversal. These findings suggest that connectivity between the centromedian-parafascicular nuclei and the striatum may be used to generally identify potential changes in context based on negative outcomes, and the effect of this signal on striatal output may be influenced by connectivity between the lateral orbitofrontal cortex and the striatum.

Tuning as convex optimisation: a polynomial tuner for multi-parametric combinatorial samplers

Combinatorial samplers are algorithmic schemes devised for the approximate- and exact-size generation of large random combinatorial structures, such as context-free words, various tree-like data structures, maps, tilings, RNA molecules. They can be adapted to combinatorial specifications with additional parameters, allowing for a more flexible control over the output profile of parametrised combinatorial patterns. One can control, for instance, the number of leaves, profile of node degrees in trees or the number of certain sub-patterns in generated strings. However, such a flexible control requires an additional and nontrivial tuning procedure. Using techniques of convex optimisation, we present an efficient tuning algorithm for multi-parametric combinatorial specifications. Our algorithm works in polynomial time in the system description length, the number of tuning parameters, the number of combinatorial classes in the specification, and the logarithm of the total target size. We demonstrate the effectiveness of our method on a series of practical examples, including rational, algebraic, and so-called Pólya specifications. We show how our method can be adapted to a broad range of less typical combinatorial constructions, including symmetric polynomials, labelled sets and cycles with cardinality lower bounds, simple increasing trees or substitutions. Finally, we discuss some practical aspects of our prototype tuner implementation and provide its benchmark results.

Fast-Setting Permeable Alkyd/Polyester Composites: Moulding Sands

This paper presents the outcomes of extensive research targeting the development of high-performance alkyd and polyester resins used as binders in mould- and core-making permeable composite materials designated for large-size/complex-shape, heavy alloy-steel and cast-iron castings (0.5 to 50 tonnes): steam turbine casings (e.g., 18K360 condensing turbine), naval engine blocks and heavy machinery. The technology was implemented by Zamech/ALSTON Power. The key issues discussed here are: (1) control of resin crosslinking kinetics; slow or rapid strength development, (2) shelf-life control of pre-mixed composite, (3) improved thermo-mechanical stability; (4) kinetics of gaseous by-product emission. Optimised composite formulations (resins, crosslinkers and catalysts) allow for the flexible control of material properties and mould-/core fabrication, i.e.,: shelf-life: 10–120 min; mould stripping time: 10 min to 24 h; compressive strength: 4–6 MPa (with post-cure: 10–12 MPa); tensile strength: up to 3 MPa (after post-cure). The moulding sands developed achieved thermal resistance temperatures of up to 345 °C, which exceeded that of 280 °C of comparable commercial material. The onset of the thermal decomposition process was 2–3 times longer than that of furan or commercial alkyd/polyester resin. The technology developed allows for the defect-free manufacture of castings (no pinholes) and binder contents minimisation to 1.2–1.5% with quartz and 1.2% with zirconium or chromite sand.

Interfacing Spinal Motor Units in Non-Human Primates Identifies a Principal Neural Component for Force Control Constrained by the Size Principle

ABSTRACTMotor units convert the last neural code of movement into muscle forces. The classic view of motor unit control is that the central nervous system sends common synaptic inputs to motoneuron pools and that motoneurons respond in an orderly fashion dictated by the size principle. This view however is in contrast with the large number of dimensions observed in motor cortex which may allow individual and flexible control of motor units. Evidence for flexible control of motor units may be obtained by tracking motor units longitudinally during the performance of tasks with some level of behavioural variability. Here we identified and tracked populations of motor units in the brachioradialis muscle of two macaque monkeys during ten sessions spanning over one month during high force isometric contractions with a broad range of rate of force development (1.8 – 38.6 N·m·s-1). During the same sessions we recorded intramuscular EMG signals from 16 arm muscles of both limbs and elicited the full recruitment through neural stimulation of the median and deep radial nerves. We found a very stable recruitment order and discharge characteristics of the motor units over sessions and contraction trials. The small deviations from orderly recruitment were observed between motor units with close recruitment thresholds, and only during high rate of force development. Moreover, we also found that one component explained more than ~50% of the motor unit discharge rate variance, and that the remaining components could be described as a time-shifted version of the first, as it could be predicted from the interplay between the size principle of recruitment and one common input. In conclusion, our results show that motoneurons recruitment is determined by the interplay of the size principle and common input and that this recruitment scheme is not violated over time nor by the speed of the contractions.

A neural circuit for flexible control of persistent behavioral states

To adapt to their environments, animals must generate behaviors that are closely aligned to a rapidly changing sensory world. However, behavioral states such as foraging or courtship typically persist over long time scales to ensure proper execution. It remains unclear how neural circuits generate persistent behavioral states while maintaining the flexibility to select among alternative states when the sensory context changes. Here, we elucidate the functional architecture of a neural circuit controlling the choice between roaming and dwelling states, which underlie exploration and exploitation during foraging in C. elegans. By imaging ensemble-level neural activity in freely-moving animals, we identify stereotyped changes in circuit activity corresponding to each behavioral state. Combining circuit-wide imaging with genetic analysis, we find that mutual inhibition between two antagonistic neuromodulatory systems underlies the persistence and mutual exclusivity of the neural activity patterns observed in each state. Through machine learning analysis and circuit perturbations, we identify a sensory processing neuron that can transmit information about food odors to both the roaming and dwelling circuits and bias the animal towards different states in different sensory contexts, giving rise to context-appropriate state transitions. Our findings reveal a potentially general circuit architecture that enables flexible, sensory-driven control of persistent behavioral states.

Bidirectional, Analog Current Source Benchmarked with Gray Molasses-Assisted Stray Magnetic Field Compensation

In ultracold-atom and ion experiments, flexible control of the direction and amplitude of a uniform magnetic field is necessary. It is achieved almost exclusively by controlling the current flowing through coils surrounding the experimental chamber. Here, we present the design and characterization of a modular, analog electronic circuit that enables three-dimensional control of a magnetic field via the amplitude and direction of a current flowing through three perpendicular pairs of coils. Each pair is controlled by one module, and we are able to continuously change the current flowing thorough the coils in the ±4 A range using analog waveforms such that smooth crossing through zero as the current’s direction changes is possible. With the electrical current stability at the 10−5 level, the designed circuit enables state-of-the-art ultracold experiments. As a benchmark, we use the circuit to compensate stray magnetic fields that hinder efficient sub-Doppler cooling of alkali atoms in gray molasses. We demonstrate how such compensation can be achieved without actually measuring the stray fields present, thus speeding up the process of optimization of various laser cooling stages.