Robust platform for inline Raman monitoring and control of perfusion cell culture

Perfusion cell culture has been gaining increasing popularity for biologics manufacturing due to benefits such as smaller footprint, increased productivity, consistent product quality and manufacturing flexibility, cost savings, and so forth. Process Analytics Technologies tools are highly desirable for effective monitoring and control of long-running perfusion processes. Raman has been widely investigated for monitoring and control of traditional fed batch cell culture process. However, implementation of Raman for perfusion cell culture has been very limited mainly due to challenges with high-cell density and long running times during perfusion which cause extremely high fluorescence interference to Raman spectra and consequently it is exceedingly difficult to develop robust chemometrics models. In this work, a platform based on Raman measurement of permeate has been proposed for effective analysis of perfusion process. It has been demonstrated that this platform can effectively circumvent the fluorescence interference issue while providing rich and timely information about perfusion dynamics to enable efficient process monitoring and robust bioreactor feed control. With the highly consistent spectral data from cell-free sample matrix, development of chemometrics models can be greatly facilitated. Based on this platform, Raman models have been developed for good measurement of several analytes including glucose, lactate, glutamine, glutamate, and permeate titer. Performance of Raman models developed this way has been systematically evaluated and the models have shown good robustness against changes in perfusion scale and variations in permeate flowrate; thus models developed from small lab scale can be directly transferred for implementation in much larger scale of perfusion. With demonstrated robustness, this platform provides a reliable approach for automated glucose feed control in perfusion bioreactors. Glucose model developed from small lab scale has been successfully implemented for automated continuous glucose feed control of perfusion cell culture at much larger scale.

Servo navigators: Linear regression and feedback control for rigid-body motion correction

PURPOSE

Navigator-based correction of rigid-body motion reconciling high precision with minimal acquisition, minimal calibration and simple, fast processing.

METHODS

A short orbital navigator (2.3 ms) is inserted in a three-dimensional (3D) gradient echo sequence for human head imaging. Head rotation and translation are determined by linear regression based on a complex-valued model built either from three reference navigators or in a reference-less fashion, from the first actual navigator. Optionally, the model is expanded by global phase and field offset. Run-time scan correction on this basis establishes servo control that maintains validity of the linear picture by keeping its expansion point stable in the head frame of reference. The technique is assessed in a phantom and demonstrated by motion-corrected imaging in vivo.

RESULTS

The proposed approach is found to establish stable motion control both with and without reference acquisition. In a phantom, it is shown to accurately detect motion mimicked by rotation of scan geometry as well as change in global B0 . It is demonstrated to converge to accurate motion estimates after perturbation well beyond the linear signal range. In vivo, servo navigation achieved motion detection with precision in the single-digit range of micrometers and millidegrees. Involuntary and intentional motion in the range of several millimeters were successfully corrected, achieving excellent image quality.

CONCLUSION

The combination of linear regression and feedback control enables prospective motion correction for head imaging with high precision and accuracy, short navigator readouts, fast run-time computation, and minimal demand for reference data.

Social influence and external feedback control in humans

This article aims to unravel the dynamics of social influence by examining the processes that occur when one person is the target of another's influence. We hypothesized that these processes are part of a feedback loop system in an individual. This loop involves the situation (input), a goal state (reference), a comparator, a selection mechanism, a feedback predictor, and an action (output). Each element can become the target of social influence, and different types of social influence can be classified and explained by how these elements are targeted. For instance, attempting to persuade another person with strong arguments targets the goal state of the affected individual, while obedience targets the selection mechanism, and violence targets the action. In summary, this article aims to categorize, order, and explain phenomena in social influence research using a feedback loop framework focusing on the influenced individual.

Modulations of stretch reflex by altering visuomotor contexts

Various functional modulations of the stretch reflex help to stabilize actions, but the computational mechanism behind its context-dependent tuning remains unclear. While many studies have demonstrated that motor contexts associated with the task goal cause functional modulation of the stretch reflex of upper limbs, it is not well understood how visual contexts independent of the task requirements affect the stretch reflex. To explore this issue, we conducted two experiments testing 20 healthy human participants (age range 20-45, average 31.3 ± 9.0), in which visual contexts were manipulated in a visually guided reaching task. During wrist flexion movements toward a visual target, a mechanical load was applied to the wrist joint to evoke stretch reflex of wrist flexor muscle (flexor carpi radialis). The first experiment (n = 10) examined the effect of altering the visuomotor transformation on the stretch reflex that was evaluated with surface electromyogram. We found that the amplitude of the stretch reflex decreased (p = 0.024) when a rotational transformation of 90° was introduced between the hand movement and the visual cursor, whereas the amplitude did not significantly change (p = 0.26) when the rotational transformation was accompanied by a head rotation so that the configuration of visual feedback was maintained in visual coordinates. The results suggest that the stretch reflex was regulated depending on whether the visuomotor mapping had already been acquired or not. In the second experiment (n = 10), we examined how uncertainty in the visual target or hand cursor affects the stretch reflex by removing these visual stimuli. We found that the reflex amplitude was reduced by the disappearance of the hand cursor (p = 0.039), but was not affected by removal of the visual target (p = 0.27), suggesting that the visual state of the body and target contribute differently to the reflex tuning. These findings support the idea that visual updating of the body state is crucial for regulation of quick motor control driven by proprioceptive signals.

Enhanced feedback performance in off-resonance AFM modes through pulse train sampling

Dynamic atomic force microscopy (AFM) modes that operate at frequencies far away from the resonance frequency of the cantilever (off-resonance tapping (ORT) modes) can provide high-resolution imaging of a wide range of sample types, including biological samples, soft polymers, and hard materials. These modes offer precise and stable control of vertical force, as well as reduced lateral force. Simultaneously, they enable mechanical property mapping of the sample. However, ORT modes have an intrinsic drawback: a low scan speed due to the limited ORT rate, generally in the low-kilohertz range. Here, we analyze how the conventional ORT control method limits the topography tracking quality and hence the imaging speed. The closed-loop controller in conventional ORT restricts the sampling rate to the ORT rate and introduces a large closed-loop delay. We present an alternative ORT control method in which the closed-loop controller samples and tracks the vertical force changes during a defined time window of the tip-sample interaction. Through this, we use multiple samples in the proximity of the maximum force for the feedback loop, rather than only one sample at the maximum force instant. This method leads to improved topography tracking at a given ORT rate and therefore enables higher scan rates while refining the mechanical property mapping.

Motor deficits in autism differ from that of developmental coordination disorder

LAY ABSTRACT

A vast majority of individuals with autism spectrum disorder experience impairments in motor skills. Those are often labelled as additional developmental coordination disorder despite the lack of studies comparing both disorders. Consequently, motor skills rehabilitation programmes in autism are often not specific but rather consist in standard programmes for developmental coordination disorder. Here, we compared motor performance in three groups of children: a control group, an autism spectrum disorder group and a developmental coordination disorder group. Despite similar level of motor skills evaluated by the standard movement assessment battery for children, in a Reach-to-Displace Task, children with autism spectrum disorder and developmental coordination disorder showed specific motor control deficits. Children with autism spectrum disorder failed to anticipate the object properties, but could correct their movement as well as typically developing children. In contrast, children with developmental coordination disorder were atypically slow, but showed a spared anticipation. Our study has important clinical implications as motor skills rehabilitations are crucial to both populations. Specifically, our findings suggest that individuals with autism spectrum disorder would benefit from therapies aiming at improving their anticipation, maybe through the support of their preserved representations and use of sensory information. Conversely, individuals with developmental coordination disorder would benefit from a focus on the use of sensory information in a timely fashion.

Synchronous and Fully Steerable Active Particle Systems for Enhanced Mimicking of Collective Motion in Nature

The collective motion observed in living active matter, such as fish schools and bird flocks, is characterized by its dynamic and complex nature, involving various moving states and transitions. By tailoring physical interactions or incorporating information exchange capabilities, inanimate active particles can exhibit similar behavior. However, the lack of synchronous and arbitrary control over individual particles hinders their use as a test system for the study of more intricate collective motions in living species. Herein, a novel optical feedback control system that enables the mimicry of collective motion observed in living objects using active particles is proposed. This system allows for the experimental investigation of the velocity alignment, a seminal model of collective motion (known as the Vicsek model), in a microscale perturbed environment with controllable and realistic conditions. The spontaneous formation of different moving states and dynamic transitions between these states is observed. Additionally, the high robustness of the active-particle group at the critical density under the influence of different perturbations is quantitatively validated. These findings support the effectiveness of velocity alignment in real perturbed environments, thereby providing a versatile platform for fundamental studies on collective motion and the development of innovative swarm microrobotics.

Two parabrachial Cck neurons involved in the feedback control of thirst or salt appetite

Thirst and salt appetite are temporarily suppressed after water and salt ingestion, respectively, before absorption; however, the underlying neural mechanisms remain unclear. The parabrachial nucleus (PBN) is the relay center of ingestion signals from the digestive organs. We herein identify two distinct neuronal populations expressing cholecystokinin (Cck) mRNA in the lateral PBN that are activated in response to water and salt intake, respectively. The two Cck neurons in the dorsal-lateral compartment of the PBN project to the median preoptic nucleus and ventral part of the bed nucleus of the stria terminalis, respectively. The optogenetic stimulation of respective Cck neurons suppresses thirst or salt appetite under water- or salt-depleted conditions. The combination of optogenetics and in vivo Ca2+ imaging during ingestion reveals that both Cck neurons control GABAergic neurons in their target nuclei. These findings provide the feedback mechanisms for the suppression of thirst and salt appetite after ingestion.

Time-delay signature suppression in delayed-feedback semiconductor lasers as a paradigm for feedback control in complex physiological networks

Physiological networks, as observed in the human organism, involve multi-component systems with feedback loops that contribute to self-regulation. Physiological phenomena accompanied by time-delay effects may lead to oscillatory and even chaotic dynamics in their behaviors. Analogous dynamics are found in semiconductor lasers subjected to delayed optical feedback, where the dynamics typically include a time-delay signature. In many applications of semiconductor lasers, the suppression of the time-delay signature is essential, and hence several approaches have been adopted for that purpose. In this paper, experimental results are presented wherein photonic filters utilized in order to suppress time-delay signatures in semiconductor lasers subjected to delayed optical feedback effects. Two types of semiconductor lasers are used: discrete-mode semiconductor lasers and vertical-cavity surface-emitting lasers (VCSELs). It is shown that with the use of photonic filters, a complete suppression of the time-delay signature may be affected in discrete-mode semiconductor lasers, but a remnant of the signature persists in VCSELs. These results contribute to the broader understanding of time-delay effects in complex systems. The exploration of photonic filters as a means to suppress time-delay signatures opens avenues for potential applications in diverse fields, extending the interdisciplinary nature of this study.

Exploration on dynamics in a discrete predator-prey competitive model involving feedback controls

In this work, we set up a new discrete predator-prey competitive model with time-varying delays and feedback controls. By virtue of the difference inequality knowledge, a sufficient condition which guarantees the permanence of the established discrete predator-prey competitive model with time-varying delays and feedback controls is derived. Under some appropriate parameter conditions, we have proved that the periodic solution of the system without delay exists and globally attractive. To verify the correctness of the derived theoretical fruits, we give two examples and execute computer simulations. Our obtained results are novel and complement previous known results.

Impairments of saccadic and reaching adaptation in essential tremor are linked to movement execution

Essential tremor (ET) is a neurological disorder characterized by involuntary oscillations of the limbs. Previous studies have hypothesized that ET is a cerebellar disorder and reported impairments in motor adaptation. However, recent advances have highlighted that motor adaptation involves several components linked to anticipation and control, all dependent on cerebellum. We studied the contribution of both components in adaptation to better understand the adaptation impairments observed in ET from a behavioral perspective. To address this question, we investigated behavioral markers of adaptation in ET patients (n = 20) and age-matched neurologically intact volunteers (n = 20) in saccadic and upper limb adaptation tasks, probing compensation for target jumps and for velocity-dependent force fields, respectively. We found that both groups adapted their movements to the novel contexts; however, ET patients adapted to a lesser extent compared with neurologically intact volunteers. Importantly, components of the movement linked to anticipation were preserved in the ET group, whereas components linked to movement execution appeared responsible for the adaptation deficit in this group. Altogether, our results suggest that execution deficits may be a specific functional consequence of the alteration of neural pathways associated with ET.NEW & NOTEWORTHY We tested essential tremor patients' adaptation abilities in classical tasks including saccadic adaptation to target jumps and reaching adaptation to force field disturbances. Patients' adaptation was present but impaired in both tasks. Interestingly, the deficits were mainly present during movement execution, whereas the anticipatory components of movements were similar to neurologically intact volunteers. These findings reinforce the hypothesis of a cerebellar origin for essential tremor and detail the motor adaptation impairments previously found in this disorder.

Model-Based Feedback Control for an Automated Micro Liquid Dispensing System Based on Contacting Droplet Generation through Image Sensing

Over the past few decades, micro liquid dispensing technology has been widely used in biology, chemistry, material and environmental sciences due to its efficacy in processing multiple samples. For practical applications, precise and effective droplet generation is very important. Despite numerous droplet generation methods, the implementation of droplet-on-demand still faces challenges concerning system complexity, precision, cost, and robustness. In this work, a novel on-demand contacting droplet generation method incorporated with model-based feedback control with an image processing unit as a sensor was proposed. By studying droplet identification using image processing techniques, the model of droplet formation was simplified. Then model-based feedback control was implemented using volumes of dispensed samples as sensing signals by tuning related parameters adaptively to resist disturbances. The proposed method was integrated and applied to a homebuilt automated micro liquid dispensing system with droplets ranging from 20 nanoliter to 200 nanoliter. The experimental results demonstrated a high degree of accuracy and precision. Additionally, the proposed system's practical utility was evaluated by analyzing mutations in genes associated with sensorineural hearing loss, verifying its effectiveness.

Flies adaptively control flight to compensate for added inertia

Animal locomotion is highly adaptive, displaying a large degree of flexibility, yet how this flexibility arises from the integration of mechanics and neural control remains elusive. For instance, animals require flexible strategies to maintain performance as changes in mass or inertia impact stability. Compensatory strategies to mechanical loading are especially critical for animals that rely on flight for survival. To shed light on the capacity and flexibility of flight neuromechanics to mechanical loading, we pushed the performance of fruit flies (Drosophila) near its limit and implemented a control theoretic framework. Flies with added inertia were placed inside a virtual reality arena which permitted free rotation about the vertical (yaw) axis. Adding inertia increased the fly's response time yet had little influence on overall gaze stabilization performance. Flies maintained stability following the addition of inertia by adaptively modulating both visuomotor gain and damping. By contrast, mathematical modelling predicted a significant decrease in gaze stabilization performance. Adding inertia altered saccades, however, flies compensated for the added inertia by increasing saccade torque. Taken together, in response to added inertia flies increase reaction time but maintain flight performance through adaptive neural control. Overall, adding inertia decreases closed-loop flight robustness. Our work highlights the flexibility and capacity of motor control in flight.

Modeling Human Suboptimal Control: A Review

This review paper provides an overview of the approaches to model neuromuscular control, focusing on methods to identify nonoptimal control strategies typical of populations with neuromuscular disorders or children. Where possible, the authors tightened the description of the methods to the mechanisms behind the underlying biomechanical and physiological rationale. They start by describing the first and most simplified approach, the reductionist approach, which splits the role of the nervous and musculoskeletal systems. Static optimization and dynamic optimization methods and electromyography-based approaches are summarized to highlight their limitations and understand (the need for) their developments over time. Then, the authors look at the more recent stochastic approach, introduced to explore the space of plausible neural solutions, thus implementing the uncontrolled manifold theory, according to which the central nervous system only controls specific motions and tasks to limit energy consumption while allowing for some degree of adaptability to perturbations. Finally, they explore the literature covering the explicit modeling of the coupling between the nervous system (acting as controller) and the musculoskeletal system (the actuator), which may be employed to overcome the split characterizing the reductionist approach.

Mind your heart to bear the weight: Cardiac interoception predicts action-related visual perception when wearing a heavy backpack

Visual perception can be modulated by the physiological potential for action. For instance, it was famously shown that a geographical slant appears steeper when wearing a heavy backpack than not wearing any. However, those results are not always replicated. In the present exploratory study, we test the hypothesis that the backpack weight's effect on perception relies on the ability of the cognitive system to integrate the physiological constraint's change rather than the change itself. Young adults (n = 54) wore an electrocardiogram monitor and completed a computerised task in which photographs of real geographical slants were displayed on a screen while wearing a heavy versus light backpack. The activity of the vagus nerve, as an index of physiological adaptability, was recorded as a proxy of the physiological state during the task. The participants also completed an interoception task assessing one's ability to detect his or her own heartbeat as the index of integration ability of the cognitive system. While Bayesian analyses revealed no difference in angle estimation between carrying a heavy versus light backpack, the results indicated that interoception predicted less accurate angle estimation only when wearing a heavy backpack. In contrast, there was anecdotal evidence that vagal activity changes predicted visual perception. Interoception might thus play a crucial role in the interplay between the physiological potential for action and action-related visual perception.

Stabilizing leaning postures with feedback controlled functional neuromuscular stimulation after trunk paralysis

Spinal cord injury (SCI) can cause paralysis of trunk and hip musculature that negatively impacts seated balance and ability to lean away from an upright posture and interact fully with the environment. Constant levels of electrical stimulation of peripheral nerves can activate typically paralyzed muscles and aid in maintaining a single upright seated posture. However, in the absence of a feedback controller, such seated postures and leaning motions are inherently unstable and unable to respond to perturbations. Three individuals with motor complete SCI who had previously received a neuroprosthesis capable of activating the hip and trunk musculature volunteered for this study. Subject-specific muscle synergies were identified through system identification of the lumbar moments produced via neural stimulation. Synergy-based calculations determined the real-time stimulation parameters required to assume leaning postures. When combined with a proportional, integral, derivative (PID) feedback controller and an accelerometer to infer trunk orientation, all individuals were able to assume non-erect postures of 30-40° flexion and 15° lateral bending. Leaning postures increased forward reaching capabilities by 10.2, 46.7, and 16 cm respectively for each subject when compared with no stimulation. Additionally, the leaning controllers were able to resist perturbations of up to 90 N, and all subjects perceived the leaning postures as moderately to very stable. Implementation of leaning controllers for neuroprostheses have the potential of expanding workspaces, increasing independence, and facilitating activities of daily living for individuals with paralysis.

Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling

A fuzzy PI controller was utilized to realize the modal matching between a driving and detecting model. A simulation model was built to study electrostatic decoupling controlling technology. The simulation results show that the modal matching can be gained by the fuzzy PI controller. The frequency difference between the driving mode and the detection mode is less than 1 Hz, and the offset of the input DC is smaller than 0.6 V. The optimal proportionality factor and integral coefficient are 1.5 and 20, respectively. The fuzzy PI controlling technology provides a good way for the parameter optimization to gain modal matching of micro gyro, via which the detecting accuracy and stability can be improved greatly.

A sensorless, physiologic feedback control strategy to increase vascular pulsatility for rotary blood pumps

Continuous flow rotary blood pumps (RBP) operating clinically at constant rotational speeds cannot match cardiac demand during varying physical activities, are susceptible to suction, diminish vascular pulsatility, and have an increased risk of adverse events. A sensorless, physiologic feedback control strategy for RBP was developed to mitigate these limitations. The proposed algorithm used intrinsic pump speed to obtain differential pump speed (ΔRPM). The proposed gain-scheduled proportional-integral controller, switching of setpoints between a higher pump speed differential setpoint (ΔRPM Hr ) and a lower pump speed differential setpoint (ΔRPM Lr ), generated pulsatility and physiologic perfusion, while avoiding suction. The switching between ΔRPM Hr and ΔRPM Lr setpoints occurred when the measured ΔRPM reached the pump differential reference setpoint. In-silico tests were implemented to assess the proposed algorithm during rest, exercise, a rapid 3-fold pulmonary vascular resistance increase, rapid change from exercise to rest, and compared with maintaining a constant pump speed setpoint. The proposed control algorithm augmented aortic pressure pulsatility to over 35 mmHg during rest and around 30 mmHg during exercise. Significantly, ventricular suction was avoided, and adequate cardiac output was maintained under all simulated conditions. The performance of the sensorless algorithm using estimation was similar to the performance of sensor-based method. This study demonstrated that augmentation of vascular pulsatility was feasible while avoiding ventricular suction and providing physiological pump outflows. Augmentation of vascular pulsatility can minimize adverse events that have been associated with diminished pulsatility. Mock circulation and animal studies would be conducted to validate these results.

Peripheral and central sensation: multisensory orienting and recognition across species

Attentional bottlenecks force animals to deeply process only a selected fraction of sensory inputs. This motivates a unifying central-peripheral dichotomy (CPD), which separates multisensory processing into functionally defined central and peripheral senses. Peripheral senses (e.g., human audition and peripheral vision) select a fraction of the sensory inputs by orienting animals' attention; central senses (e.g., human foveal vision) allow animals to recognize the selected inputs. Originally used to understand human vision, CPD can be applied to multisensory processes across species. I first describe key characteristics of central and peripheral senses, such as the degree of top-down feedback and density of sensory receptors, and then show CPD as a framework to link ecological, behavioral, neurophysiological, and anatomical data and produce falsifiable predictions.

Late integration of vision and proprioception during perturbed reaches

The motor system corrects rapidly, but selectively, for perturbations to ongoing reaching movements, depending on the constraints of the task. To account for such sophistication, it has been postulated that corrections are based on an estimated limb state that integrates all sensory changes caused by the perturbation, taking into account their processing delays.Here we asked if information from different sensory modalities is integrated immediately, or processed separately in the early phase of a response. We perturbed the estimated state of the limb with both uni-modal and bi-modal visual and proprioceptive perturbations without changing the actual limb state. For visual perturbations, a cursor representing the hand was shifted to the left or the right relative to the true hand location. For proprioceptive perturbations, the biceps or triceps muscles were vibrated, which induced illusory limb state changes to the right or the left. In the bimodal condition the perturbations to vision and proprioception were either congruent or incongruent in their directions.Response latencies show that it takes ~100 ms longer to respond to unimodal visual perturbations than to unimodal proprioceptive perturbations. Responses to bimodal perturbations show that it takes an additional ~100 ms beyond the response to unimodal visual perturbations for inter-modal consistency to impact the response. These results suggest that visual and proprioceptive signals are initially processed separately for state estimation and only combined at the level of the limb's motor output, instead of being immediately integrated into a single state estimate of the limb.

Nonlinear three-dimensional patterns of the Marangoni convection in a thin film on a poorly conducting substrate

We investigate the dynamics of a thin liquid film that is placed atop a heated substrate of very low thermal conductivity. The direct numerical simulation of the stationary long-wave Marangoni instability is performed with the system of coupled partial differential equations. These equations were previously derived within the lubrication approximation; they describe the evolution of film thickness and fluid temperature. We compare our results with the early reported results of the weakly nonlinear analysis. A good qualitative agreement is observed for values of the Marangoni number near the convective threshold. In the case of supercritical excitation, our results for the amplitudes are described by the square root dependence on the supercriticality. In the case of subcritical excitation, we report the hysteresis. For relatively high supercriticality, the convective regimes evolve into film rupture via the emergence of secondary humps. For the three-dimensional patterns, we observe rolls or squares, depending on the problem parameters. We also confirm the prediction of the asymptotic results concerning the nonlinear feedback control for the pattern selection. This article is part of the theme issue 'New trends in pattern formation and nonlinear dynamics of extended systems'.

A Theoretical Framework for Implementable Nucleic Acids Feedback Systems

Chemical reaction networks can be utilised as basic components for nucleic acid feedback control systems' design for Synthetic Biology application. DNA hybridisation and programmed strand-displacement reactions are effective primitives for implementation. However, the experimental validation and scale-up of nucleic acid control systems are still considerably falling behind their theoretical designs. To aid with the progress heading into experimental implementations, we provide here chemical reaction networks that represent two fundamental classes of linear controllers: integral and static negative state feedback. We reduced the complexity of the networks by finding designs with fewer reactions and chemical species, to take account of the limits of current experimental capabilities and mitigate issues pertaining to crosstalk and leakage, along with toehold sequence design. The supplied control circuits are quintessential candidates for the first experimental validations of nucleic acid controllers, since they have a number of parameters, species, and reactions small enough for viable experimentation with current technical capabilities, but still represent challenging feedback control systems. They are also well suited to further theoretical analysis to verify results on the stability, performance, and robustness of this important new class of control systems.

Inhibition of knee joint sensory afferents alters covariation across strides between quadriceps muscles during locomotion

Sport-related injuries to articular structures often alter the sensory information conveyed by joint structures to the nervous system. However, the role of joint sensory afferents in motor control is still unclear. Here, we evaluate the role of knee joint sensory afferents in the control of quadriceps muscles, hypothesizing that such sensory information modulates control strategies that limit patellofemoreal joint loading. We compared locomotor kinematics and muscle activity before and after inhibition of knee sensory afferents by injection of lidocaine into the knee capsule of rats. We evaluated whether this inhibition reduced the strength of correlation between the activity of vastus medialis (VM) and vastus lateralis (VL) both across strides and within each stride, coordination patterns that limit net mediolateral patellofemoral forces. We also evaluated whether this inhibition altered correlations among the other quadriceps muscle activity, the time-profiles of individual EMG envelopes, or movement kinematics. Neither the EMG envelopes nor limb kinematics was affected by the inhibition of knee sensory afferents. This perturbation also did not affect the correlations between VM and VL, suggesting that the regulation of patellofemoral joint loading is mediated by different mechanisms. However, inhibition of knee sensory afferents caused a significant reduction in the correlation between vastus intermedius (VI) and both VM and VL across, but not within, strides. Knee joint sensory afferents may therefore modulate the coordination between the vasti muscles but only at coarse time scales. Injuries compromising joint afferents might result in altered muscle coordination, potentially leading to persistent internal joint stresses and strains.NEW & NOTEWORTHY Sensory afferents originating from knee joint receptors provide the nervous system with information about the internal state of the joint. In this study, we show that these sensory signals are used to modulate the covariations among the activity of a subset of vasti muscles across strides of locomotion. Sport-related injuries that damage joint receptors may therefore compromise these mechanisms of muscle coordination, potentially leading to persistent internal joint stresses and strains.

Inflammation-Controlled Anti-Inflammatory Hydrogels

While autoregulative adaptation is a common feature of living tissues, only a few feedback-controlled adaptive biomaterials are available so far. This paper herein reports a new polymer hydrogel platform designed to release anti-inflammatory molecules in response to the inflammatory activation of human blood. In this system, anti-inflammatory peptide drugs, targeting either the complement cascade, a complement receptor, or cyclophilin A, are conjugated to the hydrogel by a peptide sequence that is cleaved by elastase released from activated granulocytes. As a proof of concept, the adaptive drug delivery from the gel triggered by activated granulocytes and the effect of the released drug on the respective inflammatory pathways are demonstrated. Adjusting the gel functionalization degree is shown to allow for tuning the drug release profiles to effective doses within a micromolar range. Feedback-controlled delivery of covalently conjugated drugs from a hydrogel matrix is concluded to provide valuable safety features suitable to equip medical devices with highly active anti-inflammatory agents without suppressing the general immunosurveillance.

Review of Intelligence for Additive and Subtractive Manufacturing: Current Status and Future Prospects

Additive manufacturing (AM), an enabler of Industry 4.0, recently opened limitless possibilities in various sectors covering personal, industrial, medical, aviation and even extra-terrestrial applications. Although significant research thrust is prevalent on this topic, a detailed review covering the impact, status, and prospects of artificial intelligence (AI) in the manufacturing sector has been ignored in the literature. Therefore, this review provides comprehensive information on smart mechanisms and systems emphasizing additive, subtractive and/or hybrid manufacturing processes in a collaborative, predictive, decisive, and intelligent environment. Relevant electronic databases were searched, and 248 articles were selected for qualitative synthesis. Our review suggests that significant improvements are required in connectivity, data sensing, and collection to enhance both subtractive and additive technologies, though the pervasive use of AI by machines and software helps to automate processes. An intelligent system is highly recommended in both conventional and non-conventional subtractive manufacturing (SM) methods to monitor and inspect the workpiece conditions for defect detection and to control the machining strategies in response to instantaneous output. Similarly, AM product quality can be improved through the online monitoring of melt pool and defect formation using suitable sensing devices followed by process control using machine learning (ML) algorithms. Challenges in implementing intelligent additive and subtractive manufacturing systems are also discussed in the article. The challenges comprise difficulty in self-optimizing CNC systems considering real-time material property and tool condition, defect detections by in-situ AM process monitoring, issues of overfitting and underfitting data in ML models and expensive and complicated set-ups in hybrid manufacturing processes.

Individually adjusted absolute blood volume feedback control: A promising solution for intradialytic hypotension

INTRODUCTION

Intradialytic hypotension (IDH) remains one of the most frequent complications associated to hemodialysis (HD), frequently triggered by a reduction in absolute blood volume (ABV) not compensated by vascular refilling. A recently developed dilutional method allows routinary measurement of ABV and, by a simple algorithm, may turn blood volume monitor (BVM) guided UF (ultrafiltration) biofeedback into an ABV control, automatically adjusting UF rate to maintain ABV above a preset threshold. The aim of this study is to identify an individual critical ABV threshold and test the ability of an ABV feedback control to avoid IDH.

METHODS

We studied 24 patients throughout three consecutive midweek HD treatments. ABV and blood pressure (BP) were measured every 30 min and anytime the patient referred any symptoms to identify each patient's critical ABV (ABV at the time of hypotension). A fixed bolus dilution approach at the start of HD was used to calculate ABV. Then, patients were followed through three additional HD treatments and IDH development was analyzed.

FINDINGS

Seventy-one treatments performed in 24 patients. ABV monitoring showed a constant decrease as HD treatment progressed. Thirteen IDH events were observed in eight different patients, with a mean systolic BP drop in IDH treatments of 37.38 ± 4.31 mmHg and a mean adjusted ABV at hypotension of 71.07 ± 14.88 mL/kg. Critical ABV was individually set in patients prone to IDH. As expected, ABV feedback control successfully maintained ABV over preset critical ABV. IDH events were avoided in 21 out of 22 treatments performed. ABV drop was successfully reduced, as well as SBP drop (despite similar UF than prior to ABV feedback control implementation).

DISCUSSION

ABV feedback control avoided IDH in 21 out of 22 treatments performed by maintaining blood volume above critical ABV, significantly reducing ABV variations without compromising prescribed UF.

Design of an Integrated Controller for a Sweeping Mechanism of a Low-Dust Almond Pickup Machine

California is the world's biggest producer and exporter of almonds. Currently, the sweeping of almonds during the harvest creates a significant amount of dust, causing air pollution in the neighboring urban areas. A low-dust sweeping system was designed to reduce the dust during the sweeping of almonds in the orchard. The system includes a feedback control system to control the sweeper brushes' height and their angular velocity by adjusting the forward velocity of the harvester and the brushes' rotational speeds to avoid any extra overlapping sweeping, which increases dust generation. The governing kinematic equations for sweepers' angular velocity and vehicle forward speed were derived. The feedback controllers for synchronizing these speeds were designed to optimize brush/dust contact to minimize dust generation. The sweepers' height controller was also designed to stabilize the gap between the brushes and the orchard floor and track the road trajectory. Controllers were simulated and tuned for a fast response for agricultural applications with less than a second response delay. Results showed that the designed system has acceptable performance and generates low amounts of dust within the acceptable range of California ambient air quality standards.

A Morphing Point-to-Point Displacement Control Based on Long Short-Term Memory for a Coplanar XXY Stage

In this study, visual recognition with a charge-coupled device (CCD) image feedback control system was used to record the movement of a coplanar XXY stage. The position of the stage is fedback through the image positioning method, and the positioning compensation of the stage is performed by the image compensation control parameter. The image resolution was constrained and resulted in an average positioning error of the optimized control parameter of 6.712 µm, with the root mean square error being 2.802 µm, and the settling time being approximately 7 s. The merit of a long short-term memory (LSTM) deep learning model is that it can identify long-term dependencies and sequential state data to determine the next control signal. As for improving the positioning performance, LSTM was used to develop a training model for stage motion with an additional dial indicator with an accuracy of 1 μm being used to record the XXY position information. After removing the assisting dial indicator, a new LSTM-based XXY feedback control system was subsequently constructed to reduce the positioning error. In other words, the morphing control signals are dependent not only on time, but also on the iterations of the LSTM learning process. Point-to-point commanded forward, backward and repeated back-and-forth repetitive motions were conducted. Experimental results revealed that the average positioning error achieved after using the LSTM model was 2.085 µm, with the root mean square error being 2.681 µm, and a settling time of 2.02 s. With the assistance of LSTM, the stage exhibited a higher control accuracy and less settling time than did the CCD imaging system according to three positioning indices.

The flagellar length control system: exploring the physical biology of organelle size

How cells build and maintain dynamic structures of defined size is currently an important unsolved problem in quantitative cell biology. The flagella of the unicellular green algaChlamydomonasprovide a highly tractable model system to investigate this general question, but while the powerful genetics of this organism have revealed numerous genes required for proper flagellar length, in most cases we do not understand their mechanistic role in length control. Flagellar length can be viewed as the steady state solution of a dynamical system involving assembly and disassembly of axonemal microtubules, with assembly depending on an active transport process known as intraflagellar transport (IFT). The inherent length dependence of IFT gives rise to a family of simple models for length regulation that can account for many previously described phenomena such as the ability of flagella to maintain equal lengths. But these models requires that the cell has a way to measure flagellar length in order to adjust IFT rates accordingly. Several models for length sensing have been modeled theoretically and evaluated experimentally, allowing them to be ruled out. Current data support a model in which the diffusive return of the kinesin motor driving IFT provides a length dependence that ultimately is the basis for length regulation. By combining models of length sensing with a more detailed representation of cargo transport and availability, it is now becoming possible to formulate concrete hypotheses to explain length altering mutants.

Learning Observer-Based Sensor Fault-Tolerant Control of Distributed Generation in an Islanded Microgrid for Bus Voltage Stability Enhancement

In order to improve robust operating performance and enhance bus voltage stability, a learning observer-based fault-tolerant control strategy is proposed for the distributed generation in islanded microgrid with sensor faults and uncertain disturbances. Firstly, the output feedback control theory and the linear matrix inequality method are used to design closed-loop controller for the voltage source inverter of distributed generation; secondly, a fault-tolerant model and control structure of the distributed generation in an islanded microgrid with sensor faults is analyzed. By employing the fault output signal conversion filter and proportional derivative type learning observer, the online estimation and real-time compensation of the sensor fault signal are realized. Thirdly, the system synthesis of output feedback control and fault-tolerant control is completed. Finally, the multi-scenario sensor fault scheme simulation experiment verifies that the proposed control strategy has strong sensor fault tolerance and adaptability.

Research on Safety Interlock System Design and Control Experiment of Combined Support and Anchor Equipment

In view of the risk of collision with humans or equipment arising from a lack of protection in the operation process of combined support and anchor equipment on the heading face, this paper designs a safety interlock system for combined support and anchor equipment. Firstly, a mathematical model of hydraulic power system control and a valve control system based on feedforward-feedback optimization were established according to the power demand of the combined support and anchor equipment. Secondly, according to the reliability indexes of the safety interlock system, corresponding sensor, logic control and execution modules were designed. Ultrasonic sensor groups were arranged at the key positions of the combined support and anchor equipment to capture the position information in real time when the equipment was moving. Thus, the pump-valve hydraulic system was controlled through closed-loop feedback. The experimental results show that the safety interlock system of the combined support and anchor equipment can adjust the revolving speed of the permanent magnet synchronous motor (PMSM) in real time according to the distance from the obstacle, so as to control the pump outlet flow, and then perform interlocking safety control of the hydraulic cylinder's movement speed. The system can effectively prevent damage to the surrounding equipment or personnel arising from equipment malfunction.

The drug titration paradox: more drug does not correlate with more effect in individual clinical data

BACKGROUND

A fundamental concept in pharmacology is that increasing dose increases drug effect. This is the basis of anaesthetic titration: the dose is increased when increased drug effect is desired and decreased when reduced drug effect is desired. In the setting of titration, the correlation of doses and observed drug effects can be negative, for example increasing dose reduces drug effect. We have termed this the drug titration paradox. We hypothesised that this could be explained, at least in part, by intrasubject variability. If the drug titration paradox is simply an artifact of pooling population data, then a mixed-effects analysis that accounts for interindividual variability in drug sensitivity should 'flip' the observed correlation, such that increasing dose increases drug effect.

METHODS

We tested whether a mixed-effects analysis could correctly reveal the underlying pharmacology using previously published data obtained during automatic feedback control of mean arterial pressure (MAP) with alfentanil (effect site concentration, Ce_Alf) during surgery. The relationship between MAP and Ce_Alf was explored with linear regression and a linear mixed-effects model.

RESULTS

A linear mixed-effects model did not identify the correct underlying pharmacology because of the presence of the titration paradox in the individual data.

CONCLUSIONS

The relationship between drug dose and drug effect must be determined under carefully controlled experimental conditions. In routine care, where the effect is profoundly influenced by varying clinical conditions and drugs are titrated to achieve the desired effect, it is nearly impossible to draw meaningful conclusions about the relationship between dose and effect.

Strengthened second law for multi-dimensional systems coupled to multiple thermodynamic reservoirs

The second law of thermodynamics can be formulated as a restriction on the evolution of the entropy of any system undergoing Markovian dynamics. Here I show that this form of the second law is strengthened for multi-dimensional, complex systems, coupled to multiple thermodynamic reservoirs, if we have a set of a priori constraints restricting how the dynamics of each coordinate can depend on the other coordinates. As an example, this strengthened second law (SSL) applies to complex systems composed of multiple physically separated, co-evolving subsystems, each identified as a coordinate of the overall system. In this example, the constraints concern how the dynamics of some subsystems are allowed to depend on the states of the other subsystems. Importantly, the SSL applies to such complex systems even if some of its subsystems can change state simultaneously, which is prohibited in a multipartite process. The SSL also strengthens previously derived bounds on how much work can be extracted from a system using feedback control, if the system is multi-dimensional. Importantly, the SSL does not require local detailed balance. So it potentially applies to complex systems ranging from interacting economic agents to co-evolving biological species. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Strengthened second law for multi-dimensional systems coupled to multiple thermodynamic reservoirs

The second law of thermodynamics can be formulated as a restriction on the evolution of the entropy of any system undergoing Markovian dynamics. Here I show that this form of the second law is strengthened for multi-dimensional, complex systems, coupled to multiple thermodynamic reservoirs, if we have a set of a priori constraints restricting how the dynamics of each coordinate can depend on the other coordinates. As an example, this strengthened second law (SSL) applies to complex systems composed of multiple physically separated, co-evolving subsystems, each identified as a coordinate of the overall system. In this example, the constraints concern how the dynamics of some subsystems are allowed to depend on the states of the other subsystems. Importantly, the SSL applies to such complex systems even if some of its subsystems can change state simultaneously, which is prohibited in a multipartite process. The SSL also strengthens previously derived bounds on how much work can be extracted from a system using feedback control, if the system is multi-dimensional. Importantly, the SSL does not require local detailed balance. So it potentially applies to complex systems ranging from interacting economic agents to co-evolving biological species. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Platforms for Optogenetic Stimulation and Feedback Control

Harnessing the potential of optogenetics in biology requires methodologies from different disciplines ranging from biology, to mechatronics engineering, to control engineering. Light stimulation of a synthetic optogenetic construct in a given biological species can only be achieved via a suitable light stimulation platform. Emerging optogenetic applications entail a consistent, reproducible, and regulated delivery of light adapted to the application requirement. In this review, we explore the evolution of light-induction hardware-software platforms from simple illumination set-ups to sophisticated microscopy, microtiter plate and bioreactor designs, and discuss their respective advantages and disadvantages. Here, we examine design approaches followed in performing optogenetic experiments spanning different cell types and culture volumes, with induction capabilities ranging from single cell stimulation to entire cell culture illumination. The development of automated measurement and stimulation schemes on these platforms has enabled researchers to implement various in silico feedback control strategies to achieve computer-controlled living systems—a theme we briefly discuss in the last part of this review.

Postural Control Adaptations in Yoga Single-Leg Support Postures: Comparison Between Practitioners and Nonpractitioners

This paper investigates whether a group of regular Yoga practitioners shows postural control differences compared with healthy controls while performing single-leg Yoga postures. Ten Yoga practitioners were compared with a control group of 10 nonpractitioners performing two single-leg support Yoga postures: Vrksasana (tree posture) and Natarajasana (dancer posture). Rambling and trembling decomposition of the center of pressure trajectories was implemented using a genetic algorithm spectral optimization that avoids using horizontal forces and was validated with bipedal posture data. Additionally, the center of mass was estimated from body kinematics using OpenSim and compared with the rambling outputs. During Natarajasana, no postural control adaptations were observed. For Vrksasana, the Yoga practitioners showed a lower center of pressure ellipse confidence interval area, center of pressure anteroposterior SD, and smaller rambling SD in the mediolateral direction, suggesting possible supraspinal feed-forward motor adaptations associated with Yoga training.

A feedback control principle common to several biological and engineered systems

Feedback control is used by many distributed systems to optimize behaviour. Traditional feedback control algorithms spend significant resources to constantly sense and stabilize a continuous control variable of interest, such as vehicle speed for implementing cruise control, or body temperature for maintaining homeostasis. By contrast, discrete-event feedback (e.g. a server acknowledging when data are successfully transmitted, or a brief antennal interaction when an ant returns to the nest after successful foraging) can reduce costs associated with monitoring a continuous variable; however, optimizing behaviour in this setting requires alternative strategies. Here, we studied parallels between discrete-event feedback control strategies in biological and engineered systems. We found that two common engineering rules—additive-increase, upon positive feedback, and multiplicative-decrease, upon negative feedback, and multiplicative-increase multiplicative-decrease—are used by diverse biological systems, including for regulating foraging by harvester ant colonies, for maintaining cell-size homeostasis, and for synaptic learning and adaptation in neural circuits. These rules support several goals of these systems, including optimizing efficiency (i.e. using all available resources); splitting resources fairly among cooperating agents, or conversely, acquiring resources quickly among competing agents; and minimizing the latency of responses, especially when conditions change. We hypothesize that theoretical frameworks from distributed computing may offer new ways to analyse adaptation behaviour of biology systems, and in return, biological strategies may inspire new algorithms for discrete-event feedback control in engineering.

Adaptive Feedback Control in Human Reaching Adaptation to Force Fields

Sensorimotor adaptation is a central function of the nervous system, as it allows humans and other animals to flexibly anticipate their interaction with the environment. In the context of human reaching adaptation to force fields, studies have traditionally separated feedforward (FF) and feedback (FB) processes involved in the improvement of behavior. Here, we review computational models of FF adaptation to force fields and discuss them in light of recent evidence highlighting a clear involvement of feedback control. Instead of a model in which FF and FB mechanisms adapt in parallel, we discuss how online adaptation in the feedback control system can explain both trial-by-trial adaptation and improvements in online motor corrections. Importantly, this computational model combines sensorimotor control and short-term adaptation in a single framework, offering novel perspectives for our understanding of human reaching adaptation and control.

Sensory feedback can give rise to neural rotations

Investigating how an artificial network of neurons controls a simulated arm suggests that rotational patterns of activity in the motor cortex may rely on sensory feedback from the moving limb.

A feedback control architecture for bioelectronic devices with applications to wound healing

Bioelectronic devices can provide an interface for feedback control of biological processes in real-time based on sensor information tracking biological response. The main control challenges are guaranteeing system convergence in the presence of saturating inputs into the bioelectronic device and complexities from indirect control of biological systems. In this paper, we first derive a saturated-based robust sliding mode control design for a partially unknown nonlinear system with disturbance. Next, we develop a data informed model of a bioelectronic device for in silico simulations. Our controller is then applied to the model to demonstrate controlled pH of a target area. A modular control architecture is chosen to interface the bioelectronic device and controller with a bistable phenomenological model of wound healing to demonstrate closed-loop biological treatment. External pH is regulated by the bioelectronic device to accelerate wound healing, while avoiding chronic inflammation. Our novel control algorithm for bioelectronic devices is robust and requires minimum information about the device for broad applicability. The control architecture makes it adaptable to any biological system and can be used to enhance automation in bioengineering to improve treatments and patient outcomes.

Mathematical model of the auditory nerve response to stimulation by a micro-machined cochlea

We report a novel mathematical model of an artificial auditory system consisting of a micro-machined cochlea and the auditory nerve response it evokes. The modeled micro-machined cochlea is one previously realized experimentally by mimicking functions of the cochlea [Shintaku et al, Sens. Actuat. 158 (2010) 183-192; Inaoka et al, Proc. Natl. Acad. Sci. USA 108 (2011) 18390-18395]. First, from the viewpoint of mechanical engineering, the frequency characteristics of a model device were experimentally investigated to develop an artificial basilar membrane based on a spring-mass-damper system. In addition, a nonlinear feedback controller mimicking the function of the outer hair cells was incorporated in this experimental system. That is, the developed device reproduces the proportional relationship between the oscillation amplitude of the basilar membrane and the cube root of the sound pressure observed in the mammalian auditory system, which is what enables it to have a wide dynamic range, and the characteristics of the control performance were evaluated numerically and experimentally. Furthermore, the stimulation of the auditory nerve by the micro-machined cochlea was investigated using the present mathematical model, and the simulation results were compared with our previous experimental results from animal testing [Shintaku et al, J. Biomech. Sci. Eng. 8 (2013) 198-208]. The simulation results were found to be in reasonably good agreement with those from the previous animal test; namely, there exists a threshold at which the excitation of the nerve starts and a saturation value for the firing rate under a large input. The proposed numerical model was able to qualitatively reproduce the results of the animal test with the micro-machined cochlea and is thus expected to guide the evaluation of micro-machined cochleae for future animal experiments.

Fixed-Time Synchronization Control of Delayed Dynamical Complex Networks

Fixed-time synchronization problem for delayed dynamical complex networks is explored in this paper. Compared with some correspondingly existed results, a few new results are obtained to guarantee fixed-time synchronization of delayed dynamical networks model. Moreover, by designing adaptive controller and discontinuous feedback controller, fixed-time synchronization can be realized through regulating the main control parameter. Additionally, a new theorem for fixed-time synchronization is used to reduce the conservatism of the existing work in terms of conditions and the estimate of synchronization time. In particular, we obtain some fixed-time synchronization criteria for a type of coupled delayed neural networks. Finally, the analysis and comparison of the proposed controllers are given to demonstrate the validness of the derived results from one numerical example.

Optimization and feedback control system of dilution rate for 1,3-propanediol in two-stage fermentation: A theoretical study

In utilizing glycerol to produce 1,3-propanediol by microbial fermentation, the problems of low utilization rate and poor production performance need to be addressed. Based on the analysis of a mathematical model for 1,3-propanediol production from glycerol by Klebsiella pneumoniae, this study theoretically investigated the effects of the dilution rate and the initial glycerol concentration in a two-stage fermentation process and the feasibility of applying the feedback control methods. First, the optimal operation conditions of initial glycerol concentration and dilution rate were obtained. Through the use of feedback control theory, a control strategy for dilution rate was designed and optimized to shorten the settling time (time required for fermentation to reach stability) from 60.92 to 36.68 h for the first reactor, and from 53.66 to 22.68 h for the second reactor. In addition, the yield of 1,3-propanediol in both two reactors reached up to 0.5 g·g^-1 . The simulation results indicated that the feedback control strategy for dilution rate increased the product concentration, reduced the residual glycerol in the fermentation broth, and greatly improved the performance of the fermentation. A feeding strategy of automatic control for dilution rate has been established and will be applied as an effective guiding scheme in automatic continuous fermentations for production of 1,3-propanediol.

Rotational dynamics in motor cortex are consistent with a feedback controller

Recent studies have identified rotational dynamics in motor cortex (MC), which many assume arise from intrinsic connections in MC. However, behavioral and neurophysiological studies suggest that MC behaves like a feedback controller where continuous sensory feedback and interactions with other brain areas contribute substantially to MC processing. We investigated these apparently conflicting theories by building recurrent neural networks that controlled a model arm and received sensory feedback from the limb. Networks were trained to counteract perturbations to the limb and to reach toward spatial targets. Network activities and sensory feedback signals to the network exhibited rotational structure even when the recurrent connections were removed. Furthermore, neural recordings in monkeys performing similar tasks also exhibited rotational structure not only in MC but also in somatosensory cortex. Our results argue that rotational structure may also reflect dynamics throughout the voluntary motor system involved in online control of motor actions.

Motor skill training without online visual feedback enhances feedforward control

Motor skill learning involves improvement in feedforward control, the ability to execute a motor plan more reliably, and feedback control, the ability to adjust the motor plan on the fly. The dependence between these control components and the association between training conditions and their improvement have not been directly examined. This study characterizes the contribution of feedforward and feedback control components to motor skill learning using the arc-pointing task (APT), a drawing task that requires high motor acuity. In experiment 1, the performance of three groups of subjects was tested before and after training with online visual feedback (OF group), with knowledge of performance feedback that was presented after movement completion (KP group), and with both online and KP feedback (KP + OF group). Although the improvement of the OF group was not different from the improvement of the KP + OF group, comparison of the KP and KP + OF groups revealed an advantage to the KP group in the fast test speed, suggesting that training without online feedback leads to a greater improvement in feedforward control. In experiment 2, subject's improvement was examined using test probes for estimating feedback and feedforward control. Both KP + OF and KP groups showed improvement in feedforward and feedback conditions with a trend toward a greater improvement of the KP group. Our results suggest that online visual feedback suppresses improvement in feedforward control during motor skill learning.NEW & NOTEWORTHY Becoming a skillful player requires both executing reliable movements and being able to efficiently control them online. We study here how training with and without online visual feedback affects feedforward and feedback control improvement in a drawing task that requires high precision. We show that training with online feedback suppresses improvement in feedforward control and leads to inferior performance in fast movements.

Differential Effects of Cerebellar Degeneration on Feedforward versus Feedback Control across Speech and Reaching Movements

Errors that result from a mismatch between predicted movement outcomes and sensory afference are used to correct ongoing movements through feedback control and to adapt feedforward control of future movements. The cerebellum has been identified as a critical part of the neural circuit underlying implicit adaptation across a wide variety of movements (reaching, gait, eye movements, and speech). The contribution of this structure to feedback control is less well understood. Although it has recently been shown in the speech domain that individuals with cerebellar degeneration produce larger online corrections for sensory perturbations than control participants, similar behavior has not been observed in other motor domains. Currently, comparisons across domains are limited by different population samples and potential ceiling effects in existing tasks. To assess the relationship between changes in feedforward and feedback control associated with cerebellar degeneration across motor domains, we evaluated adaptive (feedforward) and compensatory (feedback) responses to sensory perturbations in reaching and speech production in human participants of both sexes with cerebellar degeneration and neurobiologically healthy controls. As expected, the cerebellar group demonstrated impaired adaptation in both reaching and speech. In contrast, the groups did not differ in their compensatory response in either domain. Moreover, compensatory and adaptive responses in the cerebellar group were not correlated within or across motor domains. These results point to a general impairment in feedforward control with spared feedback control in cerebellar degeneration. However, the magnitude of feedforward impairments and potential changes in feedback-based control manifest in a domain-specific manner across individuals.SIGNIFICANCE STATEMENT The cerebellum contributes to feedforward updating of movement in response to sensory errors, but its role in feedback control is less understood. Here, we tested individuals with cerebellar degeneration (CD), using sensory perturbations to assess adaptation of feedforward control and feedback gains during reaching and speech production tasks. The results confirmed that CD leads to reduced adaption in both domains. However, feedback gains were unaffected by CD in either domain. Interestingly, measures of feedforward and feedback control were not correlated across individuals within or across motor domains. Together, these results indicate a general impairment in feedforward control with spared feedback control in CD. However, the magnitude of feedforward impairments manifests in a domain-specific manner across individuals.

An Approach for Stabilizing Abnormal Neural Activity in ADHD Using Chaotic Resonance

Reduced integrity of neural pathways from frontal to sensory cortices has been suggested as a potential neurobiological basis of attention-deficit hyperactivity disorder. Neurofeedback has been widely applied to enhance reduced neural pathways in attention-deficit hyperactivity disorder by repeated training on a daily temporal scale. Clinical and model-based studies have demonstrated that fluctuations in neural activity underpin sustained attention deficits in attention-deficit hyperactivity disorder. These aberrant neural fluctuations may be caused by the chaos–chaos intermittency state in frontal-sensory neural systems. Therefore, shifting the neural state from an aberrant chaos–chaos intermittency state to a normal stable state with an optimal external sensory stimulus, termed chaotic resonance, may be applied in neurofeedback for attention-deficit hyperactivity disorder. In this study, we applied a neurofeedback method based on chaotic resonance induced by “reduced region of orbit” feedback signals in the Baghdadi model for attention-deficit hyperactivity disorder. We evaluated the stabilizing effect of reduced region of orbit feedback and its robustness against noise from errors in estimation of neural activity. The effect of chaotic resonance successfully shifted the abnormal chaos-chaos intermittency of neural activity to the intended stable activity. Additionally, evaluation of the influence of noise due to measurement errors revealed that the efficiency of chaotic resonance induced by reduced region of orbit feedback signals was maintained over a range of certain noise strengths. In conclusion, applying chaotic resonance induced by reduced region of orbit feedback signals to neurofeedback methods may provide a promising treatment option for attention-deficit hyperactivity disorder.

Heart rate control using first- and second-order models during treadmill exercise

Heart rate control using first- and second-order models was compared using a novel control design strategy which shapes the input sensitivity function. Ten participants performed two feedback control test series on a treadmill with square wave and constant references. Using a repeated measures, counterbalanced study design, each series compared controllers C1 and C2 based on first- and second-order models, respectively. In the first series, tracking accuracy root-mean-square tracking error (RMSE) was not significantly lower for C2: 2.59 bpm vs. 2.69 bpm (mean, C1 vs. C2), p = 0.79. But average control signal power was significantly higher for C2: 11.29 × 10 - 4 m 2 / s 2 vs. 27.91 × 10 - 4 m 2 / s 2 , p = 3.1 × 10 - 10 . In the second series, RMSE was also not significantly lower for C2: 1.99 bpm vs. 1.94 bpm, p = 0.39; but average control signal power was again significantly higher for C2: 2.20 × 10 - 4 m 2 / s 2 vs. 2.78 × 10 - 4 m 2 / s 2 , p = 0.045. The results provide no evidence that controllers based on second-order models lead to better tracking accuracy, despite the finding that they are significantly more dynamic. Further investigation using a substantially larger sample size is warranted.

An active approach of pressure waveform matching for stress-based testing of arteries

BACKGROUND

Arterial compliance assists the cardiovascular system with three key roles: (i) storing up to 50% of the stroke volume; (ii) ensuring blood flow during diastole; (iii) dampening pressure oscillations through arterial distension. In mock circulation loops (MCLs), arterial compliance was simulated either with membrane, spring, or Windkessel chambers. Although they have been shown to be suitable for cardiac device testing, their passive behavior can limit stress-based testing of arteries. Here we present an active compliance chamber with a feedback control of variable compliance as part of an MCL designed for biomechanical evaluation of arteries under physiological waveforms.

MATERIALS AND METHODS

The chamber encloses a piston that changes the volume via a cascaded controller when there is a difference between the real-time pressure and the physiological reference pressure with the aim to equilibrate both pressures.

RESULTS

The experimental results showed repeatable physiological waveforms of aortic pressure in health (80-120 mm Hg), systemic hypertension (90-153 mm Hg), and heart failure reduced ejection fraction (78-108 mm Hg). Statistical validation (n = 20) of the function of the chamber is presented against compared raw data.

CONCLUSION

We demonstrate that the active compliance chamber can track the actual pressure of the MCL and balance it in real time (every millisecond) with the reference values in order to shape the given pressure waveform. The active compliance chamber is an advanced tool for MCL applications for biomechanical examination of stented arteries and for preclinical evaluation of vascular implants.

Similar stretch reflexes and behavioral patterns are expressed by the dominant and nondominant arms during postural control

Limb dominance is evident in many daily activities, leading to the prominent idea that each hemisphere of the brain specializes in controlling different aspects of movement. Past studies suggest that the dominant arm is primarily controlled via an internal model of limb dynamics that enables the nervous system to produce efficient movements. In contrast, the nondominant arm may be primarily controlled via impedance mechanisms that rely on the strong modulation of sensory feedback from individual joints to control limb posture. We tested whether such differences are evident in behavioral responses and stretch reflexes following sudden displacement of the arm during posture control. Experiment 1 applied specific combinations of elbow-shoulder torque perturbations (the same for all participants). Peak joint displacements, return times, end point accuracy, and the directional tuning and amplitude of stretch reflexes in nearly all muscles were not statistically different between the two arms. Experiment 2 induced specific combinations of joint motion (the same for all participants). Again, peak joint displacements, return times, end point accuracy, and the directional tuning and amplitude of stretch reflexes in nearly all muscles did not differ statistically when countering the imposed loads with each arm. Moderate to strong correlations were found between stretch reflexes and behavioral responses to the perturbations with the two arms across both experiments. Collectively, the results do not support the idea that the dominant arm specializes in exploiting internal models and the nondominant arm in impedance control by increasing reflex gains to counter sudden loads imposed on the arms during posture control.NEW & NOTEWORTHY A prominent hypothesis is that the nervous system controls the dominant arm through predictive internal models and the nondominant arm through impedance mechanisms. We tested whether stretch reflexes of muscles in the two arms also display such specialization during posture control. Nearly all behavioral responses and stretch reflexes did not differ statistically but were strongly correlated between the arms. The results indicate individual signatures of feedback control that are common for the two arms.