Agency evaluation in motor cognition: Action’s control-effectiveness feedback and its environmental context enhances motor performance

A perceptual effect that is temporally contiguous on one’s action holds important information about one’s control over the action and its effect (“I did that”). Previous work has demonstrated the impact of such immediate action-effect on perception and motor processes. In the current study, we investigated the promoting impact of control-effectiveness feedback – an effect that is temporally contiguous on one’s action – on motor performance. In two experiments, participants performed a rapid movement towards a target location on a computer monitor and clicked on the target with their mouse key as quickly and accurately as possible. Their click response triggered a perceptual effect (a brief white flash) on the target. We manipulated control-effectiveness feedback by employing varying levels of action-effect delay in two experimental contexts - long versus short lag distributions. Such design enabled us to investigate the impact of both the recent action-effect delay and its experimental context on motor performance. The findings demonstrate that control-effectiveness feedback (e.g., temporally contiguous perceptual effect) enhances motor performance as indicated by both endpoint precision and movement speed. In addition, a substantial effect of the experimental context was observed. Namely, we found enhanced motor performance, especially after an ambiguous (intermediate) action-effect delay when it was sampled from a short compared to long lag distribution; a pattern that supports the contribution of both ‘control’ expectations and control-feedback on motor performance. We discuss findings in the context of previous work on control-effectiveness and movement control and their potential implications for clinicians and digital interface developers.

Stress generation, relaxation and size control in confined tumor growth

Experiments on tumor spheroids have shown that compressive stress from their environment can reversibly decrease tumor expansion rates and final sizes. Stress release experiments show that nonuniform anisotropic elastic stresses can be distributed throughout. The elastic stresses are maintained by structural proteins and adhesive molecules, and can be actively relaxed by a variety of biophysical processes. In this paper, we present a new continuum model to investigate how the growth-induced elastic stresses and active stress relaxation, in conjunction with cell size control feedback machinery, regulate the cell density and stress distributions within growing tumors as well as the tumor sizes in the presence of external physical confinement and gradients of growth-promoting chemical fields. We introduce an adaptive reference map that relates the current position with the reference position but adapts to the current position in the Eulerian frame (lab coordinates) via relaxation. This type of stress relaxation is similar to but simpler than the classical Maxwell model of viscoelasticity in its formulation. By fitting the model to experimental data from two independent studies of tumor spheroid growth and their cell density distributions, treating the tumors as incompressible, neo-Hookean elastic materials, we find that the rates of stress relaxation of tumor tissues can be comparable to volumetric growth rates. Our study provides insight on how the biophysical properties of the tumor and host microenvironment, mechanical feedback control and diffusion-limited differential growth act in concert to regulate spatial patterns of stress and growth. When the tumor is stiffer than the host, our model predicts tumors are more able to change their size and mechanical state autonomously, which may help to explain why increased tumor stiffness is an established hallmark of malignant tumors.

Adaptive multilayer management remotely operated underwater vehicle

В статье рассматривается самоорганизующаяся адаптивная система управления телеуправляемыми необитаемыми подводными аппаратами. Адаптивная нейронная система многослойного управления построена по принципу декомпозиции мультичастотного набора входных сигналов, формируемых в адаптивном джойстике управления. Декомпозиция наборов последовательностей управляющих сигналов проходит процедуру трешолдинга, разделения по оценкам спектра мультичастотного сигнала управления. Каскадный алгоритм построен по принципу интерполяции и децимации коэффициентов фильтра. Трешолдинг реализуется свёрткой форматного кадра управляющего сигнала с коэффициентами всплеск формирующего фильтра в базисе всплесков Добеши. Интерполяция коэффициентов фильтра происходит сдвигом частоты, децимация схлопыванием коэффициентов фильтра. Спектральные оценки, построенные по среднеквадратическому значению спектра, укладываются в спектральный радиус нормированного сигнала и формируют матрицу математического ожидания адаптивного сигнала управления. Реакции пилота телеуправляемого необитаемого подводного аппарата формируют управляющие сигналы в трёх плоскостях с заданными скоростями и моментами. Трешолдинг в базисе всплесков позволяет формировать сигналы управления с оптимальной крутизной выходной характеристики, что позволяет отказаться от необходимой ручной регулировки мощностей движителей двигательно-рулевого комплекса, при реализации полуавтоматичеcкого и автоматического управления. Обратная связь системы управления по наблюдаемой динамике позволяет реализовать функцию автопилота, с учётом заданных критериев качества. The article discusses the self-organizing adaptive system management remotely operated underwater vehicle. Adaptive neural system of multilayer control is built on the principle of decomposition of multi-frequency set of input signals generated in adaptive joystick of management. The decomposition of the sets of control signal sequences undergoes the procedure of tresholding, separation by estimates of the spectrum of the multi-frequency control signal. The cascade algorithm is based on the principle of interpolation and decimation of filter coefficients. Tresholding is implemented by convolving the format frame of the control signal with wavelet coefficients of the forming filter in the basis of Dobeshi wavelet. Interpolation of filter coefficients occurs by frequency shift, decimation by collapse of filter coefficients. Spectral estimates based on the standard value of the spectrum fit into the spectral radius of the normalized signal and form a matrix of mathematical expectation of the adaptive control signal. The reactions of the pilot of a remotely operated underwater vehicle form control signals in three planes with given speeds and moments. Tresholding in the basis of wavelets allows you to generate control signals with an optimal slope of the output characteristic, which allows you to abandon the necessary manual adjustment of the powers of the propulsion engines of the engine-steering system, when implementing semi-automatic and automatic control. Feedback of the control system according to the observed dynamics allows implementing the autopilot function, taking into account the specified quality criteria.

Stability and control of the nonlinear system for tractor with N trailer in the presence of slip

In many engineering systems, it is not enough to merge the system paths to zero at infinite time, but the speed of moving these paths to zero is very important. Estimating this speed can be done using exponential functions. This concept is used in exponential stability definition. The purpose of this paper is to design a controller for problem inputs and implement a system of a car with N to a trailer connected to it. This approach is based on the analysis of the Lyapunov stability method. In the given problem, the purpose of conducting and converging the system considering the slip phenomenon as a primitive uncertainty in the system is toward the desired point. Since the trailer tractor system has limitation constraints in the modeling structure, it is difficult to guarantee the stability of a non-holonomic system. Because no controller designed by the control feedback method can continuously and stable ensure the convergence of the system. If this possibility almost dynamic errors, even adaptive controls do not versatile with the operation of the Lyapunov function, especially in the presence of uncertainties, which is a very important factor in system instability, which requires the development of controllers designed to deal with these disturbances. In the simulated results, this paper not only examines the convergence properties, but also shows the ability to control the system by designing a controller in the presence of a slip phenomenon to strengthen the system in the stability debate.

A cerebellar internal model calibrates a feedback controller involved in sensorimotor control

Animals must adapt their behavior to survive in a changing environment. Behavioral adaptations can be evoked by two mechanisms: feedback control and internal-model-based control. Feedback controllers can maintain the sensory state of the animal at a desired level under different environmental conditions. In contrast, internal models learn the relationship between the motor output and its sensory consequences and can be used to recalibrate behaviors. Here, we present multiple unpredictable perturbations in visual feedback to larval zebrafish performing the optomotor response and show that they react to these perturbations through a feedback control mechanism. In contrast, if a perturbation is long-lasting, fish adapt their behavior by updating a cerebellum-dependent internal model. We use modelling and functional imaging to show that the neuronal requirements for these mechanisms are met in the larval zebrafish brain. Our results illustrate the role of the cerebellum in encoding internal models and how these can calibrate neuronal circuits involved in reactive behaviors depending on the interactions between animal and environment.

Time-varying output formation-tracking of heterogeneous multi-agent systems with time-varying delays and switching topologies

This paper focuses on the time-varying output formation (TVOF) tracking control of heterogeneous linear multi-agent systems (HL-MASs) with both delays and switching topologies, where the followers’ outputs can move along the reference trajectory generated by the leaders and maintain the desired time-varying formation. First, a distributed observer is proposed for each follower, aiming to estimate the convex combination of leaders’ state with both communication delays and switching graphs. The observer’s error for heterogeneous MASs is analyzed based on Lyapunov theory and linear matrix inequality (LMI) technique. Second, the observer is incorporated into the output formation tracking protocol. Then, an algorithm is put forward to calculate the control feedback gains and the formation tracking feasibility constraint is also provided. Furthermore, the convergence of the formation tracking error is proved. At last, the effectiveness of this proposed method is validated through a numerical simulation.

Virtual reality exercise to help COVID patients with refractory breathlessness

Background: Immersive virtual reality (iVR)-based digital therapeutics (DTx) are gaining clinical attention in the field of pain management. Based on known analogy between chronic pain and dyspnea, we investigated the effects of visual respiratory feedback in iVR, on refractory breathlessness in patients recovering from severe COVID-19 pneumonia. Methods: We performed a controlled, randomized, single-blind, cross-over clinical study to evaluate an iVR-based intervention to alleviate refractory breathlessness in patients recovering from COVID-19 pneumonia. The single-site study was conducted at the university hospital of Geneva, Switzerland. Patients reported refractory breathlessness (≥5 on a 10-point dyspnea scale) and had a MoCA score of ≥24. Cross-over groups were randomly assigned, concealed from the referring clinician. Participants received synchronous (intervention) or asynchronous (control) feedback of their breathing, embodied via a gender-matched avatar in iVR. Prior to the first exposure and following both experimental conditions, patients completed questionnaires. Breathing patterns were captured continuously. The COVVR clinical study is registered with ClinicalTrials.gov (NCT04844567) and is now closed. Findings: Study enrollment was open between November 2020 and April 2021. A total of 26 patients (27% women; age: mean=57, SD±12) were enrolled; 14 patients were randomly assigned to the ″synchronous/asynchronous″ sequence, 12 to the ″asynchronous/synchronous″ sequence. Data was available for all except two (7.7%) of 26 patients. The mean rating of breathing comfort was 0.1 at baseline, 0.8±1.8 for asynchronous, and 1.3±1.4 synchronous feedback (estimated difference of 0.5 (95%CI 0.05 to 1.04; p<0.05) between iVR conditions). Of all patients, 91.2% were satisfied with the intervention (1.8±1.6, t=5.201, p<0.0001, 95%CI 1.173 to inf) and 66.7% perceived it as beneficial for their breathing (0.7±1.9, t=1.806, p<0.05, 95%CI 0.036 to inf). No adverse events were reported. Interpretation: Based on these findings, we propose that our iVR-based DTx is a feasible and safe neuro-rehabilitation tool that improves breathing comfort in patients recovering from severe COVID-19 infection. More research is needed to generalize this tool in other groups of patients suffering from refractory breathlessness.

Balancing inverted pendulum cart on inclines using accelerometers

The balance of inverted pendulum on inclined surfaces is the precursor to their control in unstructured environments. Researchers have devised control algorithms with feedback from contact (encoders - placed at the pendulum joint) and non-contact (gyroscopes, tilt) sensors. We present feedback control of Inverted Pendulum Cart (IPC) on variable inclines using non-contact sensors and a modified error function. The system is in the state of equilibrium when it is not accelerating and not falling over (rotational equilibrium). This is achieved when the pendulum is aligned along the gravity vector. The control feedback is obtained from non-contact sensors comprising of a pair of accelerometers placed on the inverted pendulum and one on the cart. The proposed modified error function is composed of the dynamic (non-gravity) acceleration of the pendulum and the velocity of the cart. We prove that the system is in equilibrium when the modified error is zero. We present algorithm to calculate the dynamic acceleration and angle of the pendulum, and incline angle using accelerometer readings. Here, the cart velocity and acceleration are assumed to be proportional to the motor angular velocity and acceleration. Thereafter, we perform simulation using noisy sensors to illustrate the balance of IPC on surfaces with unknown inclination angles using PID feedback controller with saturated motor torque, including valley profile that resembles a downhill, flat and uphill combination. The successful control of the system using the proposed modified error function and accelerometer feedback argues for future design of controllers for unstructured and unknown environments using all-accelerometer feedback.

Integrated Quality Control Process for Hydrological Database: A Case Study of Daecheong Dam Basin in South Korea

In our intelligent society, water resources are being managed using vast amounts of hydrological data collected through telemetric devices. Recently, advanced data quality control technologies for data refinement based on hydrological observation history, such as big data and artificial intelligence, have been studied. However, these are impractical due to insufficient verification and implementation periods. In this study, a process to accurately identify missing and false-reading data was developed to efficiently validate hydrological data by combining various conventional validation methods. Here, false-reading data were reclassified into suspected and confirmed groups by combining the results of individual validation methods. Furthermore, an integrated quality control process that links data validation and reconstruction was developed. In particular, an iterative quality control feedback process was proposed to achieve highly reliable data quality, which was applied to precipitation and water level stations in the Daecheong Dam Basin, South Korea. The case study revealed that the proposed approach can improve the quality control procedure of hydrological database and possibly be implemented in practice.