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Behaviors we perform each day, such as manipulating an object or walking, require precise control of the interaction forces between our bodies and the environment. These forces are generated by muscle contractions, specified by the nervous system, and by joint mechanics, determined by the intrinsic properties of the musculoskeletal system. Depending on behavioral goals, joint mechanics might simplify or complicate control of movement by the nervous system. Whether humans can exploit joint mechanics to simplify neural control remains unclear. Here we evaluated if leveraging joint mechanics simplifies neural control by comparing performance in three tasks that required subjects to generate specified torques about the ankle during imposed sinusoidal movements; only one task required torques that could be generated by leveraging the intrinsic mechanics of the joint. The complexity of the neural control was assessed by subjects' perceived difficulty and the resultant task performance. We developed a novel approach that used continuous estimates of ankle impedance, a quantitative description of the joint mechanics, and measures of muscle activity to determine the mechanical and neural contributions to the net ankle torque generated in each task. We found that the torque resulting from changes in neural control was reduced when ankle impedance was consistent with the task being performed. Subjects perceived this task to be easier than those that were not consistent with the impedance of the ankle and were able to perform it with the highest level of consistency across repeated trials. These results demonstrate that leveraging the mechanical properties of a joint can simplify task completion and improve performance. [ABSTRACT FROM AUTHOR]

In this study, an intelligent control scheme is developed for induction motors (IMs). The dynamics of IMs are unknown and are perturbed by the variation of rotor resistance and load changes. The control system has two stages. In the identification stage, the group method of data-handling (GMDH) neural network (NN) was designed for online modeling of the IM. In the control stage, the GMDH-NN was applied to compensate for the impacts of disturbances and uncertainties. The stability is shown by the Lyapunov approach. Simulations demonstrated the good accuracy of the suggested new control approach under disturbances and unknown dynamics. [ABSTRACT FROM AUTHOR]

Objective: Ankle joint stiffness is known to be modulated by co-contraction of the ankle muscles; however, it is unclear to what extent changes in agonist muscle activation alone affect ankle joint stiffness. This study tested the effects of varying levels of ankle muscle activation on ankle joint mechanical stiffness in standing and during the late stance phase of walking. Methods: Dorsiflexion perturbations were applied at various levels of ankle muscle activation via a robotic platform in standing and walking conditions. In standing, muscle activation was modulated by having participants perform an EMG target matching task that required varying levels of plantarflexor activation. In walking, muscle activation was modulated by changing walking speeds through metronome-based auditory feedback. Ankle stiffness was evaluated by performing a Least-squares system identification using a parametric model consisting of stiffness, damping, and inertia. The association between ankle muscle activation and joint stiffness was evaluated using correlation analyses. Linear regression models were used to determine the extent to which muscle activation contributed to ankle stiffness. An inclusive statistical approach (both classical and Bayesian analyses) was adopted to measure the statistical significance (p-value) and Bayes Factor (BF10). Results: Results indicate that plantarflexor activity was positively correlated with ankle stiffness in both standing and walking (p<0.001, BF10900), whereas dorsiflexor activity was negatively correlated with ankle stiffness in walking (p = 0.014, BF10 = 3.9) but not in standing (p = 0.725). Regression analyses indicated that ankle muscle activation predicted about 84% of the variation in ankle stiffness in standing and 45% in walking (p<0.001, BF10100). Conclusion: Ankle muscle activation significantly contributes to ankle stiffness during standing and walking. Significance: The results highlight the role of muscle activation on maintaining joint stiffness and underscore the importance of accounting for muscle activation when measuring ankle stiffness in healthy as well as patient populations. [ABSTRACT FROM AUTHOR]

In almost all animals, the transfer of information from the brain to the motor circuitry is facilitated by a relatively small number of neurons, leading to a constraint on the amount of information that can be transmitted. Our knowledge of how animals encode information through this pathway, and the consequences of this encoding, however, is limited. In this study, we use a simple feed-forward neural network to investigate the consequences of having such a bottleneck and identify aspects of the network architecture that enable robust information transfer. We are able to explain some recently observed properties of descending neurons—that they exhibit a modular pattern of connectivity and that their excitation leads to consistent alterations in behavior that are often dependent upon the desired behavioral state of the animal. Our model predicts that in the presence of an information bottleneck, such a modular structure is needed to increase the efficiency of the network and to make it more robust to perturbations. However, it does so at the cost of an increase in state-dependent effects. Despite its simplicity, our model is able to provide intuition for the trade-offs faced by the nervous system in the presence of an information processing constraint and makes predictions for future experiments.

Behaviors we perform each day, such as manipulating an object or walking, require precise control of the interaction forces between our bodies and the environment. These forces are generated by muscle contractions, specified by the nervous system, and by joint mechanics, determined by the intrinsic properties of the musculoskeletal system. Depending on behavioral goals, joint mechanics might simplify or complicate control of movement by the nervous system. Whether humans can exploit joint mechanics to simplify neural control remains unclear. Here we evaluated if leveraging joint mechanics simplifies neural control by comparing performance in three tasks that required subjects to generate specified torques about the ankle during imposed sinusoidal movements; only one task required torques that could be generated by leveraging the intrinsic mechanics of the joint. The complexity of the neural control was assessed by subjects’ perceived difficulty and the resultant task performance. We developed a novel approach that used continuous estimates of ankle impedance, a quantitative description of the joint mechanics, and measures of muscle activity to determine the mechanical and neural contributions to the net ankle torque generated in each task. We found that the torque resulting from changes in neural control was reduced when ankle impedance was consistent with the task being performed. Subjects perceived this task to be easier than those that were not consistent with the impedance of the ankle and were able to perform it with the highest level of consistency across repeated trials. These results demonstrate that leveraging the mechanical properties of a joint can simplify task completion and improve performance.

Understanding the contribution of the autonomic nervous system to cerebral blood flow (CBF) control is challenging, and interpretations are unclear. The identification of calcium channels and adrenoreceptors within cerebral vessels has led to common misconceptions that the function of these receptors and actions mirror those of the peripheral vasculature. This review outlines the fundamental differences and complex actions of cerebral autonomic activation compared with the peripheral circulation. Anatomical differences, including the closed nature of the cerebrovasculature, and differential adrenoreceptor subtypes, density, distribution and sensitivity, provide evidence that measures on peripheral sympathetic nerve activity cannot be extrapolated to the cerebrovasculature. Cerebral sympathetic nerve activity seems to act opposingly to the peripheral circulation, mediated at least in part by changes in intracranial pressure and cerebral blood volume. Additionally, heterogeneity in cerebral adrenoreceptor distribution highlights region‐specific autonomic regulation of CBF. Compensatory chemo‐ and autoregulatory responses throughout the cerebral circulation, and interactions with parasympathetic nerve activity are unique features to the cerebral circulation. This crosstalk between sympathetic and parasympathetic reflexes acts to ensure adequate perfusion of CBF to rising and falling perfusion pressures, optimizing delivery of oxygen and nutrients to the brain, while attempting to maintain blood volume and intracranial pressure. Herein, we highlight the distinct similarities and differences between autonomic control of cerebral and peripheral blood flow, and the regional specificity of sympathetic and parasympathetic regulation within the cerebrovasculature. Future research directions are outlined with the goal to further our understanding of autonomic control of CBF in humans. [ABSTRACT FROM AUTHOR]

The influence of proprioceptive feedback on muscle activity during isometric tasks is the subject of conflicting studies. We performed an isometric knee extension task experiment based on two common clinical tests for mobility and flexibility. The task was carried out at four preset angles of the knee, and we recorded from five muscles for two different hip positions. We applied muscle synergy analysis using nonnegative matrix factorization on surface electromyograph recordings to identify patterns in the data that changed with internal knee angle, suggesting a link between proprioception and muscle activity. We hypothesized that such patterns arise from the way proprioceptive and cortical signals are integrated in neural circuits of the spinal cord. Using the MIIND neural simulation platform, we developed a computational model based on current understanding of spinal circuits with an adjustable afferent input. The model produces the same synergy trends as observed in the data, driven by changes in the afferent input. To match the activation patterns from each knee angle and position of the experiment, the model predicts the need for three distinct inputs: two to control a nonlinear bias toward the extensors and against the flexors, and a further input to control additional inhibition of rectus femoris. The results show that proprioception may be involved in modulating muscle synergies encoded in cortical or spinal neural circuits. NEW & NOTEWORTHY The role of sensory feedback in motor control when limbs are held in a fixed position is disputed. We performed a novel experiment involving fixed position tasks based on two common clinical tests. We identified patterns of muscle activity during the tasks that changed with different leg positions and then inferred how sensory feedback might influence the observations. We developed a computational model that required three distinct inputs to reproduce the activity patterns observed experimentally. The model provides a neural explanation for how the activity patterns can be changed by sensory feedback. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is characterized by the progressive loss of dopaminergic neurons in the substantia nigra, mainly affecting people over 60 yr of age. Patients develop both classic symptoms (tremors, muscle rigidity, bradykinesia, and postural instability) and nonclassical symptoms (orthostatic hypotension, neuropsychiatric deficiency, sleep disturbances, and respiratory disorders). Thus, patients with PD can have a significantly impaired quality of life, especially when they do not have multimodality therapeutic follow-up. The respiratory alterations associated with this syndrome are the main cause of mortality in PD. They can be classified as peripheral when caused by disorders of the upper airways or muscles involved in breathing and as central when triggered by functional deficits of important neurons located in the brainstem involved in respiratory control. Currently, there is little research describing these disorders, and therefore, there is no well-established knowledge about the subject, making the treatment of patients with respiratory symptoms difficult. In this review, the history of the pathology and data about the respiratory changes in PD obtained thus far will be addressed. [ABSTRACT FROM AUTHOR]

Background. Following stretch of an active muscle, muscle force is enhanced, which is known as residual force enhancement (rFE). As earlier studies found apparent corticospinal excitability modulations in the presence of rFE, this study aimed to test whether corticospinal excitability modulations contribute to rFE. Methods. Fourteen participants performed submaximal plantar flexion stretch-hold and fixed-end contractions at 30% of their maximal voluntary soleus muscle activity in a dynamometer. During the steady state of the contractions, participants either received subthreshold or suprathreshold transcranial magnetic stimulation (TMS) of their motor cortex, while triceps surae muscle responses to stimulation were obtained via electromyography (EMG), and net ankle joint torque was recorded. B-mode ultrasound imaging was used to confirm muscle fascicle stretch during stretch-hold contractions in a subset of participants. Results. Following stretch of the plantar flexors, an average rFE of 7% and 11% was observed for contractions with subthreshold and suprathreshold TMS, respectively. 41-46 ms following subthreshold TMS, triceps surae muscle activity was suppressed by 19-25%, but suppression was not significantly different between stretch-hold and fixed-end contractions. Similarly, the reduction in plantar flexion torque following subthreshold TMS was not significantly different between contraction conditions. Motor evoked potentials, silent periods and superimposed twitches following suprathreshold TMS were also not significantly different between contraction conditions. Discussion. As TMS of the motor cortex did not result in any differences between stretch-hold and fixed-end contractions, we conclude that rFE is not linked to changes in corticospinal excitability. [ABSTRACT FROM AUTHOR]

This paper describes the implementation of fast state-dependent Riccati equation (SDRE) control algorithms through the use of shallow and deep artificial neural networks (ANN). Several ANNs are trained to replicate an SDRE controller developed for a satellite attitude dynamics simulator (SADS) to display the technique's efficacy. The neural controllers have reduced computational complexity compared with the original SDRE controller, allowing its execution at a significantly higher rate. One of the neural controllers was validated using the SADS in a practical experiment. The experimental results indicate that the training error is sufficiently small for the neural controller to perform equivalently to the original SDRE controller. • A real-time SDRE controller is designed using shallow and deep neural networks. • A significant reduction in computation is achieved using the neural controllers. • Deep denoising autoencoders were trained as deep neural controllers. • The neural controller is validated through simulations and a practical experiment. • Results show that the neural controller retains its high performance. [ABSTRACT FROM AUTHOR]

The article shows a theoretical (part 1) improvement in the stabilization of the gaze in galvanic vestibular stimulation. [ABSTRACT FROM AUTHOR]

Background Following stretch of an active muscle, muscle force is enhanced, which is known as residual force enhancement (rFE). As earlier studies found apparent corticospinal excitability modulations in the presence of rFE, this study aimed to test whether corticospinal excitability modulations contribute to rFE. Methods Fourteen participants performed submaximal plantar flexion stretch-hold and fixed-end contractions at 30% of their maximal voluntary soleus muscle activity in a dynamometer. During the steady state of the contractions, participants either received subthreshold or suprathreshold transcranial magnetic stimulation (TMS) of their motor cortex, while triceps surae muscle responses to stimulation were obtained via electromyography (EMG), and net ankle joint torque was recorded. B-mode ultrasound imaging was used to confirm muscle fascicle stretch during stretch-hold contractions in a subset of participants. Results Following stretch of the plantar flexors, an average rFE of 7% and 11% was observed for contractions with subthreshold and suprathreshold TMS, respectively. 41–46 ms following subthreshold TMS, triceps surae muscle activity was suppressed by 19–25%, but suppression was not significantly different between stretch-hold and fixed-end contractions. Similarly, the reduction in plantar flexion torque following subthreshold TMS was not significantly different between contraction conditions. Motor evoked potentials, silent periods and superimposed twitches following suprathreshold TMS were also not significantly different between contraction conditions. Discussion As TMS of the motor cortex did not result in any differences between stretch-hold and fixed-end contractions, we conclude that rFE is not linked to changes in corticospinal excitability.

Bothersome urinary symptoms plague many older adults and disproportionally affect women. Underreporting of symptoms and general stigma/embarrassment associated with incontinence has negatively impacted the availability of treatments, as research cannot be championed if the severity of the problem is not apparent. Available therapeutics have limited efficacy and are often not recommended in aged patients. Lower urinary tract function has a long and rich history in animal studies; while much of the underlying anatomy has been described, including neural control mechanisms, the impact of aging has only just begun to be addressed. Recent work has provided strong evidence that neural control over micturition is significantly impacted by aging processes. This mini review discusses recent findings regarding how aging impacts the neural control mechanisms of micturition.

Regrowing new body parts requires neural input to restore appropriately sized limbs in salamanders.

The mechanisms that regulate growth and size of the regenerating limb in tetrapods such as the Mexican axolotl are unknown. Upon the completion of the developmental stages of regeneration, when the regenerative organ known as the blastema completes patterning and differentiation, the limb regenerate is proportionally small in size. It then undergoes a phase of regeneration that we have called the ‘tiny-limb’ stage, which is defined by rapid growth until the regenerate reaches the proportionally appropriate size. In the current study we have characterized this growth and have found that signaling from the limb nerves is required for its maintenance. Using the regenerative assay known as the accessory limb model (ALM), we have found that growth and size of the limb positively correlates with nerve abundance. We have additionally developed a new regenerative assay called the neural modified-ALM (NM-ALM), which decouples the source of the nerves from the regenerating host environment. Using the NM-ALM we discovered that non-neural extrinsic factors from differently sized host animals do not play a prominent role in determining the size of the regenerating limb. We have also discovered that the regulation of limb size is not autonomously regulated by the limb nerves. Together, these observations show that the limb nerves provide essential cues to regulate ontogenetic allometric growth and the final size of the regenerating limb.

Context: Tearing of the anterior cruciate ligament (ACL) may disrupt the ability to recognize the knee position in space during limb-repositioning tasks, which is referred to as joint-position sense (JPS). Impairments in JPS have been shown to be lower during active than passive repositioning tasks, thus suggesting that coactivation patterns of the muscles surrounding the knee might compensate for the disrupted JPS and ensure accurate limb repositioning in ACL-deficient individuals. Objective: To investigate muscle coactivation patterns during JPS repositioning tasks in ACL-deficient and healthy individuals. Design: Prospective observational study. Setting: Functional assessment laboratory. Participants: 8 men age 25 ± 8 y with isolated ACL rupture and 10 men age 30 ± 4 y with no history of knee injury. Intervention: JPS was evaluated by means of an electrogoniometer in a sitting position during either passive or active joint-positioning and -repositioning tasks with a 40° target knee angle. Main Outcome Measures: Root mean square (RMS) of the surface electromyogram from the vastus lateralis and biceps femoris muscles was measured during active joint positioning and repositioning. Results: Healthy participants showed a significant decrease in vastus lateralis RMS (-19%) and an increase in biceps femoris RMS (+26%) during joint repositioning compared with positioning. In contrast, ACL-deficient patients showed no modulation in muscle coactivation between joint positioning and repositioning, although they exhibited significantly lower RMS of the vastus lateralis (injured limb, -28%; uninjured limb, -21%) and higher RMS of the biceps femoris (injured limb, +19%; uninjured limb, +30%) than the healthy participants during joint positioning. Conclusions: The lack of modulation in muscle coactivation patterns between joint positioning and repositioning in ACL-deficient patients might be attributed to disrupted neural control after the injury-related loss of proprioceptive information. These results should be taken into account in the design of rehabilitation protocols with emphasis on muscle coactivation and JPS. [ABSTRACT FROM AUTHOR]

Background: Maintaining upright posture is an unstable task that requires sophisticated neuro-muscular control. Humans use foot-ground interaction forces, characterized by point of application, magnitude, and direction to manage body accelerations. When analyzing the directions of the ground reaction forces of standing humans in the frequency domain, previous work found a consistent pattern in different frequency bands. To test whether this frequency-dependent behavior provided a distinctive signature of neural control or was a necessary consequence of biomechanics, this study simulated quiet standing and compared the results with human subject data.Methods: Aiming to develop the simplest competent and neuromechanically justifiable dynamic model that could account for the pattern observed across multiple subjects, we first explored the minimum number of degrees of freedom required for the model. Then, we applied a well-established optimal control method that was parameterized to maximize physiologically-relevant insight to stabilize the balancing model.Results: If a standing human was modeled as a single inverted pendulum, no controller could reproduce the experimentally observed pattern. The simplest competent model that approximated a standing human was a double inverted pendulum with torque-actuated ankle and hip joints. A range of controller parameters could stabilize this model and reproduce the general trend observed in experimental data; this result seems to indicate a biomechanical constraint and not a consequence of control. However, details of the frequency-dependent pattern varied substantially across tested control parameter values. The set of parameters that best reproduced the human experimental results suggests that the control strategy employed by human subjects to maintain quiet standing was best described by minimal control effort with an emphasis on ankle torque.Conclusions: The findings suggest that the frequency-dependent pattern of ground reaction forces observed in quiet standing conveys quantitative information about human control strategies. This study's method might be extended to investigate human neural control strategies in different contexts of balance, such as with an assistive device or in neurologically impaired subjects. [ABSTRACT FROM AUTHOR]

• We provide an overview of two prevalent conceptual accounts of brain aging. • We assess older adult brain function during walking and evaluate fit with accounts. • Findings suggest different interpretations based on methods and difficulty of task. • We provide suggestions for future aging, locomotion, and imaging experiments. A prominent trend in the functional brain imaging literature is that older adults exhibit increased brain activity compared to young adults to perform a given task. This phenomenon has been extensively studied for cognitive tasks, with the field converging on interpretations described in two alternative accounts. One account interprets over-activation in older adults as reflecting neural dysfunction (increased brain activity – indicates poorer performance), whereas another interprets it as neural compensation (increased brain activity - supports better performance). Here we review studies that have recorded brain activity and walking measurements in older adults, and we categorize their findings as reflecting either neural dysfunction or neural compensation. Based on this synthesis, we recommend including multiple task difficulty levels in future work to help differentiate if and when compensation fails as the locomotion task becomes more difficult. Using multiple task difficulty levels with neuroimaging will lead to a more advanced understanding of how age-related changes in locomotor brain activity fit with existing accounts of brain aging and support the development of targeted neural rehabilitation techniques. [ABSTRACT FROM AUTHOR]

Motivated by the increasing complexity of systems to be controlled and different system components that cause uncertainties, threats, and disturbances, among other system stressing phenomena. Resilient control is an important design paradigm that has attracted attention from academics, practitioners, and the industrial sector. Therefore, this paper proposes the design of a model‐free resilient control for unknown discrete‐time nonlinear systems based on a recurrent high order neural network trained with an on‐line extended Kalman filter‐based algorithm for output trajectory tracking in the presence of uncertainties, disturbances, and unmodeled dynamics. This paper also includes the stability proof of the entire proposed scheme; its applicability is shown via simulation and experimental results including a comparative analysis of the proposed controller against well‐known controllers for a three‐phase induction motor. [ABSTRACT FROM AUTHOR]

Although the torso plays an important role in the movement coordination and versatile locomotion of mammals, the structural design and neuromechanical control of a bionic torso have not been fully addressed. In this paper, a parallel mechanism is designed as a bionic torso to improve the agility, coordination, and diversity of robot locomotion. The mechanism consists of 6-degree of freedom actuated parallel joints and can perfectly simulate the bending and stretching of an animal's torso during walking and running. The overall spatial motion performance of the parallel mechanism is improved by optimizing the structural parameters. Based on this structure, the rhythmic motion of the parallel mechanism is obtained by supporting state analysis. The neural control of the parallel mechanism is realized by constructing a neuromechanical network, which merges the rhythmic signals of the legs and generates the locomotion of the bionic parallel mechanism for different motion patterns. Experimental results show that the complete integrated system can be controlled in real time to achieve proper limb-torso coordination. This coordination enables several different motions with effectiveness and good performance. [ABSTRACT FROM AUTHOR]

Metabolic syndrome encompasses a spectrum of conditions that increases the risk for cardiovascular and metabolic diseases. It is widely accepted that the sex hormone estrogen plays a protective metabolic role in premenopausal women, in part through central nervous system (CNS) mechanisms. However, most work to date has focused on the loss of estrogen in females (e.g., menopause). Interestingly, transgender individuals receiving feminizing gender affirming therapy (i.e., estrogen) are relatively protected from metabolic syndrome conditions, pointing to a role for CNS estrogen in the development of metabolic syndrome in men. Here, we show that estrogen signaling in the brain protects males from metabolic syndrome and obesity related complications. First, short-term CNS specific supplementation of low-dose 17-β-estradiol in diet-induced obese male mice resulted in a significant reduction in body weight in parallel with a decrease in food intake without alterations in energy expenditure. In conjunction, central supplementation of estrogen reduced visceral adiposity, including epididymal and abdominal regions, with slighter decreases in subcutaneous inguinal and thermogenic brown adipose tissue. Furthermore, central estrogen administration reduced the liver manifestation of metabolic syndrome including hepatomegaly and hepatic steatosis. Collectively, these findings indicate that a lack of estrogen action in the brain may predispose males to metabolic syndrome pathogenesis.

The capacity to move is essential for independence and declines with age. Slow movement speed, in particular, is strongly associated with negative health outcomes. Prior research on mobility (herein defined as movement slowness) and aging has largely focused on musculoskeletal mechanisms and processes. More recent work has provided growing evidence for a significant role of the nervous system in contributing to reduced mobility in older adults. In this article, we report four pieces of complementary evidence from behavioral, genetic, and neuroimaging experiments that, we believe, provide theoretical support for the assertion that the basal ganglia and its dopaminergic function are responsible, in part, for age-related reductions in mobility. We report four a posteriori findings from an existing dataset: (1) slower central activation of ballistic force development is associated with worse mobility among older adults; (2) older adults with the Val/Met intermediate catecholamine-O-methyl-transferase (COMT) genotype involved in dopamine degradation exhibit greater mobility than their homozygous counterparts; (3) there are moderate relationships between performance times from a series of lower and upper extremity tasks supporting the notion that movement speed in older adults is a trait-like attribute; and (4) there is a relationship of functional connectivity within the medial orbofrontal (mOFC) cortico-striatal network and measures of mobility, suggesting that a potential neural mechanism for impaired mobility with aging is the deterioration of the integrity of key regions within the mOFC cortico-striatal network. These findings align with recent basic and clinical science work suggesting that the basal ganglia and its dopaminergic function are mechanistically linked to age-related reductions in mobility capacity. [ABSTRACT FROM AUTHOR]

This article investigates the quantized adaptive finite-time bipartite tracking control problem for high-order stochastic pure-feedback nonlinear multiagent systems with sensor faults and Prandtl–Ishlinskii (PI) hysteresis. Different from the existing finite-time control results, the nonlinearity of each agent is totally unknown in this article. To overcome the difficulties caused by asymmetric hysteresis quantization and PI hysteresis, a new distributed control method is proposed by adopting the adaptive compensation technique without estimating the lower bounds of parameters. Radial basis function neural networks are employed to estimate unknown nonlinear functions and solve the problem of algebraic loop caused by the pure-feedback nonlinear systems. Then, an adaptive neural-network compensation control approach is proposed to tackle the problem of sensor faults. The problem of the “explosion of complexity” caused by repeated differentiations of the virtual controller is solved by using the dynamic surface control technique. Based on the Lyapunov stability theorem, it is proved that all signals of the closed-loop systems are semiglobal practical finite-time stable in probability, and the bipartite tracking control performance is achieved. Finally, the effectiveness of the proposed control strategy is verified by some simulation results. [ABSTRACT FROM AUTHOR]

In this article, a double strategy is proposed to find the optimal gains of a cascaded PI controller to minimize the trajectory position error in a five-bar parallel robot. The first strategy employs Differential Evolution to tune constant gains during the execution time of the desired trajectory. Once Differential Evolution achieves convergence on the solution by finding the vector of optimal gains that minimize the position tracking error, all the position error data and current of the two brushless motors are saved. In the second strategy, the data generated in the first strategy is used to train a Deep Neural Network. After that, the trained Deep Neural Network replaces the constant gains of the first strategy with time-varying gains for the desired trajectory. Three working scenarios are proposed to test the generalization of the Deep Neural Network. In the first scenario, a training trajectory is executed. In the second one, a testing trajectory of the Deep Neural Network is evaluated. In the third one, a mass change is generated in the middle of the cycle. The results show that the Deep Neural Network is robust to different trajectories and mass changes during the execution of pick and place tasks. [ABSTRACT FROM AUTHOR]

Purpose The brainstem plays an important role in the control of micturition, and brainstem strokes are known to present with micturition dysfunction. Micturition dysfunction in cases of lateral medullary infarction (LMI) is uncommon, but often manifests as urinary retention. In this study, we investigated the neuro-anatomical correlates of urinary retention in patients with LMI. Methods This was a hospital-based retrospective study conducted in the neurology unit of a quaternary-level teaching hospital. Inpatient records from January 2008 to May 2018 were searched using a computerized database. Cases of isolated LMI were identified and those with micturition dysfunction were reviewed. MRI brain images of all patients were viewed, and individual lesions were mapped onto the Montreal Neurological Institute (MNI) space manually using MRIcron. Nonparametric mapping toolbox software was used for voxel-based lesion-symptom analysis. The Liebermeister test was used for statistical analysis, and the resultant statistical map was displayed on the MNI template using MRIcron. Results During the study period, 31 patients with isolated LMI were identified. Their mean age was 48 years and 28 (90%) were male. Six of these patients (19%) developed micturition dysfunction. All 6 patients had urinary retention and 1 patient each had urge incontinence and overflow incontinence. In patients with LMI, the lateral tegmentum of the medulla showed a significant association with urinary retention. Conclusions In patients with isolated LMI, we postulate that disruption of the descending pathway from the pontine micturition centre to the sacral spinal cord at the level of the lateral tegmentum results in urinary retention.

Artificial intelligence techniques have been used in the industry to control complex systems; among these proposals, adaptive Proportional, Integrative, Derivative (PID) controllers are intelligent versions of the most used controller in the industry. This work presents an adaptive neuron PD controller and a multilayer neural PD controller for position tracking of a mobile manipulator. Both controllers are trained by an extended Kalman filter (EKF) algorithm. Neural networks trained with the EKF algorithm show faster learning speeds and convergence times than the training based on backpropagation. The integrative term in PID controllers eliminates the steady-state error, but it provokes oscillations and overshoot. Moreover, the cumulative error in the integral action may produce windup effects such as high settling time, poor performance, and instability. The proposed neural PD controllers adjust their gains dynamically, which eliminates the steady-state error. Then, the integrative term is not required, and oscillations and overshot are highly reduced. Removing the integral part also eliminates the need for anti-windup methodologies to deal with the windup effects. Mobile manipulators are popular due to their mobile capability combined with a dexterous manipulation capability, which gives them the potential for many industrial applications. Applicability of the proposed adaptive neural controllers is presented by simulating experimental results on a KUKA Youbot mobile manipulator, presenting different tests and comparisons with the conventional PID controller and an existing adaptive neuron PID controller.

Emerging evidence suggests the exercise pressor reflex is exaggerated in early stage type 1 diabetes mellitus (T1DM). Piezo channels may play a role in this exaggeration, as blocking these channels attenuates the exaggerated pressor response to tendon stretch in T1DM rats. However, tendon stretch constitutes a different mechanical and physiological stimuli than that occurring during muscle contraction. Therefore, the purpose of this study was to determine the contribution of Piezo channels in evoking the pressor reflex during an intermittent muscle contraction in T1DM. In unanesthetized decerebrate rats, we compared the pressor and cardioaccelerator responses to intermittent muscle contraction before and after locally injecting grammostola spatulata mechanotoxin 4 (GsMTx-4, 0.25 mM) into the hindlimb vasculature. Although GsMTx-4 has a high potency for Piezo channels, it has also been suggested to block transient receptor potential cation (TRPC) channels. We, therefore, performed additional experiments to control for this possibility by also injecting SKF 96365 (10 mM), a TRPC channel blocker. We found that local injection of GsMTx-4, but not SKF 96365, attenuated the exaggerated peak pressor (DMAP before: 33 ± 3 mmHg, after: 22 ± 3 mmHg, P = 0.007) and pressor index (DBPi before: 668 ± 91 mmHg·s, after: 418 ± 81 mmHg·s, P = 0.021) response in streptozotocin (STZ) rats (n = 8). GsMTx-4 attenuated the exaggerated early onset pressor and the pressor response over time, which eliminated peak differences as well as those over time between T1DM and healthy controls. These data suggest that Piezo channels are an effective target to normalize the exercise pressor reflex in T1DM. NEW & NOTEWORTHY This is the first study to demonstrate that blocking Piezo channels is effective in ameliorating the exaggerated exercise pressor reflex evoked by intermittent muscle contraction, commonly occurring during physical activity, in T1DM. Thus, these findings suggest Piezo channels may serve as an effective therapeutic target to reduce the acute and prolonged cardiovascular strain that may occur during dynamic exercise in T1DM. [ABSTRACT FROM AUTHOR]

This paper investigates the leader–follower cooperative tracking control for nonlinear multi-agent systems with unknown nonlinearities, quantized input and unknown control gain. Moreover, the system order of each follower agent can be different from each other. The obstacle of unknown nonlinearities is removed by utilizing the universal approximation property of neural network, and then we introduce a command filter to the backstepping design to generate the virtual control signal and its derivative, which averts the "explosion of complexity" phenomenon. Meanwhile, by developing a novel decomposition of quantizer, Nussbaum-based scheme can be implemented to overcome the difficulties of input quantization and unknown control input coefficient. The controllers are designed only using local information, and the control scheme is fully distributed. Furthermore, there is only one online estimator needs to be calculated for each follower agent. By implementing the proposed controller into the MASs, the consensus tracking errors converge to zero with adjustable accuracy. The examples demonstrate the performance of the presented approach. [ABSTRACT FROM AUTHOR]

In this article, we designed and implemented neural controllers to control a nonlinear and unstable magnetic levitation system composed of an electromagnet and a magnetic disk. The objective was to evaluate the implementation and performance of neural control algorithms in a low-cost hardware. In a first phase, we designed two classical controllers with the objective to provide the training data for the neural controllers. After, we identified several neural models of the levitation system using Nonlinear AutoRegressive eXogenous (NARX)-type neural networks that were used to emulate the forward dynamics of the system. Finally, we designed and implemented three neural control structures: the inverse controller, the internal model controller, and the model reference controller for the control of the levitation system. The neural controllers were tested on a low-cost Arduino control platform through MATLAB/Simulink. The experimental results proved the good performance of the neural controllers. [ABSTRACT FROM AUTHOR]

In this study, we present a novel neural control architecture for gait adaptation and obstacle avoidance of a tailless gecko robot. The control architecture is based on a hierarchical modular structure, consisting of several neural layers and modules. The first layer contains three sensory preprocessing modules which filter sensory noise and generate appropriate descending commands to activate corresponding behaviors through the second and third layers. The second and third layers contain a central pattern generator (CPG) module and CPG postprocessing modules, respectively. The CPG module generates basic rhythmic locomotion patterns, shaped by the CPG postprocessing modules to achieve different gaits (i.e., wave, intermediate, and trot) as well as different climbing directions (i.e., forward and sideways). We use a body inclination sensor to adapt the robot gait while climbing on different slope angles, with infrared sensors to detect an obstacle on its climbing path and activate obstacle avoidance behavior. We successfully tested our control approach on a real tailless gecko robot. As a result, the robot can efficiently climb forward on different slope angles (including 90∘) and automatically adapt its climbing gait accordingly, to maximize climbing speed and ensure stability. It can also avoid an obstacle by changing its climbing direction from forward to sideways. [ABSTRACT FROM AUTHOR]

We compared two standard methods routinely used to assess the grip force (GF; perpendicular force that hand exerts upon the hand-held object) in the studies of coordination of GF and load force (LF; tangential force) in manipulation tasks. A variety of static tasks were tested, and GF-LF coupling (i.e., the maximum cross-correlation between the forces) was assessed. GF was calculated either as the minimum value of the two opposing GF components acting upon the hand-held object (GFmin) or as their average value (GFavg). Although both methods revealed high GF-LF correlation coefficients, most of the data revealed the higher values for GFavg than for GFmin. Therefore, we conclude that the CNS is more likely to take into account GFavg than GFmin when controlling static manipulative actions as well as that GFavg should be the variable of choice in kinetic analyses of static manipulation tasks. [ABSTRACT FROM AUTHOR]

An inspiring scientific cooperation has come to an end, when Gerta Vrbová, an internationally renowned researcher in the field of neuromuscular interactions, passed away on October 2, 2020. Comparative EMG studies had led Gerta to suggest that different contractile properties of fast- and slow-twitch muscle fibers relate to specific firing patterns of their motoneurones. In support of her hypothesis, long term stimulation of fast-twitch muscles with a stimulus pattern resembling that of slow motoneurones, were shown to induce a pronounced fast-to-slow shift in contractile properties. In our cooperation which started in 1970, and also in cooperation with others, Gerta's experiment proved to be an ideal model for the study of neurally controlled changes in phenotype characteristics at various levels of molecular and cellular organization, their time courses and ranges. It has become most important in basic research on the adaptive potential or plasticity of muscle.

Purpose: of ways to improve operational efficiency of center-pivot sprinkling machines on models of neural network control. Materials and methods. Research and field data collection were carried out in Engels district Saratov region. The object of research is center-pivot sprinkling machines. Most center-pivot sprinklers use ON/OFF controllers. These controllers cannot provide optimal results for different time delays, different system parameters and external influences. Modern methods of intelligent data analysis are applied, namely, methods of neurocontrol of dynamic objects. Results. As a result of research, it was found that traditional approaches based only on physical modeling of technical processes and connections often complicate the search for effective solutions. Intelligent control of irrigation technology is essential for maximum efficiency and productivity. An approach based on intelligent data analyses model is proposed, namely, the control of a sprinkler machine using a neural controller. Conclusions. The algorithm for neural control by speed (neural controller) is proposed, which minimizes the deviation of the actual values of irrigation rates from the specified ones, arising under the influence of operational, stochastic factors, up to 1–3 %, and methods of its implementation into control systems to improve the efficiency of control of existing equipment and in the development of modern sprinkler machines. The proposed controller based on an artificial neural network is created using MATLAB. The main parameter of modeling is speed. Improving sprinkler equipment based on intelligent control methods is a new trend in increasing the efficiency of Russian sprinkler equipment.

In this study, an intelligent control scheme is developed for induction motors (IMs). The dynamics of IMs are unknown and are perturbed by the variation of rotor resistance and load changes. The control system has two stages. In the identification stage, the group method of data-handling (GMDH) neural network (NN) was designed for online modeling of the IM. In the control stage, the GMDH-NN was applied to compensate for the impacts of disturbances and uncertainties. The stability is shown by the Lyapunov approach. Simulations demonstrated the good accuracy of the suggested new control approach under disturbances and unknown dynamics.

• We propose a model describing the roles of the human CNS during split-belt treadmill gait adaptation. • Initial adjustments to split-belts rely on proprioceptive feedback to spinal circuits. • Adaptation requires cognitive and cerebellar influence to learn a new gait pattern. • However, despite altered neural control, clinical populations can adapt the gait pattern. Many studies of split-belt treadmill adaptation have been focused on the biomechanical changes that occur in response to walking on belts at different speeds. This process of adaptation, and the ensuing aftereffects that are present when participants return to typical treadmill walking, have inspired the potential use of the split-belt treadmill as a rehabilitation tool. However, a full systematic review of the current split-belt treadmill literature has not yet been published to consolidate what is known about how the human central nervous system (CNS) controls adaptation to this type of symmetry perturbation. A systematic literature search identified 55 studies that investigated the neural control of human gait adaptation to a split-belt treadmill. Studies of infants and manipulated sensory feedback in healthy adults suggest that the initial gait adjustments to split-belt walking are reliant on proprioceptive feedback to inform central pattern generators to modify lower limb muscle activation patterns appropriately. Simultaneously, this literature suggested that proprioceptive and visual feedback inform supraspinal centres for motor planning and motor output to adapt and store a new and efficient gait pattern to walk on belts at different speeds. However, evidence from participants with brain injury (post-stroke, cerebellar lesions) suggest that injury impedes, but does not completely take away, the ability to adjust and adapt aspects of the gait pattern to split-belts. The model proposed from this review provides the overarching roles of the CNS in the adaptation process, specifically in short-term, and potential sites of focus within the human CNS for future rehabilitation-based work. [ABSTRACT FROM AUTHOR]

Leg rigidity is associated with frequent falls in people with Parkinson's disease (PD), suggesting a potential role in functional balance and gait impairments. Changes in the neural state due to secondary tasks, e.g., activation maneuvers, can exacerbate (or "activate") rigidity, possibly increasing the risk of falls. However, the subjective interpretation and coarse classification of the standard clinical rigidity scale has prohibited the systematic, objective assessment of resting and activated leg rigidity. The pendulum test is an objective diagnostic method that we hypothesized would be sensitive enough to characterize resting and activated leg rigidity. We recorded kinematic data and electromyographic signals from rectus femoris and biceps femoris during the pendulum test in 15 individuals with PD, spanning a range of leg rigidity severity. From the recorded data of leg swing kinematics, we measured biomechanical outcomes including first swing excursion, first extension peak, number and duration of the oscillations, resting angle, relaxation index, maximum and minimum angular velocity. We examined associations between biomechanical outcomes and clinical leg rigidity score. We evaluated the effect of increasing rigidity through activation maneuvers on biomechanical outcomes. Finally, we assessed whether either biomechanical outcomes or changes in outcomes with activation were associated with a fall history. Our results suggest that the biomechanical assessment of the pendulum test can objectively quantify parkinsonian leg rigidity. We found that the presence of high rigidity during clinical exam significantly impacted biomechanical outcomes, i.e., first extension peak, number of oscillations, relaxation index, and maximum angular velocity. No differences in the effect of activation maneuvers between groups with clinically assessed low rigidity were observed, suggesting that activated rigidity may be independent of resting rigidity and should be scored as independent variables. Moreover, we found that fall history was more common among people whose rigidity was increased with a secondary task, as measured by biomechanical outcomes. We conclude that different mechanisms contributing to resting and activated rigidity may play an important yet unexplored functional role in balance impairments. The pendulum test may contribute to a better understanding of fundamental mechanisms underlying motor symptoms in PD, evaluating the efficacy of treatments, and predicting the risk of falls. [ABSTRACT FROM AUTHOR]

The superior laryngeal nerve provides detailed sensory information from the mucosal surfaces of laryngeal structures superior to the vocal folds, including the valleculae. Injury to this nerve results in airway penetration and aspiration. Furthermore, such injuries might have an impact on the function of multiple structures involved in intraoral transport and swallowing due to connections within the brainstem. We sought to determine the effects of a surgical lesion of the superior laryngeal nerve on kinematics of the tongue, hyoid, and epiglottis during swallowing. We implanted radio-opaque markers into five infant pigs under anesthesia. Then we fed milk mixed with contrast agent to the pigs while they were recorded via video fluoroscopy, before and after a surgery to transect the superior laryngeal nerve. We digitized and rated airway protection in 177 swallows. We found that in most animals, swallow duration was shorter after nerve lesion. The hyoid also traveled a shorter distance after lesion. Frequently, individuals reacted differently to the same nerve lesion. We suggest that these differences are due to individual differences in neurological connections. When comparing hyoid kinematics between swallows with successful or failed airway protection, we found more consistency among individuals. This indicates that protecting the airway requires specific sets of kinematic events to occur, regardless of the neurological differences among individuals. [ABSTRACT FROM AUTHOR]

Testing new therapies in heart failure (HF) requires a chronic stable model of HF in large animals. Microembolization of the coronary arteries has been used to model HF previously; however, neural control has not been previously explored in this model. Thus the aim of this study was to further characterize neural control in this model of HF. HF was induced by infusion of microspheres (45 micron; 1.3 ml) into the proximal left coronary artery or left descending coronary arteries, with three sequential embolizations over 3 weeks. Twelve to 14 weeks after the final embolization, and when ejection fraction had decreased below 45%, animals were instrumented to record blood pressure and heart rate. Baroreflex control of heart rate was investigated in conscious animals. Additionally, pressure-volume loops were constructed under anesthesia. Embolization-induced HF was associated with a decrease in mean arterial pressure (67 ± 2 vs. 85 ± 4 mmHg, p < 0.05), an increase in heart rate (108 ± 4 vs. 94 ± 4 bpm, p < 0.05), and a significant increase in left ventricular end-diastolic pressure (11.4 ± 2 vs. 6.2 ± 1 mmHg, p < 0.01). Under conscious conditions, there was a significant decrease in the gain (−8.2 ± 2 vs. −4.1 ± 1 beats/min/mmHg, p < 0.05) as well as the lower plateau of the baroreflex in HF compared to control animals. HF was also associated with significantly increased respiratory rate (107 ± 4 vs. 87 ± 4 breaths/min, p < 0.01) and incidence of apneas (520 ± 24 vs. 191 ± 8 apnea periods >4 s, p < 0.05), compared to control sheep. The microembolization model of heart failure is associated with an increase in left ventricular end-diastolic pressure, impaired cardiac function, and altered baroreflex control of the heart. These findings suggest this chronic model of HF is appropriate to use for investigating interventions aimed at improving neural control in HF.

A common neural control mechanism coordinates various types of rhythmic locomotion performed in the sagittal plane, but it is unclear whether frontal plane movements show similar neural patterning in adult humans. The purpose of this study was to compare cutaneous reflex modulation patterns evoked during sagittal and frontal plane rhythmic movements. Eight healthy, neurologically intact adults (three males, five females) walked and sidestepped on a treadmill at approximately 1 Hz. The sural nerve of the dominant (and lead) limb was stimulated randomly every 3–7 steps at eight phases of each gait cycle. Ipsilateral electromyographic recordings from four lower leg muscles and kinematic data from the ankle were collected continuously throughout both tasks. Data from unstimulated gait cycles were used as control trials to calculate middle-latency reflex responses (80–120 ms) and kinematic changes (140–220 ms) following electrical stimulation. Results show that the cutaneous reflex modulation patterns were similar across both tasks despite significant differences in background EMG activity. However, increased reflex amplitudes were observed during the late swing and early stance phases of sidestepping, which directly altered ankle kinematics. These results suggest that the neural control mechanisms responsible for coordinating sagittal locomotion are flexibly modified to coordinate frontal plane activities even with very different foot landing mechanics. [ABSTRACT FROM AUTHOR]

In this article, a novel self-evolving general regression neural network (SEGRNN) is designed for tracking control of a class of discrete-time dynamic systems with unknown dynamics and unknown external disturbances. The proposed controller starts from scratch and automatically adjusts its structure and parameters online to solve the tracking control problem. The proposed controller can add, prune, and replace nodes online according to the control task, external disturbance, and the design specifications. A robustifying control term is also added to SEGRNN's output to mitigate the effects of the external disturbance. The concept of a data reservoir is proposed where a record of the deleted nodes is stored for any future recall, if they are seen to be significant again. Unlike most of the previously proposed self-evolving systems, our controller offers user-friendly design parameters to suit a variety of real-world systems. Lyapunov stability analysis is utilized to study the stability of the suggested controller and to determine an appropriate learning rate for the SEGRNN weights. A continuous stirred-tank reactor simulation example is employed to verify the performance of the proposed controller. The performance of the proposed controller is also compared with a variety of controllers, including adaptive radial basis functional networks, adaptive feed-forward neural networks, adaptive fuzzy logic system, proportional integral derivative controller, sliding-mode controller, and iterative learning controller. Finally, a dc motor platform is used to experimentally validate the controller performance. [ABSTRACT FROM AUTHOR]

Spatially restricted expression of genes by global circulating inducers (hormones, secreted proteins, growth factors, neuromodulators, etc.) was a prerequisite for the evolution of animals. Far from a random occurrence, it is a systematically occurring, certain event, implying that specific information is invested for it to happen. In this minireview, we show for the first time that the expression and regionalization takes place at the level of receptors via a neural mechanism and make an attempt to reconstruct the causal chain from neural signaling to expression of nuclear receptors. Key Findings: Spatially restricted expression of receptor genes was a prerequisite of animal evolution.Neural signals induce spatially restricted expression of nuclear receptors.Neural signals are involved in alternative splicing of nuclear receptors.Nuclear receptor isoforms feedback to change the relevant neural mechanisms. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the underlying age-related differences in dynamic motor control during different step ascent conditions using muscle synergy analysis. Eleven older women (67.0 y ± 2.5) and ten young women (22.5 y ± 1.6) performed stepping in forward and lateral directions at step heights of 10, 20 and 30 cm. Surface electromyography was obtained from 10 lower limb and torso muscles. Non-negative matrix factorization was used to identify sets of (n) synergies across age groups and stepping conditions. In addition, variance accounted for (VAF) by the detected number of synergies was compared to assess complexity of motor control. Finally, correlation coefficients of muscle weightings and between-subject variability of the temporal activation patterns were calculated and compared between age groups and stepping conditions. Four synergies accounted for >85% VAF across age groups and stepping conditions. Age and step height showed a significant negative correlation with VAF during forward stepping but not lateral stepping, with lower VAF indicating higher synergy complexity. Muscle weightings showed higher similarity across step heights in older compared to young women. Neuromuscular control of young and community-dwelling older women could not be differentiated based on the number of synergies extracted. Additional analyses of synergy structure and complexity revealed subtle age- and step-height-related differences, indicating that older women rely on more complex neuromuscular control strategies. [ABSTRACT FROM AUTHOR]

Fifty years ago, David Marr and James Albus proposed a computational model of cerebellar cortical function based on the pioneering circuit models described by John Eccles, Masao Ito and Janos Szentagothai. The Marr–Albus model remains one of the most enduring and influential models in computational neuroscience, despite apparent falsification of some of the original predictions. We re‐examine the Marr–Albus model in the context of the modern theory of computational neural networks and in the context of expanded interpretations of the connectivity and function of cerebellar cortex within the full motor system. By doing so, we show that the original elements of the codon theory continue to make important predictions for cerebellar mechanism, and we show that evidence appearing to contradict the original model is based on an artificially narrow interpretation of cerebellar structure and motor function. [ABSTRACT FROM AUTHOR]