Sensory Feedback Loops Research Articles

Research progress of botulinum toxin A in the therapeutic applications of oral diseases

Botulinum toxin A (BTX-A) is a powerful neurotoxin produced by Clostridium botulinum, which can relieve muscle spasm or limit gland secretion by inhibiting the release of acetylcholine at the neuromuscular/glandular junction. In addition, BTX-A can also play a role in the sensory feedback loop, which can ease pain. Currently, dentists are paying more attention to the cosmetic applications of BTX-A in the oral and maxillofacial region, while their understanding of BTX-A's non-cosmetic applications is still insufficient. Although the specific molecular mechanism of BTX-A in oral diseases has not been fully clarified, with the development of evidence-based medicine, more and more clinical evidence has began to support the effectiveness of BTX-A in the therapeutic applications of oral diseases. This article will briefly review the main molecular mechanisms of BTX-A, the latest clinical research progress of BTX-A at home and abroad in the treatment of oral diseases, clinical contraindications and adverse reactions of BTX-A, providing a new idea for the treatment of oral diseases.

Closing the sensory feedback loop is necessary for effective neurorehabilitation.

Recent advances in neurotechnology enable somatosensory feedback restoration in disabled individuals. This Perspective discusses how closing the sensory feedback loop with brain implants and nerve electrodes for stimulation may improve rehabilitation and assistive systems for patients.

The neuron as a direct data-driven controller

In the quest to model neuronal function amid gaps in physiological data, a promising strategy is to develop a normative theory that interprets neuronal physiology as optimizing a computational objective. This study extends current normative models, which primarily optimize prediction, by conceptualizing neurons as optimal feedback controllers. We posit that neurons, especially those beyond early sensory areas, steer their environment toward a specific desired state through their output. This environment comprises both synaptically interlinked neurons and external motor sensory feedback loops, enabling neurons to evaluate the effectiveness of their control via synaptic feedback. To model neurons as biologically feasible controllers which implicitly identify loop dynamics, infer latent states, and optimize control we utilize the contemporary direct data-driven control (DD-DC) framework. Our DD-DC neuron model explains various neurophysiological phenomena: the shift from potentiation to depression in spike-timing-dependent plasticity with its asymmetry, the duration and adaptive nature of feedforward and feedback neuronal filters, the imprecision in spike generation under constant stimulation, and the characteristic operational variability and noise in the brain. Our model presents a significant departure from the traditional, feedforward, instant-response McCulloch-Pitts-Rosenblatt neuron, offering a modern, biologically informed fundamental unit for constructing neural networks.

Transcriptome and secretome profiling of sensory neurons reveals sex differences in pathways relevant to insulin sensing and insulin secretion.

Sensory neurons in the dorsal root ganglia (DRG) convey somatosensory and metabolic cues to the central nervous system and release substances from stimulated terminal endings in peripheral organs. Sex-biased variations driven by the sex chromosome complement (XX and XY) have been implicated in the sensory-islet crosstalk. However, the molecular underpinnings of these male-female differences are not known. Here, we aim to characterize the molecular repertoire and the secretome profile of the lower thoracic spinal sensory neurons and to identify molecules with sex-biased insulin sensing- and/or insulin secretion-modulating activity that are encoded independently of circulating gonadal sex hormones. We used transcriptomics and proteomics to uncover differentially expressed genes and secreted molecules in lower thoracic T5-12 DRG sensory neurons derived from sexually immature 3-week-old male and female C57BL/6J mice. Comparative transcriptome and proteome analyses revealed differential gene expression and protein secretion in DRG neurons in males and females. The transcriptome analysis identified, among others, higher insulin signaling/sensing capabilities in female DRG neurons; secretome screening uncovered several sex-specific candidate molecules with potential regulatory functions in pancreatic β cells. Together, these data suggest a putative role of sensory interoception of insulin in the DRG-islet crosstalk with implications in sensory feedback loops in the regulation of β-cell activity in a sex-biased manner. Finally, we provide a valuable resource of molecular and secretory targets that can be leveraged for understanding insulin interoception and insulin secretion and inform the development of novel studies/approaches to fathom the role of the sensory-islet axis in the regulation of energy balance in males and females.

Evaluating the effect of non-invasive force feedback on prosthetic grasp force modulation in participants with and without limb loss.

Grasping an object is one of the most common and complex actions performed by humans. The human brain can adapt and update the grasp dynamics through information received from sensory feedback. Prosthetic hands can assist with the mechanical performance of grasping, however currently commercially available prostheses do not address the disruption of the sensory feedback loop. Providing feedback about a prosthetic hand's grasp force magnitude is a top priority for those with limb loss. This study tested a wearable haptic system, i.e., the Clenching Upper-Limb Force Feedback device (CUFF), which was integrated with a novel robotic hand (The SoftHand Pro). The SoftHand Pro was controlled with myoelectrics of the forearm muscles. Five participants with limb loss and nineteen able-bodied participants completed a constrained grasping task (with and without feedback) which required modulation of the grasp to reach a target force. This task was performed while depriving participants of incidental sensory sources (vision and hearing were significantly limited with glasses and headphones). The data were analyzed with Functional Principal Component Analysis (fPCA). CUFF feedback improved grasp precision for participants with limb loss who typically use body-powered prostheses as well as a sub-set of able-bodied participants. Further testing, that is more functional and allows participants to use all sensory sources, is needed to determine if CUFF feedback can accelerate mastery of myoelectric control or would benefit specific patient sub-groups.

Effects of exercise on electroencephalography-recorded neural oscillations: a systematic review

ABSTRACT Research on the effects of exercise on cortical activity has grown significantly, with a predominant focus on the technique of electroencephalography (EEG). Technological advancements in EEG render this technique suitable for studies that explore human movement. There is a noticeable gap in the literature concerning how EEG-recorded cortical oscillatory activity is affected by exercise. Accordingly, the aim of this review was to summarise studies that investigated the effects of exercise on brain activity using EEG. This was a systematic review of 47 studies, predicated on PRISMA guidelines. The results were, on the whole, equivocal in nature, with the exception that activity in the alpha and beta frequency bands increased both during and post-exercise across the frontal, central, and limbic regions. The reported increases could be attributed to a variety of neural processes, such as neuro-connectivity, cortical inhibition, and sensory feedback loops. Future researchers need to give careful consideration to exercise parameters (e.g. mode of exercise, intensity, duration) to facilitate their interpretation of experimental data. The present findings support the notion that exercise alters alpha and beta neural oscillations but more work is needed to provide a fuller picture of the brain processes that manifest during exercise.

What gets on the nerves of cardiac patients? Pathophysiological changes in cardiac innervation.

The autonomic nervous system regulates cardiac function by balancing the actions of sympathetic and parasympathetic inputs to the heart. Intrinsic cardiac neurocircuits integrate these autonomic signals to fine‐tune cardiac control, and sensory feedback loops regulate autonomic transmission in the face of external stimuli. These interconnected neural systems allow the heart to adapt to constantly changing circumstances that range from simple fluctuations in body position to running a marathon. The cardiac reflexes that serve to maintain homeostasis in health are disrupted in many disease states. This is often characterized by increased sympathetic and decreased parasympathetic transmission. Studies of cardiovascular disease reveal remodelling of cardiac neurocircuits at several functional and anatomical levels. Central circuits change so that sympathetic pathways become hyperactive, while parasympathetic circuits exhibit decreased activity. Peripheral sensory nerves also become hyperactive in disease, which increases patients’ risk for poor cardiac outcomes. Injury and disease also alter the types of neurotransmitters and neuropeptides released by autonomic nerves in the heart, and can lead to regional hyperinnervation (increased nerve density) or denervation (decreased nerve density) of cardiac tissue. The mechanisms responsible for neural remodelling are not fully understood, but neurotrophins and inflammatory cytokines are likely involved. Areas of active investigation include the role of immune cells and inflammation in neural remodelling, as well as the role of glia in modulating peripheral neuronal activity. Our growing understanding of autonomic dysfunction in disease has facilitated development of new therapeutic strategies to improve health outcomes.

Development of EMG-FMG Based Prosthesis With PVDF-Film Vibrational Feedback Control

The paper proposes an EMG-FMG-based prosthesis using a vibrational feedback method. The control loop for bio-feedback consists of a feed-forward loop for controlling the prosthetic hand and a sensory feedback loop for delivering the sense of vibration according to the distance with an object. In addition, the motion of the prosthetic hand using the EMG-FMG knit band sensor as an input device is generated via a decision tree algorithm, the distance is measured using a capacitive knit data glove, and the vibrational feedback using a PVDF piezoelectric actuator is provided. The control loop for bio-feedback was verified experimentally. First, the performance of the sensors and control methods was analyzed, and the results of EMG-FMG motion recognition and vibrational feedback were verified. Second, the experiment was conducted on ten subjects who wore prosthesis to which the bio-feedback method was applied. Thanks to the control loops for bio-feedback, the grasping time with blindfolded was reduced by 2.92 seconds and the number of failures decreased by 1.04 times. As a result, it was confirmed that the control loop for bio-feedback could improve the performance of the prosthesis.

Flexible Hybrid Sensor Systems with Feedback Functions

AbstractSkin‐like wearable sensors are regarded as key technologies toward home‐based healthcare, human–machine interfaces, robotics, prostheses, and enhanced augmented/virtual reality (AR/VR). Inspired by human somatosensory functions, artificial sensory feedback systems play vital roles in shaping interactions with complex environments and timely decision‐making. This study presents an overview of recent advances in feedback‐driven, closed‐loop skin‐inspired flexible sensor systems that make use of emerging functional nanomaterials and elaborate structures. Drawing on feedback solutions, four categories of sensor systems are highlighted, which include prosthesis‐ and AR/VR‐based human–machine interfaces, smartphone‐based approaches for point‐of‐care detection, and smart wearable displays for direct signal visualizations. Furthermore, the progress of machine learning on the reliable recognition of massive quantities of signals generated by flexible sensor networks is briefly discussed. The state‐of‐the‐art hybrid sensor techniques, along with other emerging strategies, will enable total sensory feedback loop systems to be developed for next‐generation electronic skins.

Recent Developments in Prosthesis Sensors, Texture Recognition, and Sensory Stimulation for Upper Limb Prostheses.

Current developments being made in upper limb prostheses are focused on replacing lost sensory information to the amputees. Providing sensory stimulation from the prosthesis can directly improve control over the prosthetic and provide a sense of body ownership. The focus of this review article is on recent developments while including foundational knowledge for some of the critical concepts in neural prostheses. Reported concepts follow the flow of information from sensors to signal processing, with emphasis on texture recognition, and then to sensory stimulation strategies that reestablish the lost sensory feedback loop. Prosthetic sensors are used to detect the physical environment, converting pressure, force, and position into electrical signals. The electrical signals can then be processed in an effort to identify the surrounding environment using distinctive characteristics such as stiffness and texture. In order for the amputee to use this information in a natural manner, there must be real-time sensory stimulation, perception, and motor control of the prosthesis. Although truly complete sensory replacement has not yet been realized, some basic percepts can be partially restored, allowing progress towards a more realistic prosthesis with natural sensations.

Stochastic optimal open-loop control as a theory of force and impedance planning via muscle co-contraction.

Understanding the underpinnings of biological motor control is an important issue in movement neuroscience. Optimal control theory is a leading framework to rationalize this problem in computational terms. Previously, optimal control models have been devised either in deterministic or in stochastic settings to account for different aspects of motor control (e.g. average behavior versus trial-to-trial variability). While these approaches have yielded valuable insights about motor control, they typically fail in explaining muscle co-contraction. Co-contraction of a group of muscles associated to a motor function (e.g. agonist and antagonist muscles spanning a joint) contributes to modulate the mechanical impedance of the neuromusculoskeletal system (e.g. joint viscoelasticity) and is thought to be mainly under the influence of descending signals from the brain. Here we present a theory suggesting that one primary goal of motor planning may be to issue feedforward (open-loop) motor commands that optimally specify both force and impedance, according to noisy neuromusculoskeletal dynamics and to optimality criteria based on effort and variance. We show that the proposed framework naturally accounts for several previous experimental findings regarding the regulation of force and impedance via muscle co-contraction in the upper-limb. Stochastic optimal (closed-loop) control, preprogramming feedback gains but requiring on-line state estimation processes through long-latency sensory feedback loops, may then complement this nominal feedforward motor command to fully determine the limb's mechanical impedance. The proposed stochastic optimal open-loop control theory may provide new insights about the general articulation of feedforward/feedback control mechanisms and justify the occurrence of muscle co-contraction in the neural control of movement.

Effect of Botulinum Toxin A on Bladder Pain-Molecular Evidence and Animal Studies.

Botulinum toxin A (BTX-A) is a powerful neurotoxin with long-lasting activity that blocks muscle contractions. In addition to effects on neuromuscular junctions, BTX-A also plays a role in sensory feedback loops, suggesting the potentiality for pain relief. Although the only approved indications for BTX-A in the bladder are neurogenic detrusor overactivity and refractory overactive bladder, BTX-A injections to treat bladder pain refractory to conventional therapies are also recommended. The mechanism of BTX-A activity in bladder pain is complex, with several hypotheses proposed in recent studies. Here we comprehensively reviewed properties of BTX-A in peripheral afferent and efferent nerves, the inhibition of nociceptive neurotransmitter release, the reduction of stretch-related visceral pain, and its anti-inflammatory effects on the bladder urothelium. Studies have also revealed possible effects of BTX-A in the human brain. However, further basic and clinical studies are warranted to provide solid evidence-based support in using BTX-A to treat bladder pain.

EEG-Based Volitional Control of Prosthetic Legs for Walking in Different Terrains

More natural and intuitive control is expected to maximize the auxiliary effect of the powered prosthetic leg for lower limb amputees. In order to realize the stable and flexible walking of prosthetic legs in different terrains according to human intention, a brain-computer interface (BCI) based on motor imagery (MI) is developed. For the raw electroencephalogram (EEG) signals, discrete wavelet transform (DWT) is utilized to extract the time-frequency domain features, which are used as the input signals of the common spatial pattern (CSP) to obtain the time-frequency-space domain features of EEG signals. Then, a support vector machine (SVM) classifier and a directed acyclic graph (DAG) structure are combined to classify multiclass imaginary tasks. According to the result of human intention recognition, the prosthetic leg performs the corresponding gait trajectory generated by coding the ground reaction force (GRF). In addition, a sensory feedback loop is established by functional electrical stimulation (FES), which feeds back the movement of the prosthetic leg to human in real time. The effectiveness and feasibility of the developed EEG-based volitional control of powered prosthetic legs have been validated by three subjects, all of whom were able to fulfill smoothly walking on the floor, ascending stairs, and descending stairs according to their own intentions using prosthetic legs.

Neuromuscular adaptations and sensorimotor integration following a unilateral transfemoral amputation

BackgroundFollowing an amputation, the human postural control system develops neuromuscular adaptations to regain an effective postural control. We investigated the compensatory mechanisms behind these adaptations and how sensorimotor integration is affected after a lower-limb transfemoral amputation.MethodsCenter of pressure (CoP) data of 12 unilateral transfemoral amputees and 12 age-matched able-bodied subjects were recorded during quiet standing with eyes open (EO) and closed (EC). CoP adjustments under each leg were recorded to study their contribution to posture control. The spatial structure of the CoP displacements was characterized by measuring the mean distance, the mean velocity of the CoP adjustments, and the sway area. The Entropic Half-Life (EnHL) quantifies the temporal structure of the CoP adjustments and was used to infer disrupted sensory feedback loops in amputees. We expanded the analysis with measures of weight-bearing imbalance and asymmetry, and with two standardized balance assessments, the Berg Balance Scale (BBS) and Timed Up-and-Go (TUG).ResultsThere was no difference in the EnHL values of amputees and controls when combining the contributions of both limbs (p = 0.754). However, amputees presented significant differences between the EnHL values of the intact and prosthetic limb (p < 0.001). Suppressing vision reduced the EnHL values of the intact (p = 0.001) and both legs (p = 0.028), but not in controls. Vision feedback in amputees also had a significant effect (increase) on the mean CoP distance (p < 0.001), CoP velocity (p < 0.001) and sway area (p = 0.007). Amputees presented an asymmetrical stance. The EnHL values of the intact limb in amputees were positively correlated to the BBS scores (EO: ρ = 0.43, EC: ρ = 0.44) and negatively correlated to the TUG times (EO: ρ = − 0.59, EC: ρ = − 0.69).ConclusionThese results suggest that besides the asymmetry in load distribution, there exist neuromuscular adaptations after an amputation, possibly related to the loss of sensory feedback and an altered sensorimotor integration. The EnHL values suggest that the somatosensory system predominates in the control of the intact leg. Further, suppressing the visual system caused instability in amputees, but had a minimal impact on the CoP dynamics of controls. These findings points toward the importance of providing somatosensory feedback in lower-limb prosthesis to reestablish a normal postural control.Trial registrationDRKS00015254, registered on September 20th, 2018.

Rapid limb-specific modulation of vestibular contributions to ankle muscle activity during locomotion.

The vestibular influence on human walking is phase-dependent and modulated across both limbs with changes in locomotor velocity and cadence. Using a split-belt treadmill, we show that vestibular influence on locomotor activity is modulated independently in each limb. The independent vestibular modulation of muscle activity from each limb occurs rapidly at the onset of split-belt walking, over a shorter time course relative to the characteristic split-belt error-correction mechanisms (i.e. muscle activity and kinematics) associated with locomotor adaptation. Together, the present results indicate that the nervous system rapidly modulates the vestibular influence of each limb separately through processes involving ongoing sensory feedback loops. These findings help us understand how vestibular information is used to accommodate the variable and commonplace demands of locomotion, such as turning or navigating irregular terrain. During walking, the vestibular influence on locomotor activity is phase-dependent and modulated in both limbs with changes in velocity. It is unclear, however, whether this bilateral modulation is due to a coordinated mechanism between both limbs or instead through limb-specific processes that remain masked by the symmetric nature of locomotion. Here, human subjects walked on a split-belt treadmill with one belt moving at 0.4ms-1 and the other moving at 0.8ms-1 while exposed to an electrical vestibular stimulus. Muscle activity was recorded bilaterally around the ankles of each limb and used to compare vestibulo-muscular coupling between velocity-matched and unmatched tied-belt walking. In general, response magnitudes decreased by ∼20-50% and occurred ∼13-20% earlier in the stride cycle at the higher belt velocity. This velocity-dependent modulation of vestibular-evoked muscle activity was retained during split-belt walking and was similar, within each limb, to velocity-matched tied-belt walking. These results demonstrate that the vestibular influence on ankle muscles during locomotion can be adapted independently to each limb. Furthermore, modulation of vestibular-evoked muscle responses occurred rapidly (∼13-34 strides) after onset of split-belt walking. This rapid adaptation contrasted with the prolonged adaptation in step length symmetry (∼128 strides) as well as EMG magnitude and timing (∼40-100 and ∼20-70 strides, respectively). These results suggest that vestibular influence on ankle muscle control is adjusted rapidly in sensorimotor control loops as opposed to longer-term error correction mechanisms commonly associated with split-belt adaptation. Rapid limb-specific sensorimotor feedback adaptation may be advantageous for asymmetric overground locomotion, such as navigating irregular terrain or turning.

Rigidity and Flexibility: The Central Basis of Inter-Leg Coordination in the Locust.

Many motor behaviors, and specifically locomotion, are the product of an intricate interplay between neuronal oscillators known as central pattern generators (CPGs), descending central commands, and sensory feedback loops. The relative contribution of each of these components to the final behavior determines the trade-off between fixed movements and those that are carefully adapted to the environment. Here we sought to decipher the endogenous, default, motor output of the CPG network controlling the locust legs, in the absence of any sensory or descending influences. We induced rhythmic activity in the leg CPGs in isolated nervous system preparations, using different application procedures of the muscarinic agonist pilocarpine. We found that the three thoracic ganglia, each controlling a pair of legs, have different inherent bilateral coupling. Furthermore, we found that the pharmacological activation of one ganglion is sufficient to induce activity in the other, untreated, ganglia. Each ganglion was thus capable to impart its own bilateral inherent pattern onto the other ganglia via a tight synchrony among the ipsilateral CPGs. By cutting a connective and severing the lateral-longitudinal connections, we were able to uncouple the oscillators’ activity. While the bilateral connections demonstrated a high modularity, the ipsilateral CPGs maintained a strict synchronized activity. These findings suggest that the central infrastructure behind locust walking features both rigid elements, which presumably support the generation of stereotypic orchestrated leg movements, and flexible elements, which might provide the central basis for adaptations to the environment and to higher motor commands.

The Botulinum Toxin as a Therapeutic Agent: Molecular Structure and Mechanism of Action in Motor and Sensory Systems.

Botulinum neurotoxin (BoNT) produced by Clostridium botulinum is the most potent molecule known to mankind. Higher potency of BoNT is attributed to several factors, including structural and functional uniqueness, target specificity, and longevity. Although BoNT is an extremely toxic molecule, it is now increasingly used for the treatment of disorders related to muscle hyperactivity and glandular hyperactivity. Weakening of muscles due to peripheral action of BoNT produces a therapeutic effect. Depending on the target tissue, BoNT can block the cholinergic neuromuscular or cholinergic autonomic innervation of exocrine glands and smooth muscles. In recent observations of the analgesic properties of BoNT, the toxin modifies the sensory feedback loop to the central nervous system. Differential effects of BoNT in excitatory and inhibitory neurons provide a unique therapeutic tool. In this review the authors briefly summarize the structure and mechanism of actions of BoNT on motor and sensory neurons to explain its therapeutic effects and future potential.

Mechanisms of interpersonal sway synchrony and stability.

Here we explain the neural and mechanical mechanisms responsible for synchronizing sway and improving postural control during physical contact with another standing person. Postural control processes were modelled using an inverted pendulum under continuous feedback control. Interpersonal interactions were simulated either by coupling the sensory feedback loops or by physically coupling the pendulums with a damped spring. These simulations precisely recreated the timing and magnitude of sway interactions observed empirically. Effects of firmly grasping another person's shoulder were explained entirely by the mechanical linkage. This contrasted with light touch and/or visual contact, which were explained by a sensory weighting phenomenon; each person's estimate of upright was based on a weighted combination of veridical sensory feedback combined with a small contribution from their partner. Under these circumstances, the model predicted reductions in sway even without the need to distinguish between self and partner motion. Our findings explain the seemingly paradoxical observation that touching a swaying person can improve postural control.

A key region in the human parietal cortex for processing proprioceptive hand feedback during reaching movements

Seemingly effortless, we adjust our movements to continuously changing environments. After initiation of a goal-directed movement, the motor command is under constant control of sensory feedback loops. The main sensory signals contributing to movement control are vision and proprioception. Recent neuroimaging studies have focused mainly on identifying the parts of the posterior parietal cortex (PPC) that contribute to visually guided movements. We used event-related TMS and force perturbations of the reaching hand to test whether the same sub-regions of the left PPC contribute to the processing of proprioceptive-only and of multi-sensory information about hand position when reaching for a visual target. TMS over two distinct stimulation sites elicited differential effects: TMS applied over the posterior part of the medial intraparietal sulcus (mIPS) compromised reaching accuracy when proprioception was the only sensory information available for correcting the reaching error. When visual feedback of the hand was available, TMS over the anterior intraparietal sulcus (aIPS) prolonged reaching time. Our results show for the first time the causal involvement of the posterior mIPS in processing proprioceptive feedback for online reaching control, and demonstrate that distinct cortical areas process proprioceptive-only and multi-sensory information for fast feedback corrections.

On-line motion synthesis and adaptation using a trajectory database

Autonomous robots cannot be programmed in advance for all possible situations. Instead, they should be able to generalize the previously acquired knowledge to operate in new situations as they arise. A possible solution to the problem of generalization is to apply statistical methods that can generate useful robot responses in situations for which the robot has not been specifically instructed how to respond. In this paper we propose a methodology for the statistical generalization of the available sensorimotor knowledge in real-time. Example trajectories are generalized by applying Gaussian process regression, using the parameters describing a task as query points into the trajectory database. We show on real-world tasks that the proposed methodology can be integrated into a sensory feedback loop, where the generalization algorithm is applied in real-time to adapt robot motion to the perceived changes of the external world.