TRANSCRANIAL DIRECT STIMULATION IN THE NEUROMODULATION OF CONTROLLING MAIN SYMPTOMS OF PARKINSON’S DISEASE: A CASE STUDY

Parkinson’s disease (PD) is a central nervous system neurodegenerative disorder that primarily affects the motor system, decreasing motor coordination, balance and generating tremors, and a progressive loss of everyday mobility, including walking. This study was conducted to verify the effects of Transcranial Direct Current Stimulation (tDCS) on balance, motor control, and the quality of life in Parkinson’s disease patients. The patient received three treatments consisting of 10 sessions of 20 minutes each and a one-week interval between treatments. Active stimulation was applied on the primary motor cortex (M1), the dorsolateral prefrontal cortex (DLPFC), and the dorsolateral prefrontal cortex (D Sham-tDCS. DLPFC stimulation produced the best improvements in terms of motor control, balance, gait, and overall PD symptoms, as evaluated by different scales and questionnaires. As a result, active stimulation of the DLPFC produced superior outcomes and may contribute to treating Parkinson’s disease.

The Control of Movements via Motor Gamma Oscillations

The ability to perform movements is vital for our daily life. Our actions are embedded in a complex environment where we need to deal efficiently in the face of unforeseen events. Neural oscillations play an important role in basic sensorimotor processes related to the execution and preparation of movements. In this review, I will describe the state of the art regarding the role of motor gamma oscillations in the control of movements. Experimental evidence from electrophysiological studies has shown that motor gamma oscillations accomplish a range of functions in motor control beyond merely signaling the execution of movements. However, these additional aspects associated with motor gamma oscillation remain to be fully clarified. Future work on different spatial, temporal and spectral scales is required to further understand the implications of gamma oscillations in motor control.

Effects of virtual reality-based motor control training on inflammation, oxidative stress, neuroplasticity and upper limb motor function in patients with chronic stroke: a randomized controlled trial

Background Immersive virtual reality (VR)-based motor control training (VRT) is an innovative approach to improve motor function in patients with stroke. Currently, outcome measures for immersive VRT mainly focus on motor function. However, serum biomarkers help detect precise and subtle physiological changes. Therefore, this study aimed to identify the effects of immersive VRT on inflammation, oxidative stress, neuroplasticity and upper limb motor function in stroke patients. Methods Thirty patients with chronic stroke were randomized to the VRT or conventional occupational therapy (COT) groups. Serum biomarkers including interleukin 6 (IL-6), intracellular adhesion molecule 1 (ICAM-1), heme oxygenase 1 (HO-1), 8-hydroxy-2-deoxyguanosine (8-OHdG), and brain-derived neurotrophic factor (BDNF) were assessed to reflect inflammation, oxidative stress and neuroplasticity. Clinical assessments including active range of motion of the upper limb and the Fugl-Meyer Assessment for upper extremity (FMA-UE) were also used. Two-way mixed analyses of variance (ANOVAs) were used to examine the effects of the intervention (VRT and COT) and time on serum biomarkers and upper limb motor function. Results We found significant time effects in serum IL-6 (p = 0.010), HO-1 (p = 0.002), 8-OHdG (p = 0.045), and all items/subscales of the clinical assessments (ps < 0.05), except FMA-UE-Coordination/Speed (p = 0.055). However, significant group effects existed only in items of the AROM-Elbow Extension (p = 0.007) and AROM-Forearm Pronation (p = 0.048). Moreover, significant interactions between time and group existed in item/subscales of FMA-UE-Shoulder/Elbow/Forearm (p = 0.004), FMA-UE-Total score (p = 0.008), and AROM-Shoulder Flexion (p = 0.001). Conclusion This was the first study to combine the effectiveness of immersive VRT using serum biomarkers as outcome measures. Our study demonstrated promising results that support the further application of commercial and immersive VR technologies in patients with chronic stroke.

EXPRESS: Don’t blame yourself: Conscious source monitoring modulates feedback control during speech production

Sensory feedback plays an important role in speech motor control. One of the main sources of evidence for this are studies where online auditory feedback is perturbed during ongoing speech. In motor control, it is therefore crucial to distinguish between sensory feedback and externally generated sensory events. This is called source monitoring. Previous altered feedback studies have taken non-conscious source monitoring for granted, as automatic responses to altered sensory feedback imply that the feedback changes are processed as self-caused. However, the role of conscious source monitoring is unclear. The current study investigated whether conscious source monitoring modulates responses to unexpected pitch changes in auditory feedback. During a first block, some participants spontaneously attributed the pitch shifts to themselves (self-blamers) while others attributed them to an external source (other-blamers). Before block 2, all participants were informed that the pitch shifts were experimentally induced. The self-blamers then showed a reduction in response magnitude in block 2 compared with block 1, while the other-blamers did not. This suggests that conscious source monitoring modulates responses to altered auditory feedback, such that consciously ascribing feedback to oneself leads to larger compensation responses. These results can be accounted for within the dominant comparator framework, where conscious source monitoring could modulate the gain on sensory feedback. Alternatively, the results can be naturally explained from an inferential framework, where conscious knowledge may bias the priors in a Bayesian process to determine the most likely source of a sensory event.

Aerodynamics and motor control of ultrasonic vocalizations for social communication in mice and rats

Background Rodent ultrasonic vocalizations (USVs) are crucial to their social communication and a widely used translational tool for linking gene mutations to behavior. To maximize the causal interpretation of experimental treatments, we need to understand how neural control affects USV production. However, both the aerodynamics of USV production and its neural control remain poorly understood. Results Here, we test three intralaryngeal whistle mechanisms—the wall and alar edge impingement, and shallow cavity tone—by combining in vitro larynx physiology and individual-based 3D airway reconstructions with fluid dynamics simulations. Our results show that in the mouse and rat larynx, USVs are produced by a glottal jet impinging on the thyroid inner wall. Furthermore, we implemented an empirically based motor control model that predicts motor gesture trajectories of USV call types. Conclusions Our results identify wall impingement as the aerodynamic mechanism of USV production in rats and mice. Furthermore, our empirically based motor control model shows that both neural and anatomical components contribute to USV production, which suggests that changes in strain specific USVs or USV changes in disease models can result from both altered motor programs and laryngeal geometry. Our work provides a quantitative neuromechanical framework to evaluate the contributions of brain and body in shaping USVs and a first step in linking descending motor control to USV production.

Multiparameter Identification of Permanent Magnet Synchronous Motor Based on Model Reference Adaptive System—Simulated Annealing Particle Swarm Optimization Algorithm

The accurate identification of permanent magnet synchronous motor (PMSM) parameters is the basis for high-performance drive control. The traditional PMSM multiparameter identification method experiences problems with the uncertainty of the identification results and low identification accuracy due to the under-ranking of the mathematical model of motor control. A multiparameter identification of PMSM based on a model reference adaptive system and simulated annealing particle swarm optimization (MRAS-SAPSO) is proposed here. The algorithm first identifies the electrical parameters of the PMSM (stator winding resistance R, cross-axis inductance L, and magnetic linkage ψf) by means of the model reference adaptive system method. Second, the result is used as the initial population in particle swarm optimization identification to further optimize and identify the electrical and mechanical parameters (moment of inertia J and damping coefficient B) in the motor control system. Additionally, in order to avoid problems such as premature convergence of the particle swarm in the optimization search process, the results of the adaptive simulated annealing algorithm to optimize multiparameter identification are introduced. The simulation experiment results show that the five identification parameters obtained by the MRAS-SAPSO algorithm are highly accurate and stable, and the errors between them and the real values are below 2%. This also verifies the effectiveness and reliability of this identification method.

Causal effects of motor control on gait kinematics after orthopedic surgery in cerebral palsy: a machine-learning approach

Background Altered motor control is common in cerebral palsy (CP). Understanding how altered motor control effects movement and treatment outcomes is important, but challenging due to complex interactions between impairments. While regression can be used to examine associations between impairments and gait, causal modeling provides a mathematical framework to specify assumed causal relationships, identify covariates that may introduce bias, and test model plausibility. The goal of this research was to quantify the causal effects of altered motor control and other impairments on gait, before and after single-event multi-level orthopedic surgery (SEMLS). Methods We evaluated the impact of SEMLS on change in Gait Deviation Index (GDI) between gait analyses. We constructed our causal model with a Directed Acyclic Graph that included the assumed causal relationships between SEMLS, change in GDI, baseline GDI (GDIpre), baseline neurologic and orthopedic impairments (Imppre), age, and surgical history. We identified the adjustment set to evaluate the causal effect of SEMLS on change in GDI and the impact of Imppre on change in GDI and GDIpre. We used Bayesian Additive Regression Trees (BART) and accumulated local effects to assess relative effects. Results We prospectively recruited a cohort of children with bilateral CP undergoing SEMLS (N=54, 35 males, age: 10.5+/-3.1 years) and identified a control cohort with bilateral CP who did not undergo SEMLS (N=55, 30 males, age: 10.0+/-3.4 years). There was a small positive causal effect of SEMLS on change in GDI (1.68 GDI points). Altered motor control (i.e., dynamic and static motor control) and strength had strong effects on GDIpre, but minimal effects on change in GDI. Spasticity and orthopedic impairments had minimal effects on GDIpre or change in GDI. Conclusions Altered motor control and other baseline impairments did have a strong effect on GDIpre, indicating that these impairments do have a causal effect on a child's gait pattern but minimal effect on expected changes in GDI after SEMLS. Heterogeneity in outcomes suggests there are other factors contributing to changes in gait. Identifying these factors and employing causal methods to examine the complex relationships between impairments and movement will be required to advance our understanding and care of children with CP.

Dissociation of impulsive traits by subthalamic metabotropic glutamate receptor 4

Behavioral strategies require gating of premature responses to optimize outcomes. Several brain areas control impulsive actions, but the neuronal basis of natural variation in impulsivity between individuals remain largely unknown. Here, by combining a Go/No-Go behavioral assay with resting state (rs) functional MRI in mice, we identified the subthalamic nucleus (STN), a known gate for motor control in the basal ganglia, as a major hot spot for trait impulsivity. In vivo recorded STN neural activity encoded impulsive action as a separable state from basic motor control, characterized by decoupled STN/Substantia nigra pars reticulata (SNr) mesoscale networks. Optogenetic modulation of STN activity bi-directionally controlled impulsive behavior. Pharmacological and genetic manipulations showed that these impulsive actions are modulated by metabotropic glutamate receptor 4 (mGlu4) function in STN and its coupling to SNr in a behavioral trait-dependent manner, and independently of general motor function. In conclusion, STN circuitry multiplexes motor control and trait impulsivity, which are molecularly dissociated by mGlu4. This provides a potential mechanism for the genetic modulation of impulsive behavior, a clinically relevant predictor for developing psychiatric disorders associated with impulsivity.

Intrinsic somatosensory feedback supports motor control and learning to operate artificial body parts

Objective Considerable resources are being invested to enhance the control and usability of artificial limbs through the delivery of unnatural forms of somatosensory feedback. Here, we investigated whether intrinsic somatosensory information from the body part(s) remotely controlling an artificial limb can be leveraged by the motor system to support control and skill learning. Approach In a placebo-controlled design, we used local anaesthetic to attenuate somatosensory inputs to the big toes while participants learned to operate through pressure sensors a toe-controlled and hand-worn robotic extra finger. Motor learning outcomes were compared against a control group who received sham anaesthetic and quantified in three different task scenarios: while operating in isolation from, in synchronous coordination, and collaboration with, the biological fingers. Main results Both groups were able to learn to operate the robotic extra finger, presumably due to abundance of visual feedback and other relevant sensory cues. Importantly, the availability of displaced somatosensory cues from the distal bodily controllers facilitated the acquisition of isolated robotic finger movements, the retention and transfer of synchronous hand-robot coordination skills, and performance under cognitive load. Motor performance was not impaired by toes anaesthesia when tasks involved close collaboration with the biological fingers, indicating that the motor system can close the sensory feedback gap by dynamically integrating task-intrinsic somatosensory signals from multiple, and even distal, body- parts. Significance Together, our findings demonstrate that there are multiple natural avenues to provide intrinsic surrogate somatosensory information to support motor control of an artificial body part, beyond artificial stimulation.