Motor Tasks Research Articles

The effect of VR on fine motor performance by older adults: a comparison between real and virtual tasks

Virtual Reality (VR) technology has the potential to support the aging population and improve testing of daily abilities to detect functional decline. In multiple research studies, VR performance of participants has been assessed by measuring time to complete test, but the effect of learning how to use the VR system and differences between real and virtual environments have been understudied, especially for fine motor tasks. In this study, 20 older adults ages 65–84 performed a task that required fine motor skills in real-life and then in a VR replica of the same task. All participants completed the task in each setting with no difficulties. A clear learning effect was observed in VR, which was attributed to learning how to use the device itself. Still, participants could not reach the same level of performance (time) in VR as in real-life. Participants rated the VR task more mentally and physically demanding than in real-life, as well as more stressful, but with an overall low cognitive demand. In an exploratory cluster analysis, participants with an average age of 69 years old had more technological devices, found the VR system more usable and realistic than participants in the group with an average of 76 years old. This study demonstrated that VR influences time to complete a fine motor task, and that learning effects related to the system could be confounded with actual task performance if not properly considered in VR studies with older adults.

Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition

Dynamic mode (DM) decomposition decomposes spatiotemporal signals into basic oscillatory components (DMs). DMs can improve the accuracy of neural decoding when used with the nonlinear Grassmann kernel, compared to conventional power features. However, such kernel-based machine learning algorithms have three limitations: large computational time preventing real-time application, incompatibility with non-kernel algorithms, and low interpretability. Here, we propose a mapping function corresponding to the Grassmann kernel that explicitly transforms DMs into spatial DM (sDM) features, which can be used in any machine learning algorithm. Using electrocorticographic signals recorded during various movement and visual perception tasks, the sDM features were shown to improve the decoding accuracy and computational time compared to conventional methods. Furthermore, the components of the sDM features informative for decoding showed similar characteristics to the high-γ power of the signals, but with higher trial-to-trial reproducibility. The proposed sDM features enable fast, accurate, and interpretable neural decoding.

Effects of IMU sensor-to-segment calibration on clinical 3D elbow joint angles estimation

Introduction: Inertial Measurement Units (IMU) require a sensor-to-segment calibration procedure in order to compute anatomically accurate joint angles and, thereby, be employed in healthcare and rehabilitation. Research literature proposes several algorithms to address this issue. However, determining an optimal calibration procedure is challenging due to the large number of variables that affect elbow joint angle accuracy, including 3D joint axis, movement performed, complex anatomy, and notable skin artefacts. Therefore, this paper aims to compare three types of calibration techniques against an optical motion capture reference system during several movement tasks to provide recommendations on the most suitable calibration for the elbow joint.Methods: Thirteen healthy subjects were instrumented with IMU sensors and optical marker clusters. Each participant performed a series of static poses and movements to calibrate the instruments and, subsequently, performed single-plane and multi-joint tasks. The metrics used to evaluate joint angle accuracy are Range of Motion (ROM) error, Root Mean Squared Error (RMSE), and offset. We performed a three-way RM ANOVA to evaluate the effect of joint axis and movement task on three calibration techniques: N-Pose (NP), Functional Calibration (FC) and Manual Alignment (MA).Results: Despite small effect sizes in ROM Error, NP displayed the least precision among calibrations due to interquartile ranges as large as 24.6°. RMSE showed significant differences among calibrations and a large effect size where MA performed best (RMSE = 6.3°) and was comparable with FC (RMSE = 7.2°). Offset showed a large effect size in the calibration*axes interaction where FC and MA performed similarly.Conclusion: Therefore, we recommend MA as the preferred calibration method for the elbow joint due to its simplicity and ease of use. Alternatively, FC can be a valid option when the wearer is unable to hold a predetermined posture.

Investigating cognitive-motor effects during slacklining using mobile EEG

Balancing is a very important skill, supporting many daily life activities. Cognitive-motor interference (CMI) dual-tasking paradigms have been established to identify the cognitive load of complex natural motor tasks, such as running and cycling. Here we used wireless, smartphone-recorded electroencephalography (EEG) and motion sensors while participants were either standing on firm ground or on a slackline, either performing an auditory oddball task (dual-task condition) or no task simultaneously (single-task condition). We expected a reduced amplitude and increased latency of the P3 event-related potential (ERP) component to target sounds for the complex balancing compared to the standing on ground condition, and a further decrease in the dual-task compared to the single-task balancing condition. Further, we expected greater postural sway during slacklining while performing the concurrent auditory attention task. Twenty young, experienced slackliners performed an auditory oddball task, silently counting rare target tones presented in a series of frequently occurring standard tones. Results revealed similar P3 topographies and morphologies during both movement conditions. Contrary to our predictions we observed neither significantly reduced P3 amplitudes, nor significantly increased latencies during slacklining. Unexpectedly, we found greater postural sway during slacklining with no additional task compared to dual-tasking. Further, we found a significant correlation between the participant’s skill level and P3 latency, but not between skill level and P3 amplitude or postural sway. This pattern of results indicates an interference effect for less skilled individuals, whereas individuals with a high skill level may have shown a facilitation effect. Our study adds to the growing field of research demonstrating that ERPs obtained in uncontrolled, daily-life situations can provide meaningful results. We argue that the individual CMI effects on the P3 ERP reflects how demanding the balancing task is for untrained individuals, which draws on limited resources that are otherwise available for auditory attention processing. In future work, the analysis of concurrently recorded motion-sensor signals will help to identify the cognitive demands of motor tasks executed in natural, uncontrolled environments.

Perturbation-based dual task assessment in older adults with mild cognitive impairment

BackgroundDual tasking (i.e., concurrent performance of motor and cognitive task) is significantly impaired in older adults with mild cognitive impairment (OAwMCI) compared to cognitively intact older adults (CIOA) and has been associated with increased fall risk. Dual task studies have primarily examined volitionally driven events, and the effects of mild cognitive impairment on reactive balance control (i.e., the ability to recover from unexpected balance threats) are unexplored. We examined the effect of cognitive tasks on reactive balance control in OAwMCI compared to CIOA.MethodsAdults >55 years were included and completed the Montreal Cognitive Assessment (MoCA) to categorize them as OAwMCI (MoCA: 18–24, n = 15) or CIOA (MoCA: ≥25, n = 15). Both OAwMCI [MoCA: 22.4 (2.2), 65.4 (6.1) years, 3 females] and CIOA [MoCA: 28.4 (1.3), 68.2 (5.5) years, 10 females] responded to large magnitude stance slip-like perturbations alone (single task) and while performing perceptual cognitive tasks targeting the visuomotor domain (target and tracking game). In these tasks, participants rotated their head horizontally to control a motion mouse and catch a falling target (target game) or track a moving object (track). Margin of stability (MOS) and fall outcome (harness load cell >30% body weight) were used to quantify reactive balance control. Cognitive performance was determined using performance error (target) and sum of errors (tracking). A 3 × 2 repeated measures ANOVA examined the effect of group and task on MOS, and generalized estimating equations (GEE) model was used to determine changes in fall outcome between groups and tasks. 2 × 2 repeated measures ANOVAs examined the effect of group and task on cognitive performance.ResultsCompared to CIOA, OAwMCI exhibited significantly deteriorated MOS and greater number of falls during both single task and dual task (p < 0.05), and lower dual task tracking performance (p < 0.01). Compared to single task, both OAwMCI and CIOA exhibited significantly deteriorated perceptual cognitive performance during dual task (p < 0.05); however, no change in MOS or fall outcome between single task and dual task was observed.ConclusionCognitive impairment may diminish the ability to compensate and provide attentional resources demanded by sensory systems to integrate perturbation specific information, resulting in deteriorated ability to recover balance control among OAwMCI.

Video mirror feedback induces more extensive brain activation compared to the mirror box: an fNIRS study in healthy adults

BackgroundMirror therapy (MT) has been shown to be effective for motor recovery of the upper limb after a stroke. The cerebral mechanisms of mirror therapy involve the precuneus, premotor cortex and primary motor cortex. Activation of the precuneus could be a marker of this effectiveness. MT has some limitations and video therapy (VT) tools are being developed to optimise MT. While the clinical superiority of these new tools remains to be demonstrated, comparing the cerebral mechanisms of these different modalities will provide a better understanding of the related neuroplasticity mechanisms.MethodsThirty-three right-handed healthy individuals were included in this study. Participants were equipped with a near-infrared spectroscopy headset covering the precuneus, the premotor cortex and the primary motor cortex of each hemisphere. Each participant performed 3 tasks: a MT task (right hand movement and left visual feedback), a VT task (left visual feedback only) and a control task (right hand movement only). Perception of illusion was rated for MT and VT by asking participants to rate the intensity using a visual analogue scale. The aim of this study was to compare brain activation during MT and VT. We also evaluated the correlation between the precuneus activation and the illusion quality of the visual mirrored feedback.ResultsWe found a greater activation of the precuneus contralateral to the visual feedback during VT than during MT. We also showed that activation of primary motor cortex and premotor cortex contralateral to visual feedback was more extensive in VT than in MT. Illusion perception was not correlated with precuneus activation.ConclusionVT led to greater activation of a parieto-frontal network than MT. This could result from a greater focus on visual feedback and a reduction in interhemispheric inhibition in VT because of the absence of an associated motor task. These results suggest that VT could promote neuroplasticity mechanisms in people with brain lesions more efficiently than MT.Clinical trial registrationNCT04738851.

Modeling the cortical response elicited by wrist manipulation via a nonlinear delay differential embedding.

Regarding motor processes, modeling healthy people's brains is essential to understand the brain activity in people with motor impairments. However, little research has been undertaken when external forces disturb limbs, having limited information on physiological pathways. Therefore, in this paper, a nonlinear delay differential embedding model is used to estimate the brain response elicited by externally controlled wrist movement in healthy individuals. The aim is to improve the understanding of the relationship between a controlled wrist movement and the generated cortical activity of healthy people, helping to disclose the underlying mechanisms and physiological relationships involved in the motor event. To evaluate the model, a public database from the Delft University of Technology is used, which contains electroencephalographic recordings of ten healthy subjects while wrist movement was externally provoked by a robotic system. In this work, the cortical response related to movement is identified via Independent Component Analysis and estimated based on a nonlinear delay differential embedding model. After a cross-validation analysis, the model performance reaches 90.21% ± 4.46% Variance Accounted For, and Correlation 95.14% ± 2.31%. The proposed methodology allows to select the model degree, to estimate a general predominant operation mode of the cortical response elicited by wrist movement. The obtained results revealed two facts that had not previously been reported: the movement's acceleration affects the cortical response, and a common delayed activity is shared among subjects. Going forward, identifying biomarkers related to motor tasks could aid in the evaluation of rehabilitation treatments for patients with upper limbs motor impairments.

Paradoxical Long-term Memory Augmentation following Temporal Pairing between "Limited" and "Extensive" Motor Sequence Training Experiences.

Consecutive training on two movement sequences often leads to retroactive interference-obstructing memory for the initially trained sequence but not for the second. However, in the context of hippocampal-system dependent memories, a poor learning experience, memory for which would soon decay, can be enhanced if temporally paired with a "strong," memory triggering experience. The synaptic tagging and capture hypothesis explains this paradoxical enhancement by suggesting that only strong experiences generate cellular resources necessary for synaptic remodeling. However, synapses engaged in a "weak" learning experience can capture and utilize plasticity-related resources generated for a subsequent strong learning experience. Here, we tested whether such "paradoxical" outcome would result in the context of motor (procedural) memory, if two movement sequences are unequally trained, consecutively. We show, in young adults (n = 100), that limited practice on a novel sequence of finger-to-thumb opposition movements led to different long-term outcomes, depending on whether and when (5 min, 5 hr) it was followed by extensive training on a different sequence. Five-minute pairing, only, resulted in overnight gains for the limited-trained sequence that were well-retained a week later; the overnight gains for the extensively trained sequence were compromised. Thus, consecutive training on different motor tasks can result in mnemonic interactions other than interference. We propose that the newly discovered mnemonic interaction provides the first-tier behavioral evidence in support of the possible applicability of notions stemming from the synaptic tagging and capture hypothesis in relation to human motor memory generation, specifically in relation to the practice-dependent consolidation of novel explicitly instructed movement sequences.

Electrophysiological correlates of dentate nucleus deep brain stimulation for post-stroke motor recovery

While ipsilesional cortical electroencephalography has been associated with post-stroke recovery mechanisms and outcomes, the role of cerebellum and its interaction with the ipsilesional cortex is still largely unknown. We have previously shown that post-stroke motor control relies on increased cortico-cerebellar coherence (CCC) in the low beta band to maintain motor task accuracy and to compensate for decreased excitability of the ipsilesional cortex. We now extend our work to investigate corticocerebellar network changes associated with chronic stimulation of the dentato-thalamo-cortical pathway aimed at promoting post-stroke motor rehabilitation. We investigated the excitability of ipsilesional cortex, dentate (DN), and their interaction as a function of treatment outcome measures. Relative to baseline, ten human participants (two women) at the end of 4-8 months of DN deep brain stimulation (DBS) showed 1) significantly improved motor control indexed by computerized motor tasks; 2) significant increase in ipsilesional premotor cortex event-related desynchronization that correlated with improvements in motor function; and 3) significant decrease in CCC, including causal interactions between the DN and ipsilesional cortex, which also correlated with motor function improvements. Furthermore, we show that the functional state of the DN in the post-stroke state and its connectivity with ipsilesional cortex were predictive of motor outcomes associated with DN-DBS. The findings suggest that as participants recovered, the ipsilesional cortex became more involved in motor control, with less demand on the cerebellum to support task planning and execution. Our data provide unique mechanistic insights into the functional state of cortico-cerebellar-cortical network after stroke and its modulation by DN-DBS.Significance StatementThe study aims to understand the brain mechanisms underlying the effects of cerebellar dentate deep brain stimulation (DN-DBS), a novel upcoming therapy for chronic stroke. We provide evidence that functional improvements as a result of DN-DBS therapy were accompanied by significant improvements in task behavior and ipsilesional cortex excitability. More importantly,

Older adults use fewer muscles to overcome perturbations during a seated locomotor task.

Locomotor perturbations provide insights into the human's response to motor errors. We investigated the differences in motor adaptation and muscle co-contraction between young and older adults during perturbed arms and legs recumbent stepping. We hypothesized that besides prolonged adaptation due to use-dependent learning, older adults would exhibit greater muscle co-contraction than young adults in response to the perturbations. Perturbations were brief increases in resistance applied during each stride at the extension-onset or mid-extension of the left or right leg. Seventeen young adults and eleven older adults completed four 10-minute perturbed stepping tasks. Subjects were instructed to follow a visual pacing cue, step smoothly, and use all their limbs to drive the stepper. Results showed that young and older adults did not decrease their errors with more perturbation experience, and errors did not wash out after perturbations were removed. Interestingly, older adults consistently had smaller motor errors than young adults in response to the perturbations. Older adults used fewer muscles to drive the stepper and had greater co-contraction than young adults. The results suggest that despite similar motor error responses, young and older adults use distinctive muscle recruitment patterns to perform the motor task. Age-related motor strategies help track motor changes across the human lifespan and are a baseline for rehabilitation and performance assessment.

Nonlinear EEG Analysis During Motor and Cognitive Tasks in Patients With Long COVID: A Dynamic Systems Approach.

Introduction. Nonlinear EEG provides information about dynamic properties of the brain. This study aimed to compare nonlinear EEG parameters estimated from patients with Long COVID in different cognitive and motor tasks. Materials and Methods. This 12-month prospective cohort study included 83 patients with Long COVID: 53 symptomatic and 30 asymptomatic. Brain electrical activity was evaluated by EEG in 4 situations: (1) at rest, (2) during the Trail Making Test Part A (TMT-A), (3) during the TMT Part B (TMT-B), and (4) during a coordination task: the Box and Blocks Test (BBT). Nonlinear EEG parameters were estimated in the time domain (activity and complexity). Assessments were made at 0 to 3, 3 to 6, and 6 to 12 months after inclusion. Results. There was a decrease in activity and complexity during the TMT-A and TMT-B, and an increase of these parameters during the BBT in both groups. There was an increase in activity at rest and during the TMT-A in the COVID-19 group at 0 to 3 months compared to the control, an increase in activity in the TMT-B in the COVID-19 group at 3 to 6 months compared to the control, and reduced activity and complexity at rest and during the TMT-A at 6 to 12 months compared to the control. Conclusion. The tasks followed a pattern of increased activity and complexity in cognitive tasks, which decreased during the coordination task. It was also observed that an increase in activity at rest and during cognitive tasks in the early stages, and reduced activity and complexity at rest and during cognitive tasks in the late phases of Long COVID.

Pain Education and Virtual Reality Improves Pain, Pain-related Fear of Movement, and Trunk Kinematics in Individuals with Persistent Low Back Pain.

To evaluate the effect of combining pain education and virtual reality exposure therapy using a cognitive behavioural therapy-informed approach (VR-CBT) on pain intensity, fear of movement, and trunk movement, in individuals with persistent low back pain. Thirty-seven participants were recruited in a single cohort repeated measures study, attending three sessions one week apart. The VR-CBT intervention included standardised pain education (Session 1), and virtual reality exposure therapy (Session 2) incorporating gameplay with mixed reality video capture and reflective feedback of performance. Outcome measures (Pain intensity, pain-related fear of movement (Tampa Scale of Kinesiophobia), and trunk kinematics during functional movements (maximum amplitude, peak velocity) were collected at baseline (Session1), and one week following education (Session 2) and virtual reality exposure therapy (Session 3). One-way repeated measures ANOVAs evaluated change in outcomes from baseline to completion. Post-hoc contrasts evaluated effect sizes for the education and virtual reality components of VR-CBT. Thirty-four participants completed all sessions. Significant (P<0.001) reductions were observed in Mean(SD) pain (baseline 5.9(1.5); completion 4.3(2.1)) and fear of movement (baseline 42.6(6.4); completion 34.3(7.4)). Large effect sizes (Cohen's d) were observed for education (pain intensity 0.85; fear of movement 1.28) while the addition of virtual reality exposure therapy demonstrated very small insignificant effect sizes, (pain intensity 0.10; fear of movement 0.18). Peak trunk velocity, but not amplitude, increased significantly (P<0.05) across trunk movement tasks. A VR-CBT intervention improved pain, pain-related fear of movement, and trunk kinematics. Further research should explore increased VR-CBT dosage and mechanisms underlying improvement.

Simultaneous whole-head electrophysiological recordings using EEG and OPM-MEG

Abstract Electroencephalography (EEG) and magnetoencephalography (MEG) non-invasively measure human brain electrophysiology. They differ in nature; MEG offers better performance whilst EEG (a wearable platform) is more practical. They are also complementary, with studies showing that concurrent MEG/EEG provides advantages over either modality alone, and consequently clinical guidelines for MEG in epilepsy recommend simultaneous acquisition of MEG and EEG. In recent years, new instrumentation— the optically pumped magnetometer (OPM)— has had a significant impact on MEG, offering improved performance, lifespan compliance, and wearable MEG systems. Nevertheless, the ability to carry out simultaneous EEG/OPM-MEG remains critical. Here, we investigated whether simultaneous, wearable, whole-head EEG and OPM-MEG measurably degrades signal quality in either modality. We employed two tasks: a motor task known to modulate beta oscillations, and an eyes-open/closed task known to modulate alpha oscillations. In both, we characterised the performance of EEG alone, OPM-MEG alone, and concurrent EEG/OPM-MEG. Results show that the SNR of the beta response was similar, regardless of whether modalities were used individually or concurrently. Likewise, our alpha band recordings demonstrated that signal contrast was stable, regardless of the concurrent recording. We also demonstrate significant advantages of OPM-MEG; specifically, the OPM-MEG signal is less correlated across channels and less susceptible to interference from non-brain sources. Our results suggest that there are no barriers to simultaneous wearable EEG/OPM-MEG, and consequently this technique is ripe for neuroscientific and clinical adoption. This will be important in the clinic where simultaneous EEG and OPM-MEG recordings will facilitate better interpretation of OPM-MEG data in patients.

Developing Functional Thinking: from Concrete to Abstract Through an Embodied Design

AbstractIn addressing the challenge of fostering functional thinking (FT) in secondary school students, our research centered on the question of how an embodied design can enhance FT’s different aspects, including input–output, covariation, and correspondence views. Drawing from embodied cognition theory and focusing on an action- and perception-based task design that uses light ray contexts and different function representations, we developed a digital-embodied learning environment, using the nomogram as a central representation. Our pilot study involving four eighth-grade students provided insights into their physical interactions with these modules through a multi-touch digital interface. Analysis of video and audio recordings from the pilots, including students’ hand gestures and verbal expressions, was guided by comparing hypothetical learning activities with the actual learning activities. The results show that (1) a concrete light ray context enables students to ground the abstract mathematical function concept; (2) the bimanual coordinating motion tasks, incorporating the covariation aspect of FT, allow students to connect their bodily experience with function properties; and (3) our embodied and dragging tasks support insight in the conversion between nomograms and graphs of functions, encouraging students’ correspondence thinking by providing multiple perspectives to understand, reason about, and manipulate the function. In conclusion, our findings suggest the potential of digital-embodied tasks in fostering FT, evident in students’ diverse strategies and reasoning.

Gray matter volume of functionally relevant primary motor cortex is causally related to learning a hand motor task.

Variability in brain structure is associated with the capacity for behavioral change. However, a causal link between specific brain areas and behavioral change (such as motor learning) has not been demonstrated. We hypothesized that greater gray matter volume of a primary motor cortex (M1) area active during a hand motor learning task is positively correlated with subsequent learning of the task, and that the disruption of this area blocks learning of the task. Healthy participants underwent structural MRI before learning a skilled hand motor task. Next, participants performed this learning task during fMRI to determine M1 areas functionally active during this task. This functional ROI was anatomically constrained with M1 boundaries to create a group-level "Active-M1" ROI used to measure gray matter volume in each participant. Greater gray matter volume in the left hemisphere Active-M1 ROI was related to greater motor learning in the corresponding right hand. When M1 hand area was disrupted with repetitive transcranial stimulation (rTMS), learning of the motor task was blocked, confirming its causal link to motor learning. Our combined imaging and rTMS approach revealed greater cortical volume in a task-relevant M1 area is causally related to learning of a hand motor task in healthy humans.

Revolutionizing motor dysfunction treatment: a novel closed-loop electrical stimulator guided by multiple motor tasks with predictive control

Functional electrical stimulation (FES) has been demonstrated as a viable method for addressing motor dysfunction in individuals affected by stroke, spinal cord injury, and other etiologies. By eliciting muscle contractions to facilitate joint movements, FES plays a crucial role in fostering the restoration of motor function compromised nervous system. In response to the challenge of muscle fatigue associated with conventional FES protocols, a novel biofeedback electrical stimulator incorporating multi-motor tasks and predictive control algorithms has been developed to enable adaptive modulation of stimulation parameters. The study initially establishes a Hammerstein model for the stimulated muscle group, representing a time-varying relationship between the stimulation pulse width and the root mean square (RMS) of the surface electromyography (sEMG). An online parameter identification algorithm utilizing recursive least squares is employed to estimate the time-varying parameters of the Hammerstein model. Predictive control is then implemented through feedback corrections based on the comparison between predicted and actual outputs, guided by an optimization objective function. The integration of predictive control and roll optimization enables closed-loop control of muscle stimulation. The motor training tasks of elbow flexion and extension, wrist flexion and extension, and five-finger grasping were selected for experimental validation. The results indicate that the model parameters were accurately identified, with a RMS error of 3.83% between actual and predicted values. Furthermore, the predictive control algorithm, based on the motor tasks, effectively adjusted the stimulus parameters to ensure that the stimulated muscle groups can achieve the desired sEMG characteristic trajectory. The biofeedback electrical stimulator that was developed has the potential to assist patients experiencing motor dysfunction in achieving the appropriate joint movements. This research provides a foundation for a novel intelligent electrical stimulation model.

Dissecting Bayes: Using influence measures to test normative use of probability density information derived from a sample.

Bayesian decision theory (BDT) is frequently used to model normative performance in perceptual, motor, and cognitive decision tasks where the possible outcomes of actions are associated with rewards or penalties. The resulting normative models specify how decision makers should encode and combine information about uncertainty and value-step by step-in order to maximize their expected reward. When prior, likelihood, and posterior are probabilities, the Bayesian computation requires only simple arithmetic operations: addition, etc. We focus on visual cognitive tasks where Bayesian computations are carried out not on probabilities but on (1) probability density functions and (2) these probability density functions are derived from samples. We break the BDT model into a series of computations and test human ability to carry out each of these computations in isolation. We test three necessary properties of normative use of pdf information derived from a sample-accuracy, additivity and influence. Influence measures allow us to assess how much weight each point in the sample is assigned in making decisions and allow us to compare normative use (weighting) of samples to actual, point by point. We find that human decision makers violate accuracy and additivity systematically but that the cost of failure in accuracy or additivity would be minor in common decision tasks. However, a comparison of measured influence for each sample point with normative influence measures demonstrates that the individual's use of sample information is markedly different from the predictions of BDT. We will show that the normative BDT model takes into account the geometric symmetries of the pdf while the human decision maker does not. An alternative model basing decisions on a single extreme sample point provided a better account for participants' data than the normative BDT model.

Characterization of Human Shoulder Joint Stiffness Across 3D Arm Postures and Its Sex Differences.

Understanding the characteristics of shoulder joint stiffness can offer insights into how the shoulder joint contributes to arm stability and assists in various arm postures and movements. This study aims to characterize posture-dependent shoulder stiffness in a three-dimensional (3D) space and investigate its potential sex differences. A multi-degree-of-freedom, parallel-actuated shoulder exoskeleton robot was used' to perturb the participant's shoulder joint and measure the resulting torque responses while participants relaxed their shoulder muscles. The group average results of 40 healthy individuals (20 males and 20 females) revealed that arm postures significantly affect shoulder stiffness, particularly in postures involving shoulder flexion/extension and horizontal flexion/extension. Shoulder stiffness consistently increased as the shoulder flexion angle decreased and the shoulder horizontal flexion/extension approached the limit of its range of motion. The comparative group results between males and females indicated that shoulder stiffness in males was greater than that in females across all 15 arm postures measured in this study. Even after normalizing the data by subject body mass, the female group showed significantly lower stiffness than the male group in 12 out of the 15 arm postures. The results highlight that 3D arm postures and sex significantly affect shoulder stiffness even under relaxed muscles. This study provides valuable foundations for future studies aimed at characterizing shoulder stiffness in the context of active muscles and dynamic movement tasks, evaluating changes in shoulder stiffness following neuromuscular injuries, and formulating rehabilitative training protocols for individuals suffering from shoulder problems.

How reliable are femoropelvic kinematics during deep squats? The influence of subject-specific skeletal modelling on measurement variability

BackgroundBiplanar radiography displays promising results in the production of subject-specific (S.specific) biomechanical models. However, the focus has predominantly centred on methodological investigations in gait analysis. Exploring the influence of such models on the analysis of high range of motion tasks linked to hip pathologies is warranted. The aim of this study is to investigate the effect of S.Specific modelling techniques on the reliability of deep squats kinematics in comparison to generic modelling. Methods8 able-bodied male participants attended 5 motion capture sessions conducted by 3 observers and performed 5 deep squats in each. Prior to each session a biplanar scan was acquired with the reflective-markers attached. Inverse kinematics of pelvis and thigh segments were calculated based on S.specific and Generic model definition. Agreement between the two models femoropelvic orientation in standing was assessed with Bland-Altman plots and paired t- tests. Inter-trial, inter-session, inter-observer variability and observer/trial difference and ratio were calculated for squat kinematic data derived from the two modelling approaches. ResultsCompared to the Generic model, the S.Specific model produced a calibration trial that is significantly offset into more posterior pelvis tilt (-2.8±2.7), hip extension (-2.2±3.8), hip abduction (-1.2±3.6) and external rotation (-13.8±11.4). The S.specific model produced significantly different squat kinematics in the sagittal plane of the pelvis (entire squat cycle) and hip (between 40-60% of the squat cycle). Variability analysis indicated that the error magnitude between the two models was comparable (difference<2°). The S.specific model exhibited a lower variability in the observer/trial ratio in the sagittal pelvis and hip, the frontal hip, but showed a higher variability in the transverse hip. SignificanceS.specific modelling appears to introduce a calibration offset that primarily translates into an effect in the sagittal plane kinematics. However, the clinical added value of S.specific modelling in terms of reducing experimental sources of kinematic variability was limited.

A sirtuin 6 activator in the pipeline: New perspectives in depressive disorder treatment

Major Depressive Disorder (MDD) is among the most prevalent mental illnesses worldwide. Its symptoms include persistent feelings of sadness, loss of interest in previously enjoyed activities, and a lack of motivation for daily tasks. While FDA-approved medications are available, they often come with side effects, especially those targeting monoamine neurotransmitters like SSRIs and SNRIs. Thus, there is a need for innovative medications with different mechanisms of action. Sp-624, a derivative of griseofulvin, is currently undergoing clinical trials for MDD treatment. It acts as a sirtuin 6 (SIRT6) activator, offering a novel approach to treating this disorder. This article discusses the biochemical aspects related to the mechanism of action of sp-624, provides a brief overview of related patents, and highlights ongoing clinical trials involving this substance.