Electrophysiological Correlates of Changes in Reaction Time Based on Stimulus Intensity

Background: Although reaction time is commonly used as an indicator of central nervous system integrity, little is currently understood about the mechanisms that determine processing time. In the current study, we are interested in determining the differences in electrophysiological events associated with significant changes in reaction time that could be elicited by changes in stimulus intensity. The primary objective is to assess the effect of increasing stimulus intensity on the latency and amplitude of afferent inputs to the somatosensory cortex, and their relation to reaction time. Methods: Median nerve stimulation was applied to the non-dominant hand of 12 healthy young adults at two different stimulus intensities (HIGH & LOW). Participants were asked to either press a button as fast as possible with their dominant hand or remain quiet following the stimulus. Electroencephalography was used to measure somatosensory evoked potentials (SEPs) and event related potentials (ERPs). Electromyography from the flexor digitorum superficialis of the button-pressing hand was used to assess reaction time. Response time was the time of button press. Results: Reaction time and response time were significantly shorter following the HIGH intensity stimulus compared to the LOW intensity stimulus. There were no differences in SEP (N20 & P24) peak latencies and peak-to-peak amplitude for the two stimulus intensities. ERPs, locked to response time, demonstrated a significantly larger pre-movement negativity to positivity following the HIGH intensity stimulus over the Cz electrode

Kinetics Analysis Of Multi-Segment Trunk After Experimental Errors Minimization

A two-dimensional analytical heat conduction model of an annular composite fin has been carried out. The composite fins composed of a porous polyethylene core, a square aluminum insert, and metallic zinc coating layers, was fabricated using wire-arc spraying technology. Analytical solutions of temperature distribution, energy dissipation and fin efficiency through the fins at natural convection condition have been proposed

Trunk Stability during Postural Control: Tool Development and Analysis

Trunk instability is a major problem for people with spinal cord injury (SCI); it not only limits their independence, but also leads to secondary health complications such as kyphosis, pressure sores, and respiratory dysfunction. In exploring mechanisms that may facilitate or compromise postural stability, dynamic models are very useful because the spine dynamics are difficult to study in vivo compared to other structures of the body. Therefore, one objective of this work was to develop a detailed three-dimensional dynamic model of the human trunk as a tool for investigating the neural-mechanical control strategy that healthy people apply to maintain trunk stability during various tasks. Since trunk control is fairly complex, however, another objective of this work was to provide insights into the balance control strategy of a simpler neuro-musculo-skeletal system that may facilitate future studies on trunk control. For this purpose, the control of the ankle joint complex during quiet standing (anterior-posterior degree of freedom) was studied in place of the trunk. The obtained results reveal that a neural-mechanical control scheme using a proportional-derivative controller as the neural control strategy can overcome a large sensory-motor (feedback) time delay and stabilize the ankle joint during quiet standing. Moreover, a detailed dynamic model of the trunk has been developed that is: (1) based on highly accurate geometric models; and (2) universally applicable. Thus, this work also responds to the postulation that structurally more complex models are needed to better characterize the biomechanics of multifaceted systems. Combining the developed biomechanical tools for the trunk with the postural control insights for the ankle joint during standing will be beneficial for: (1) understanding the neural-mechanical control strategy that facilitates trunk stability in healthy people; and for (2) developing neuroprostheses for trunk stability after SCI and other neurological disorders.Ph

Technology-based balance performance assessment can eliminate floor and ceiling effects

Abstract Many clinical measurement tools for balance have ceiling effects. Technology-based assessments using virtual reality systems such as the Computer-Assisted Rehabilitation Environment (CAREN) may provide a way to develop objective, quantitative measures that scale from low to high levels of difficulty. Our objective was to: (1) develop a performance assessment tool (PAT) for the CAREN; (2) quantify the reliability of the tool; (3) validate the scores against clinical balance measures; and (4) compare the scores from a population with balance impairments to those from able-bodied individuals in a cross-sectional validation study. Three games were developed on the CAREN and tested on 49 participants (36 able-bodied and 13 with impaired mobility). For each module, the corresponding measures were transformed into scores using a series of functions such that ceiling and flooring effects would be minimized. The results showed an association between scores and age, an overlap in scores from impaired high-performance individuals and able-bodied low performance individuals, and a correlation of PAT scores with other clinical tests. Several of the limitations of current clinical tools, including floor and ceiling effects, were overcome by the PAT, suggesting that the PAT can be used to monitor the effect of rehabilitation and training

Revised Submission (R3) to 'IEEE TNSRE' - Neural-Mechanical Feedback Control Scheme Generates Physiological Ankle Torque Fluctuation during Quiet Stance Running Title: Neural-Mechanical Control Scheme of Quiet Stance Neural-Mechanical Control Scheme of Qu

ABSTRACT We have recently demonstrated in simulations and experiments that a proportional and derivative (PD) feedback controller can regulate the active ankle torque during quiet stance and stabilize the body despite a long sensory-motor time delay. The purpose of the present study was to: 1) model the active and passive ankle torque mechanisms and identify their contributions to the total ankle torque during standing; and 2) investigate whether a neural-mechanical control scheme that implements the PD controller as the neural controller can successfully generate the total ankle torque as observed in healthy individuals during quiet stance. Fourteen young subjects were asked to stand still on a force platform to acquire data for model optimization and validation. During two trials of 30 s each, the fluctuation of the body angle, the electromyogram of the right soleus muscle, and the ankle torque were recorded. Using these data, the parameters of: 1) the active and passive torque mechanisms (Model I); and 2) the PD controller within the neural-mechanical control scheme (Model II) were optimized to achieve potential matching between the measured and predicted ankle torque. The performance of the two models was finally validated with a new set of data. Our results indicate that not only the passive, but also the active ankle torque mechanism contributes significantly to the total ankle torque and, hence, to body stabilization during quiet stance. In addition, we conclude that the proposed neuralmechanical control scheme successfully mimics the physiological control strategy during quiet stance and that a PD controller is a legitimate model for the strategy that the central nervous system applies to regulate the active ankle torque in spite of a long sensory-motor time delay

Algorithmic Implementation of Visually Guided Interceptive Actions: Harmonic Ratios and Stimulation Invariants

This research presents a novel algorithmic implementation to improve the analysis of visually controlled interception and accompanying motor action through the computational application of harmonic ratios and stimulation invariants. Unlike traditional models that focus mainly on psychological aspects, our approach integrates the relevant constructs into a practical mathematical framework. This allows for dynamic prediction of interception points with improved accuracy and real-time perception–action capabilities, essential for applications in neurorehabilitation and virtual reality. Our methodology uses stimulation invariants as key parameters within a mathematical model to quantitatively predict and improve interception outcomes. The results demonstrate the superior performance of our algorithms over conventional methods, confirming their potential for advancing robotic vision systems and adaptive virtual environments. By translating complex theories of visual perception into algorithmic solutions, this study provides innovative ways to improve motion perception and interactive systems. This study aims to articulate the complex interplay of geometry, perception, and technology in understanding and utilizing cross ratios at infinity, emphasizing their practical applications in virtual and augmented reality settings