Estimation of the Motor Threshold for Near-Rectangular Stimuli Using the Hodgkin–Huxley Model

The motor threshold measurement is a standard in preintervention probing in TMS experiments. We aim to predict the motor threshold for near-rectangular stimuli to efficiently determine the motor threshold size before any experiments take place. Estimating the behavior of large-scale networks requires dynamically accurate and efficient modeling. We utilized a Hodgkin–Huxley (HH) type model to evaluate motor threshold values and computationally validated its function with known true threshold data from 50 participants trials from state-of-the-art published datasets. For monophasic, bidirectional, and unidirectional rectangular stimuli in posterior-anterior or anterior-posterior directions as generated by the cTMS device, computational modeling of the HH model captured the experimentally measured population-averaged motor threshold values at high precision (maximum error ≤ 8%). The convergence of our biophysically based modeling study with experimental data in humans reveals that the effect of the stimulus shape is strongly correlated with the activation kinetics of the voltage-gated ion channels. The proposed method can reliably predict motor threshold size using the conductance-based neuronal models and could therefore be embedded in new generation neurostimulators. Advancements in neural modeling will make it possible to enhance treatment procedures by reducing the number of delivered magnetic stimuli to participants.

Issues of simulation, aggravation and dissimulation in expert questions for hearing disorders

Those who are working in the conditions accompanied with industrial noise exceeding normal rates and who receive irreversible decrease in hearing of sensorineural nature, proceeding from the existing legislation, have to be exposed to expert assessment of the audiologist-otorhinolaryngologist, for the purpose of examination of professional suitability. Medical experts should face such phenomena as aggravation and simulation of hearing loss which exposure and also definition of a true threshold for sound perception, nature of the available violations, is their paramount task.The tests serving for simulation identification are carried out with application of subjective audiometry, i.e. with active participation of the examined person or by means of the objective audiometry excluding participation of the patient. Observation of the patient behavior, analysis of the anamnestic data, carrying out the acumetry and tuning testing, subjective and objective audiometry and also comparison of the obtained data allows to make expert assessment of a clinical case. The objective audiometry (OET, KSVP, ECOG, acoustic impedancemetry) is crucial in case of the doubts arising after carrying out a subjective audiometric research.

Estimating Nonorganic Hearing Thresholds Using Binaural Auditory Stimuli

Purpose Minimum contralateral interference levels (MCILs) are used to estimate true hearing thresholds in individuals with unilateral nonorganic hearing loss. In this study, we determined MCILs and examined the correspondence of MCILs to true hearing thresholds to quantify the accuracy of this procedure. Method Sixteen adults with normal hearing participated. Subjects were asked to feign a unilateral hearing loss at 1.0, 2.0, and 4.0 kHz. MCILs were determined. Subjects also made lateralization judgments for simultaneously presented tones with varying interaural intensity differences. Results The 90% confidence intervals, calculated for the distributions, indicate that the MCIL in 90% of cases would be expected to be very close to threshold to approximately 17–19 dB poorer than the true hearing threshold. How close the MCIL is to true threshold appears to be based on the individual's response criterion. Conclusions Response bias influences the MCIL and how close an MCIL is to true hearing threshold. The clinician can never know a client's response bias and therefore should use a 90% confidence interval to predict the range for the expected true threshold. On the basis of this approach, a clinician may assume that true threshold is at or as much as 19 dB better than MCIL.

Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples

Within the context of threshold regressions, we show that asymptotically-valid likelihood-ratio-based confidence intervals for threshold parameters perform poorly in finite samples when the threshold effect is large. A large threshold effect leads to a poor approximation of the profile likelihood in finite samples such that the conventional approach to constructing confidence intervals excludes the true threshold parameter value too often, resulting in low coverage rates. We propose a conservative modification to the standard likelihood-ratio-based confidence interval that has coverage rates at least as high as the nominal level, while still being informative in the sense of including relatively few observations of the threshold variable. An application to thresholds for US industrial production growth at a disaggregated level shows the empirical relevance of applying the proposed approach.

Evaluation of Peaks-Over-Threshold Method

Two extreme wave analysis models, namely Peaks-Over-Threshold (POT) and Generalized Pareto Distribution (GPD), were developed in order to improve the POT model and highlight merits and limitations of the two models. Studies have shown that the POT model was not equipped with a suitable approach to determine a true threshold value. This paper proposed an approach to specify the most suitable threshold value for the POT model, which is called Hybrid method. In addition, until now the MIR (minimum ratio of residual correlation coefficient) criterion has been used as a goodness-of-fit method in the POT model. However, the examinations on the method represented that MIR is not always a stable approach in determining true distribution function. This paper proposed an alternative approach instead of the MIR criterion method, it is called Norm of Residuals, and its credibility was examined by the Chi-Square test. The results drawn from this study also demonstrated that the Hybrid method completely matched with the POT model, and the threshold obtained by this method is credible, moreover, the Norm of Residuals method is completely stable in determining the best fitting distribution for the POT model.

BOUNDARY ESTIMATION OF INSPECTION THRESHOLD FOR MULTI-COMPONENT SYSTEM

Inspection threshold is one of effective methods to reduce causes of misjudgement under imperfect inspection. Based on the Bayesian theory, the threshold is defined as the boundary between inspection and noninspection execution. However, the formulation of the true threshold is difficult under a general complex system. This paper proposes approximation methods to derive the maximum and the minimum inspection thresholds for a general system. A binary reliability theory is used for the derivation of the thresholds. Structure functions, minimal path and cut sets are used for the approximation. Finally, some numerical examples are given.