Response Time Distributions Research Articles

Equal Quality for Online and Lab Data: A Direct Comparison from Two Dual-Task Paradigms

Abstract Conducting behavioral experiments online has become more prevalent recently. Still, there is reluctance to embrace the possibilities this technology has to offer. So far, only simple tasks have been replicated in an online setting. In order to investigate whether collecting online also leads to high quality data in demanding tasks, we directly compared data collected in the lab with data collected online from a demanding dual-task paradigm and a psychological refractory period paradigm. In Experiment 1, we recruited from local pools, online and offline; in Experiment 2, we collected lab data from our local pool and online data from a remote commercial participant platform. We found that all relevant effects were replicated in the lab and online settings; effect sizes were similar. Additionally, most response time distributions were even statistically equivalent when comparing online and lab data. Thus, online effect sizes and variances can be comparable to lab-based data. Online studies are time-efficient and recruiting an online sample instead or on top of a laboratory sample should be considered for basic behavioral research. This can serve an important role in the generalizability and replicability of findings in the cognitive and behavioral sciences.

When does “inhibition of return” occur in spatial cueing tasks? Temporally disentangling multiple cue-triggered effects using response history and conditional accuracy analyses

Abstract Research on spatial cueing has shown that uninformative cues often facilitate mean response time (RT) performance in valid- compared to invalid-cueing conditions at short cue-target stimulus-onset-asynchronies (SOAs), and robustly generate a reversed or inhibitory cueing effect at longer SOAs that is widely known as inhibition-of-return (IOR). To study the within-trial time course of the IOR and facilitation effects we employ discrete-time hazard and conditional accuracy analyses to analyze the shapes of the RT and accuracy distributions measured in two experimental tasks. Our distributional analyses show that (a) IOR is present only from ~160 ms to ~280 ms after target onset for cue-target SOAs above ~200 ms, (b) facilitation does not precede IOR, but co-occurs with it, (c) the cue-triggered motor response activation is selectively and actively inhibited before target onset, (d) the IOR effect consists of a facilitatory and an inhibitory component when compared to central cueing, (e) the addition of an extra central cue causes a temporary negative cueing effect in the conditional accuracy functions, and (f) the within-trial time course of IOR is not affected much by the task employed (detection or localization). We conclude that the traditional mean performance measures conceal crucial information on behavioral dynamics in spatial cueing paradigms.

Modulating verbal working memory with fronto-parietal transcranial electric stimulation at theta frequency: Does it work?

Oscillatory theta activity in a fronto-parietal network has been associated with working memory (WM) processes and may be directly related to WM performance. In their seminal study, Polanía et al. (2012) (de-)coupled a fronto-parietal theta-network by applying transcranial alternating current stimulation (tACS), and showed that anti-phase tACS led to slower and in-phase tACS to faster response times in a verbal WM task compared to placebo stimulation. In the literature, this 'synchronization-desynchronization' effect has only been partly replicated, and electric field modelling suggests that it might not be the fronto-parietal network that is primarily stimulated during in-phase tACS with a shared return electrode. This provides one possible reason for inconsistency in the literature. In this study, we aimed to reproduce the findings reported by Polanía et al. (2012). We also aimed to investigate whether in-phase theta tACS with multiple close-by return electrodes for focal stimulation of the frontal and the parietal cortex will have at least as much of a facilitatory effect as the in-phase stimulation as indicated by Polania et al. (2012). In a single-trial distributional analysis, we explored whether mean, variation and right-skewness of the response time distribution are affected. Against our hypothesis, we found no 'synchronization-desynchronization' effect by fronto-parietal theta tACS on response times using the same delayed letter discrimination task and stimulation parameters in two experiments, both between-subjects and within-subjects. However, we could show that in a more demanding 3-back task, fronto-parietal in-phase and in-phase focal theta tACS substantially improved task performance compared to placebo stimulation.

Do Attentional Lapses Account for the Worst Performance Rule?

The worst performance rule (WPR) describes the phenomenon that individuals’ slowest responses in a task are often more predictive of their intelligence than their fastest or average responses. To explain this phenomenon, it was previously suggested that occasional lapses of attention during task completion might be associated with particularly slow reaction times. Because less intelligent individuals should experience lapses of attention more frequently, reaction time distribution should be more heavily skewed for them than for more intelligent people. Consequently, the correlation between intelligence and reaction times should increase from the lowest to the highest quantile of the response time distribution. This attentional lapses account has some intuitive appeal, but has not yet been tested empirically. Using a hierarchical modeling approach, we investigated whether the WPR pattern would disappear when including different behavioral, self-report, and neural measurements of attentional lapses as predictors. In a sample of N = 85, we found that attentional lapses accounted for the WPR, but effect sizes of single covariates were mostly small to very small. We replicated these results in a reanalysis of a much larger previously published data set. Our findings render empirical support to the attentional lapses account of the WPR.

PASSENGER RESPONSE TIME DATA-SETS FOR LARGE PASSENGER FERRIES AND CRUISE SHIPS DERIVED FROM SEA TRIALS


 
 
 This paper describes research that was carried-out under the EU FP7 research project SAFEGUARD and presents passenger response time data generated from five full-scale semi-unannounced assembly trials at sea. The data-sets were generated from three different types of passenger ships, a RO-PAX ferry without cabins (RP1), a cruise ship (CS) and a RO-PAX ferry with cabins (RP2). In total, response times from 2366 people were collected making it the largest response time data-set ever collected – on land or sea. The analysis methodology used to extract the response time data and the resultant response time distributions (RTD) is presented. A number of key findings from the data analysis are presented along with three recommendations to modify the IMO guidelines governing ship evacuation analysis, namely; (a) it is inappropriate to use the same RTD for cruise ships and RO-PAX vessels; (b) a new Day Case RTD is suggested for RO-PAX vessels and (c) new Day and Night RTDs are suggested for cruise ships.
 
 

Cortical Source Domain Based Motor Imagery and Motor Execution Framework for Enhanced Brain Computer Interface Applications

In the recent decades, there has been growing interest in novel applications of neuro-rehabilitation and motor power augmentation based on the experimental paradigm of Motor Imagery (MI) and Motor Execution (ME) respectively. Qualitative comparison between MI and ME reveals significant difference in response time, activation magnitude, and cortical source distribution. Based on these differences, different frameworks of MI and ME have been developed for enhanced Brain Computer Interface (BCI) applications by providing task specific information in time and cortical source space. Decoding of subject's intent using cortical source domain processing increases the accuracy in the MI and ME scenario by 5.18% and 3.68% respectively, compared to conventional sensor domain processing. The performance of the proposed methodology outperforms the stat-of-the-art techniques. The present study highlights the limitation of cross framework i.e., utilization of MI framework in ME experimental paradigm or vice versa. In particular, the performance degradation of MI and ME tasks was observed in the cross framework scenario. The experimental results are expected to provide an evidence for researchers when designing an imagery or execution based online (or offline) BCI system.

Unveiling the boost in the sandwich priming technique.

The masked priming technique (which compares #####-house-HOUSE vs. #####-fight-HOUSE) is the gold-standard tool to examine the initial moments of word processing. Lupker and Davis showed that adding a pre-prime identical to the target produced greater priming effects in the sandwich technique (which compares #####-HOUSE-house-HOUSE vs #####-HOUSE-fight-HOUSE). While there is consensus that the sandwich technique magnifies the size of priming effects relative to the standard procedure, the mechanisms underlying this boost are not well understood (i.e., does it reflect quantitative or qualitative changes?). To fully characterise the sandwich technique, we compared the sandwich and standard techniques by examining the response times (RTs) and their distributional features (delta plots; conditional-accuracy functions), comparing identity versus unrelated primes. The results showed that the locus of the boost in the sandwich technique was two-fold: faster responses in the identity condition (via a shift in the RT distributions) and slower responses in the unrelated condition. We discuss the theoretical and methodological implications of these findings.

Does the choice of response time threshold procedure substantially affect inferences concerning the identification and exclusion of rapid guessing responses?\xa0A meta-analysis

BackgroundIn testing contexts that are predominately concerned with power, rapid guessing (RG) has the potential to undermine the validity of inferences made from educational assessments, as such responses are unreflective of the knowledge, skills, and abilities assessed. Given this concern, practitioners/researchers have utilized a multitude of response time threshold procedures that classify RG responses in these contexts based on either the use of no empirical data (e.g., an arbitrary time limit), response time distributions, and the combination of response time and accuracy information. As there is little understanding of how these procedures compare to each other, this meta-analysis sought to investigate whether threshold typology is related to differences in descriptive, measurement property, and performance outcomes in these contexts.MethodsStudies were sampled that: (a) employed two or more response time (RT) threshold procedures to identify and exclude RG responses on the same computer-administered low-stakes power test; and (b) evaluated differences between procedures on the proportion of RG responses and responders, measurement properties, and test performance.ResultsBased on as many as 86 effect sizes, our findings indicated non-negligible differences between RT threshold procedures in the proportion of RG responses and responders. The largest differences for these outcomes were observed between procedures using no empirical data and those relying on response time and accuracy information. However, these differences were not related to variability in aggregate-level measurement properties and test performance.ConclusionsWhen filtering RG responses to improve inferences concerning item properties and group score outcomes, the actual threshold procedure chosen may be of less importance than the act of identifying such deleterious responses. However, given the conservative nature of RT thresholds that use no empirical data, practitioners may look to avoid the use of these procedures when making inferences at the individual-level, given their potential for underclassifying RG.

Qualitative speed-accuracy tradeoff effects can be explained by a diffusion/fast-guess mixture model

Rafiei and Rahnev (2021) presented an analysis of an experiment in which they manipulated speed-accuracy stress and stimulus contrast in an orientation discrimination task. They argued that the standard diffusion model could not account for the patterns of data their experiment produced. However, their experiment encouraged and produced fast guesses in the higher speed-stress conditions. These fast guesses are responses with chance accuracy and response times (RTs) less than 300 ms. We developed a simple mixture model in which fast guesses were represented by a simple normal distribution with fixed mean and standard deviation and other responses by the standard diffusion process. The model fit the whole pattern of accuracy and RTs as a function of speed/accuracy stress and stimulus contrast, including the sometimes bimodal shapes of RT distributions. In the model, speed-accuracy stress affected some model parameters while stimulus contrast affected a different one showing selective influence. Rafiei and Rahnev’s failure to fit the diffusion model was the result of driving subjects to fast guess in their experiment.

A two-stage diffusion modeling approach to the compelled-response task.

The issue of how perception and motor planning interact to generate a given choice between actions is a fundamental question in both psychology and neuroscience. Salinas and colleagues have developed a behavioral paradigm, the compelled-response task, where the signal that instructs the subject to make an eye movement is given before the cue that indicates which of two possible target choices is the correct one. When the cue is given rather late, the participant must guess and make an uninformed random choice. Perceptual performance can be tracked as a function of the amount of time during which sensory information is available. In Salinas' accelerated race-to-threshold model, two variables race against each other to a threshold, at which a saccade is initiated. The source of random variability is in the initial state of information buildup across trials. This implies that incorrect decisions are due to the inertia of the racing variables that have, at the start, sampled a constant buildup in the "wrong" direction. Here we suggest an alternative, non-time-homogeneous two-stage-diffusion model that is able to predict both response time distributions and choice probabilities with a few easy-to-interpret parameters and without assuming cross-trial parameter variability. It is falsifiable already at the level of qualitative features, for example, predicting bimodal reaction time (RT) distributions for particular gap times. It connects the compelled-response paradigm with an approach to decision making that has been uniquely successful in describing both behavioral and neural data in a variety of experimental settings for the last 40 years. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Response Time Distribution in a Tandem Pair of Queues with Batch Processing

Response time density is obtained in a tandem pair of Markovian queues with both batch arrivals and batch departures. The method uses conditional forward and reversed node sojourn times and derives the Laplace transform of the response time probability density function in the case that batch sizes are finite. The result is derived by a generating function method that takes into account that the path is not overtake-free in the sense that the tagged task being tracked is affected by later arrivals at the second queue. A novel aspect of the method is that a vector of generating functions is solved for, rather than a single scalar-valued function, which requires investigation of the singularities of a certain matrix. A recurrence formula is derived to obtain arbitrary moments of response time by differentiation of the Laplace transform at the origin, and these can be computed rapidly by iteration. Numerical results for the first four moments of response time are displayed for some sample networks that have product-form solutions for their equilibrium queue length probabilities, along with the densities themselves by numerical inversion of the Laplace transform. Corresponding approximations are also obtained for (non-product-form) pairs of “raw” batch-queues—with no special arrivals—and validated against regenerative simulation, which indicates good accuracy. The methods are appropriate for modeling bursty internet and cloud traffic and a possible role in energy-saving is considered.

Performance Analysis of Work Stealing in Large-scale Multithreaded Computing

Randomized work stealing is used in distributed systems to increase performance and improve resource utilization. In this article, we consider randomized work stealing in a large system of homogeneous processors where parent jobs spawn child jobs that can feasibly be executed in parallel with the parent job. We analyse the performance of two work stealing strategies: one where only child jobs can be transferred across servers and the other where parent jobs are transferred. We define a mean-field model to derive the response time distribution in a large-scale system with Poisson arrivals and exponential parent and child job durations. We prove that the model has a unique fixed point that corresponds to the steady state of a structured Markov chain, allowing us to use matrix analytic methods to compute the unique fixed point. The accuracy of the mean-field model is validated using simulation. Using numerical examples, we illustrate the effect of different probe rates, load, and different child job size distributions on performance with respect to the two stealing strategies, individually, and compared to each other.

Comparison of Different Response Time Outlier Exclusion Methods: A Simulation Study.

In response time (RT) research, RT outliers are typically excluded from statistical analysis to improve the signal-to-noise ratio. Nevertheless, there exist several methods for outlier exclusion. This poses the question, how these methods differ with respect to recovering the uncontaminated RT distribution. In the present simulation study, two RT distributions with a given population difference were simulated in each iteration. RTs were replaced by outliers following two different approaches. The first approach generated outliers at the tails of the distribution, the second one inserted outliers overlapping with the genuine RT distribution. We applied ten different outlier exclusion methods and tested, how many pairs of distributions significantly differed. Outlier exclusion methods were compared in terms of bias. Bias was defined as the deviation of the proportion of significant differences after outlier exclusion from the proportion of significant differences in the uncontaminated samples (before introducing outliers). Our results showed large differences in bias between the exclusion methods. Some methods showed a high rate of Type-I errors and should therefore clearly not be used. Overall, our results showed that applying an exclusion method based on z-scores / standard deviations introduced only small biases, while the absence of outlier exclusion showed the largest absolute bias.

Numerical study on the deadline-concerning priority queuing model

The Barab\'asi's priority queuing model [A.-L. Barab\'asi, Nature \textbf{435}, 207 (2005)] and its variants have been extensively studied to understand heavy-tailed distributions of the inter-event times and the response times observed in various empirical analyses of human dynamics. In this paper, we focus on the effects of deadlines assigned to the tasks in a queue of fixed size on the response-time distributions. Here, the response time is defined as the time interval between the arrival and the execution of the task. We propose a deadline-concerning priority queuing model, in which as the deadline approaches, the priority is adjusted using the inverse of the remaining time to the deadline. By performing the numerical simulations, we find that the power-law exponent characterizing the response-time distributions is less than $1$ under the deterministic selection protocol while it has the value of $1$ under the nondeterministic selection protocol.

On the Application of Mean Value Analysis Without the Normalization Constant in the Closed Queuing Networks

An example of closed queue network could be view when patients arrive at a doctor’s office to update their medical records, then it’s off to the nurse’s station for various measurements like weight, blood pressure, and so on. The next stop is generally to queue (i.e., wait patiently) for one of the doctors to arrive and begin the consultation and examination. Perhaps it may be necessary to have some X-rays taken, an ultrasound may be called for, and so on. After these procedures have been completed, it may be necessary to talk with the doctor once again. The final center through which the patient must pass is always the billing office. In this work, multiple-node” system in which a customer requires service at more than one node, which may be viewed as a network of nodes, and each node is a service center having storage room for queues to form and perhaps with multiple servers to handle customer requests is investigated in order to provide some insight into the performance measure analysis. Our quest is to exempt the normalization constant in the computation of performance measure in the closed queueing network. The arrival properties and Little’s law are use with the help of some existing equations and formulas in queueing network. Performance measures, such as Mean number of customers, response time, throughput, and marginal probability distribution are obtained for central server and load dependent server closed queuing networks for nodes 4 and 5, and also for k = 3 and k = 10.

Time Will Tell: Recovering Preferences When Choices Are Noisy

When choice is stochastic, revealed preference analysis often relies on random utility models. However, it is impossible to infer preferences without assumptions on the distribution of utility noise. We show that this difficulty can be overcome by using response time data. A simple condition on response time distributions ensures that choices reveal preferences without distributional assumptions. Standard models from economics and psychology generate data fulfilling this condition. Sharper results are obtained under symmetric or Fechnerian noise, where response times allow uncovering preferences or predicting choice probabilities out of sample. Application of our tools is simple and generates remarkable prediction accuracy.

Location-response binding and inhibition of return in a detection task

In the present study, we investigated the binding of location and response in a detection task of the target-target paradigm of inhibition of return (IOR). Results showed a cost of responding to a target at the repeated location (IOR) when the response was not repeated and an effect of facilitation of return (FOR) when the response was repeated. These findings suggest that when responding to a target, its location and the response to it are integrated together. In addition, an analysis of the Vincentized cumulative response time (RT) distribution further showed that memory retrieval of event representations requires time to operate. These findings were discussed according to the theoretical framework of event files.

Binding Costs in Processing Efficiency as Determinants of Cognitive Ability.

Performance in elementary cognitive tasks is moderately correlated with fluid intelligence and working memory capacity. These correlations are higher for more complex tasks, presumably due to increased demands on working memory capacity. In accordance with the binding hypothesis, which states that working memory capacity reflects the limit of a person’s ability to establish and maintain temporary bindings (e.g., relations between items or relations between items and their context), we manipulated binding requirements (i.e., 2, 4, and 6 relations) in three choice reaction time paradigms (i.e., two comparison tasks, two change detection tasks, and two substitution tasks) measuring mental speed. Response time distributions of 115 participants were analyzed with the diffusion model. Higher binding requirements resulted in generally reduced efficiency of information processing, as indicated by lower drift rates. Additionally, we fitted bi-factor confirmatory factor analysis to the elementary cognitive tasks to separate basal speed and binding requirements of the employed tasks to quantify their specific contributions to working memory capacity, as measured by Recall−1-Back tasks. A latent factor capturing individual differences in binding was incrementally predictive of working memory capacity, over and above a general factor capturing speed. These results indicate that the relation between reaction time tasks and working memory capacity hinges on the complexity of the reaction time tasks. We conclude that binding requirements and, therefore, demands on working memory capacity offer a satisfactory account of task complexity that accounts for a large portion of individual differences in ability.

Fault-Detection Managers: More May Not Be the Merrier.

A fault management system contains managers that detect faults as well as initiate recovery actions. Such management systems often come in an architecture that is not only a distributed one but also decoupled from the applications. Although an arrangement like this promotes scalability, it unfortunately makes the recovery of applications dependent on the fault management system itself. This work introduces two novel equations to meet the performance objectives of applications. To this end, we first create an equation that estimates the maximum number of jobs to be handled by an application instance for meeting a given performance objective. This formula is then used by admission control mechanism to restrict the number of jobs (targeted for operational application instances) to be allowed to enter the system. Next, we create a second equation that computes the response time distribution of an application. Thereafter, we develop a simulation model that predicts the impact of the failure of four sample fault management architectures on application’s performance. Exploiting our equations, we compare the architectures in terms of three distinct ways of handling affected jobs when application instances fail—allow job loss; retry jobs resulting in overload; employ admission control to mitigate the overload. Our simulation results show that boosting the number of managers may not always be beneficial; rather, it could possibly be the interconnection topology (i.e. the layout of interconnects linking the architectural components) of the management architecture, together with the model parameter values that may sometimes have a bigger role to play in the application’s performance.

Beyond Looking for the Rewarded Target: The Effects of Reward on Attention in Search Tasks.

One puzzling result in training-test paradigms is that effects of reward-associated stimuli on attention are often seen in test but not in training. We focus on one study, where reward-related performance benefits occur in the training and which was discussed contentiously. By using a similar design, we conceptually replicated the results. Moreover, we investigated the underlying mechanisms and processes resulting in these reward-related performance benefits. In two experiments, using search tasks and having participants perform the tasks either with or without individually adjusted time pressure, we disentangled the mechanisms and processes contributing to the reward-related benefits. We found evidence that not only search efficiency is increased with increasing reward, but also that non-search factors contribute to the results. By also investigating response time distributions, we were able to show that reward-related performance effects increased as search time increased in demanding tasks but not in less demanding tasks. Theoretical implications of the results regarding how reward influences attentional processing are discussed.