RT Distributions Research Articles

Sleep deprivation affects interference control: A diffusion model analysis.

Previous studies suggest that interference control may be unaffected by sleep deprivation based on the unchanged interference effects (reaction time [RT] differences between incongruent and congruent conditions), while ignoring the overall slower RTs after sleep deprivation. In the present study, we interpreted these results from a new angle using a variant of diffusion model, diffusion model for conflict tasks (DMC), and investigated whether and how interference control is affected by sleep deprivation. Mathematical derivations and model simulations showed that unchanged task-irrelevant information processing (i.e., unaffected interference control) may not lead to the observed unchanged interference effects when considering the overall slower RTs after sleep deprivation (due to either decreased drift rate of task-relevant information or increased decision boundary). Therefore, the unchanged interference effects do not necessarily indicate unchanged interference control. We then conducted a Simon task following one night of sleep deprivation or normal sleep, and fitted the DMC to the data. Experimental results showed that the Simon effect was reversed when most of the trials were incongruent, indicating that participants used learned spatially incompatible stimulus-response associations to predict responses. However, the Simon effects in both mean RTs and RT distributions were not significantly modulated by sleep deprivation. Model fits showed that the drift rate of task-relevant information decreased and the time-to-peak of task-irrelevant activation increased after sleep deprivation. These results suggest that central information processing was degraded after sleep loss, and most importantly, task-irrelevant activation increased after sleep deprivation as interference control was impaired. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Charged-particle production as a function of the relative transverse activity classifier in pp, p–Pb, and Pb–Pb collisions at the LHC

Measurements of charged-particle production in pp, p–Pb, and Pb–Pb collisions in the toward, away, and transverse regions with the ALICE detector are discussed. These regions are defined event-by-event relative to the azimuthal direction of the charged trigger particle, which is the reconstructed particle with the largest transverse momentum pTtrig\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\left({p}_{\ extrm{T}}^{\ extrm{trig}}\\right) $$\\end{document} in the range 8 <pTtrig\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {p}_{\ extrm{T}}^{\ extrm{trig}} $$\\end{document}< 15 GeV/c. The toward and away regions contain the primary and recoil jets, respectively; both regions are accompanied by the underlying event (UE). In contrast, the transverse region perpendicular to the direction of the trigger particle is dominated by the so-called UE dynamics, and includes also contributions from initial- and final-state radiation. The relative transverse activity classifier, RT=NchT/NchT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {R}_{\ extrm{T}}={N}_{\ extrm{ch}}^{\ extrm{T}}/\\left\\langle {N}_{\ extrm{ch}}^{\ extrm{T}}\\right\\rangle $$\\end{document}, is used to group events according to their UE activity, where NchT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {N}_{\ extrm{ch}}^{\ extrm{T}} $$\\end{document} is the charged-particle multiplicity per event in the transverse region and NchT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\left\\langle {N}_{\ extrm{ch}}^{\ extrm{T}}\\right\\rangle $$\\end{document} is the mean value over the whole analysed sample. The energy dependence of the RT distributions in pp collisions at s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{s} $$\\end{document} = 2.76, 5.02, 7, and 13 TeV is reported, exploring the Koba-Nielsen-Olesen (KNO) scaling properties of the multiplicity distributions. The first measurements of charged-particle pT spectra as a function of RT in the three azimuthal regions in pp, p–Pb, and Pb–Pb collisions at sNN\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{s_{\ extrm{NN}}} $$\\end{document} = 5.02 TeV are also reported. Data are compared with predictions obtained from the event generators PYTHIA 8 and EPOS LHC. This set of measurements is expected to contribute to the understanding of the origin of collective-like effects in small collision systems (pp and p–Pb).

Drift diffusion models of perceptual learning indicate long-term improvements in sensitivity and short-term fluctuations in caution.

Evidence-accumulation models have enabled strong theoretical advances in our understanding of decision-making. Yet most of these models assume stationary performance; when concerned with performance improvements, dynamic versions of these models are critical to inform the mechanisms of learning. This is particularly true because most domains of learning, from low-level perception to more complex skills, involve changes in both choices (e.g., accuracy) and the speed at which those choices can be made (i.e., response time). Evidence-accumulation models provide frameworks for understanding these joint changes. Using data from participants completing a dynamic random dot-motion direction discrimination task over 4 daily sessions for a total of 2800 trials, we characterized alterations in both perceptual sensitivity [drift rate] and response caution [boundary separation] across multiple possible timescales. Nonlinear mixed-effect Bayesian Wiener diffusion models were applied to estimate individuals’ trajectories of performance change in joint RT and accuracy distributions, with different models allowing for various dynamics. For example, the models could be stable across the entirety of the training, changing as a continuous function of trial number, or changing continuously within sessions, but varying across sessions. Model comparisons then used estimates of Bayes Factors as well as approximations to leave-one-out cross-validation. The best-fitting model of perceptual improvements included sensitivity changing as a continuous, exponential function of trial number (i.e., 1 through 2800), but response caution changing continuously within each daily session and in an independent manner across sessions. Such results uncover two different processes producing the full pattern of behavior across the entire trajectory of experience, one involving a continuous tuning of perceptual sensitivity, and another more idiosyncratic process describing how participants convert perceptual evidence into behavioral decisions. Theories of perceptual learning involving multiple timescales of change are thus supported, with distinct processes and outcomes associated with each time scale.

Scanning a compressed ordered representation of the future.

Several authors have suggested a deep symmetry between the psychological processes that underlie our ability to remember the past and make predictions about the future. The judgment of recency (JOR) task measures temporal order judgments for the past by presenting pairs of probe stimuli; participants choose the probe that was presented more recently. We performed a short-term relative JOR task and introduced a novel judgment of imminence (JOI) task to study temporal order judgments for the future. In the JOR task, participants were presented with a sequence of stimuli and asked to choose which of two probe stimuli was presented closer to the present. In the JOI task, participants were trained on a probabilistic sequence. After training, the sequence was interrupted with probe stimuli. Participants were asked to choose which of two probe stimuli was expected to be presented closer to the present. Replicating prior work on JOR, we found that RT results supported a backward self-terminating search model operating on a temporally organized representation of the past. We also showed that RT distributions are consistent with this model and that the temporally organized representation is compressed. Critically, results for the JOI task probing expectations of the future suggest a forward self-terminating search model operating on a temporally organized representation of the future. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Beyond Drift Diffusion Models: Fitting a Broad Class of Decision and Reinforcement Learning Models with HDDM.

Computational modeling has become a central aspect of research in the cognitive neurosciences. As the field matures, it is increasingly important to move beyond standard models to quantitatively assess models with richer dynamics that may better reflect underlying cognitive and neural processes. For example, sequential sampling models (SSMs) are a general class of models of decision-making intended to capture processes jointly giving rise to RT distributions and choice data in n-alternative choice paradigms. A number of model variations are of theoretical interest, but empirical data analysis has historically been tied to a small subset for which likelihood functions are analytically tractable. Advances in methods designed for likelihood-free inference have recently made it computationally feasible to consider a much larger spectrum of SSMs. In addition, recent work has motivated the combination of SSMs with reinforcement learning models, which had historically been considered in separate literatures. Here, we provide a significant addition to the widely used HDDM Python toolbox and include a tutorial for how users can easily fit and assess a (user-extensible) wide variety of SSMs and how they can be combined with reinforcement learning models. The extension comes batteries included, including model visualization tools, posterior predictive checks, and ability to link trial-wise neural signals with model parameters via hierarchical Bayesian regression.

When two faces are not better than one: Serial limited-capacity processing with redundant-target faces.

Many researchers believe that faces-whether presented alone or as part of an ensemble-are processed automatically. According to this idea, (a) the detection of single or multiple faces is resource free and does not require allocation of attention, and (b) visual search for faces is held in parallel. The current study put these hypotheses under direct scrutiny. Participants performed in a redundant target-detection task, responding according to the presence or absence of a face (or faces) on the display. I used a rigorous methodology known as the system factorial technology (SFT). The SFT methodology afforded simultaneous assessment of (a) architecture (serial vs. parallel), (b) stopping rule (exhaustive vs. self-terminating), and (c) capacity (limited, unlimited, or supercapacity). SFT analyses were held at the level of the mean RTs and at the level of the RT distributions. The analyses pointed conclusively to a serial self-terminating architecture with limited capacity. These findings cast serious doubts on the alleged automaticity of faceperception.

Visual search under physical effort is faster but more vulnerable to distractor interference

Cognition and action are often intertwined in everyday life. It is thus pivotal to understand how cognitive processes operate with concurrent actions. The present study aims to assess how simple physical effort operationalized as isometric muscle contractions affects visual attention and inhibitory control. In a dual-task paradigm, participants performed a singleton search task and a handgrip task concurrently. In the search task, the target was a shape singleton among distractors with a homogeneous but different shape. A salient-but-irrelevant distractor with a unique color (i.e., color singleton) appeared on half of the trials (Singleton distractor present condition), and its presence often captures spatial attention. Critically, the visual search task was performed by the participants with concurrent hand grip exertion, at 5% or 40% of their maximum strength (low vs. high physical load), on a hand dynamometer. We found that visual search under physical effort is faster, but more vulnerable to distractor interference, potentially due to arousal and reduced inhibitory control, respectively. The two effects further manifest in different aspects of RT distributions that can be captured by different components of the ex-Gaussian model using hierarchical Bayesian method. Together, these results provide behavioral evidence and a novel model for two dissociable cognitive mechanisms underlying the effects of simple muscle exertion on the ongoing visual search process on a moment-by-moment basis.

How do recall requirements affect decision-making in free recall initiation? A linear ballistic accumulator approach.

Models of free recall describe free recall initiation as a decision-making process in which items compete to be retrieved. Recently, Osth and Farrell (Psychological Review, 126, 578–609, 2019) applied evidence accumulation models to complete RT distributions and serial positions of participants’ first recalls in free recall, which resulted in some novel conclusions about primacy and recency effects. Specifically, the results of the modeling favored an account in which primacy was due to reinstatement of the start-of-the-list, and recency was found to be exponential in shape. In this work, we examine what happens when participants are given alternative recall instructions. Prior work has demonstrated weaker primacy and greater recency when fewer items are required to report (Ward & Tan, Memory & Cognition, 2019), and a key question is whether this change in instructions qualitatively changes the nature of the recall process, or merely changes the parameters of the recall competition. We conducted an experiment where participants studied six- or 12-item lists and were post-cued as to whether to retrieve a single item, or as many items as possible. Subsequently, we applied LBA models with various assumptions about primacy and recency, implemented using hierarchical Bayesian techniques. While greater recency was observed when only one item was required for output, the model selection did not suggest that there were qualitative differences between the two conditions. Specifically, start-of-list reinstatement and exponential recency functions were favored in both conditions.Supplementary InformationThe online version contains supplementary material available at (10.3758/s13421-020-01117-2).

Non-stationary Salience Processing During Perceptual Training in Humans

Performance in sensory tasks improves with practice. Some theories suggest that the generalization of learning depends on task difficulty. In consequence, most studies have focused on measuring learning specificity, and perceptual impact after training completes. However, how exactly sustained changes in task difficulty influence the learning curves and how this affects the efficiency of perceptual discrimination is not well understood. Here, we adapted a visual task for humans by creating monocular training programs with increasing (SIMinc) and decreasing (SIMdec) stimulus similarities. We found a marked improvement in all participants after 10 days of training, with an almost complete transfer of learning to the untrained eyes. Interestingly, the training paradigms led to drastically different learning curves for the SIMinc and SIMdec groups. The learning curves were best predicted by an associative learning model that allowed stimuli to gain or lose salience depending on how the subject’s learned about them. On addition, a non-stationary sequential sampling model that jointly accounts for choice and RT distributions revealed that the SIMinc group led to faster evidence accumulation rate relative to the SIMdec group. Altogether, our results illustrate how different learning trajectories influenced attentional salience processing leading to distinctive stimulus processing efficiencies. This crucial interdependence determines how observers learn to guide their attention towards visual stimuli in search for a decision.

Accounting for the build-up of proactive interference across lists in a list length paradigm reveals a dominance of item-noise in recognition memory

Abstract There has been a longstanding debate concerning whether interference in recognition memory is attributable to other items on the study list (i.e., item-noise) or to prior memories (i.e., context-noise and background-noise). Recently, Osth and Dennis (2015) devised a global matching model that could estimate the magnitude of each interference contribution and they found that context-noise and background-noise were dominant in recognition. In the present investigation, data from a list length experiment were analysed using variants of the Osth, Jansson, Dennis, and Heathcote (2018) model, that integrates the memory retrieval components of the Osth and Dennis (2015) model with the diffusion decision model (Ratcliff, 1978) to jointly account for choice probabilities and RT distributions. The standard version of the model, like existing recognition models, treated each condition as if no proactive interference had accumulated over the session. A more comprehensive version of the model allowed both study and test items from prior conditions to contribute proactive interference (PI) to future conditions. While the standard model estimated a dominance of background-noise, the PI model estimated a dominance of item-noise, reversing the conclusions made by Osth and Dennis (2015). Along with list length, the experimental design provided a measure of the test position effect (TPE). While the standard model attributed the TPE to context drift, the PI model attributed the TPE to both context drift and increases in item-noise.

Using response time distributions and race models to characterize primacy and recency effects in free recall initiation.

Primacy and recency effects are common benchmarks for models of free recall and episodic memory. In this work, we show that RT distributions carry diagnostic information about how items enter into competition for recall, and how that competition impacts on the dynamics of recall and leads to novel conclusions about the forms of primacy and recency effects. We jointly fit RT distributions and serial position functions for free recall initiation with both a racing diffusion model and the linear ballistic accumulator (LBA: Brown & Heathcote, 2008). The models were fit in a hierarchical Bayesian framework, factorially varying different assumptions of how primacy and recency are generated. Recency functions were either exponential or power law in shape. Primacy was treated either as a strength boost to the early list items so that both primacy and recency items jointly compete to be retrieved; a mixture of primacy and recency gradients reflecting the usage of different retrieval cues; or a primacy-as-recency account in which primacy items are functionally recent due to the contribution of rehearsal. Although serial position curves do not distinguish between these accounts, they make distinct predictions about how RT distributions vary across serial positions. Results from a number of data sets strongly favor an exponential recency function along with a mixture model of primacy and recency gradients. These results suggest that complete RT distributions can provide informative constraints on models of free recall. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Cognitive Modeling Suggests That Attentional Failures Drive Longer Stop-Signal Reaction Time Estimates in Attention Deficit/Hyperactivity Disorder.

Mean stop-signal reaction time (SSRT) is frequently employed as a measure of response inhibition in cognitive neuroscience research on ADHD. However, this measurement model is limited by two factors which may bias SSRT estimation in this population: 1) excessive skew in "go" RT distributions, and 2) trigger failures, or instances in which individuals fail to trigger an inhibition process in response to the "stop" signal. We use a Bayesian parametric approach, which allows unbiased estimation of the shape of entire SSRT distributions and the probability of trigger failures, to clarify mechanisms of stop-signal task deficits in ADHD. Children with ADHD displayed greater positive skew than their peers in both "go" RT and SSRT distributions. However, they also displayed more frequent trigger failures, which appeared to drive ADHD-related stopping difficulties. Results suggest that stop-signal task performance in ADHD reflects impairments in early attentional processes, rather than inefficiency in the stop process.

Developmental Shifts in Detection and Attention for Auditory, Visual, and Audiovisual Speech.

Successful speech processing depends on our ability to detect and integrate multisensory cues, yet there is minimal research on multisensory speech detection and integration by children. To address this need, we studied the development of speech detection for auditory (A), visual (V), and audiovisual (AV) input. Participants were 115 typically developing children clustered into age groups between 4 and 14 years. Speech detection (quantified by response times [RTs]) was determined for 1 stimulus, /buh/, presented in A, V, and AV modes (articulating vs. static facial conditions). Performance was analyzed not only in terms of traditional mean RTs but also in terms of the faster versus slower RTs (defined by the 1st vs. 3rd quartiles of RT distributions). These time regions were conceptualized respectively as reflecting optimal detection with efficient focused attention versus less optimal detection with inefficient focused attention due to attentional lapses. Mean RTs indicated better detection (a) of multisensory AV speech than A speech only in 4- to 5-year-olds and (b) of A and AV inputs than V input in all age groups. The faster RTs revealed that AV input did not improve detection in any group. The slower RTs indicated that (a) the processing of silent V input was significantly faster for the articulating than static face and (b) AV speech or facial input significantly minimized attentional lapses in all groups except 6- to 7-year-olds (a peaked U-shaped curve). Apparently, the AV benefit observed for mean performance in 4- to 5-year-olds arose from effects of attention. The faster RTs indicated that AV input did not enhance detection in any group, but the slower RTs indicated that AV speech and dynamic V speech (mouthing) significantly minimized attentional lapses and thus did influence performance. Overall, A and AV inputs were detected consistently faster than V input; this result endorsed stimulus-bound auditory processing by these children.

Is the head-fake effect in basketball robust against practice? Analyses of trial-by-trial adaptations, frequency distributions, and mixture effects to evaluate effects of practice.

Reactions to the pass of a basketball player performing a head fake are typically slower than reactions to a basketball player who passes without a head fake (i.e., head-fake effect). The present study shows that extensive practice reduces the head-fake effect in basketball. Additional analyses were conducted to explore the mechanism behind the reduced head-fake effect. First, we analyzed whether or not participants developed some control over the processing of irrelevant gaze direction, as indicated by specific trial-to-trial adaptations (i.e., congruency sequence effect). Second, we fitted the individual frequency distributions of RTs to ex-Gaussian distributions, to evaluate if practice specifically affects the Gaussian part of the distribution or the exponential part of the distribution. Third, we modeled individual RT distributions as the so-called mixture effects to examine whether the way irrelevant gaze direction impacts performance (either occasionally but massively or continuously but moderately) changes with practice. The analyses revealed that the effect of practice could not be explained with an increasing congruency-sequence effect. Also, it could not be found in the ex-Gaussian distributional analyses. The assumption that residual failure to inhibit the processing of the gaze direction in contrast to continuous failures to do so might favor mixed effects over uniform effects at later courses of practice could not be validated. The reduced head-fake effect thus is argued to source in participants' general increasing ability to inhibit the processing of the task-irrelevant gaze direction information and/or in a priority shift of gaze processing to a processing of the pass direction.

Modeling 2-alternative forced-choice tasks: Accounting for both magnitude and difference effects

We present a model-based analysis of two-alternative forced-choice tasks in which two stimuli are presented side by side and subjects must make a comparative judgment (e.g., which stimulus is brighter). Stimuli can vary on two dimensions, the difference in strength of the two stimuli and the magnitude of each stimulus. Differences between the two stimuli produce typical RT and accuracy effects (i.e., subjects respond more quickly and more accurately when there is a larger difference between the two). However, the overall magnitude of the pair of stimuli also affects RT and accuracy. In the more common two-choice task, a single stimulus is presented and the stimulus varies on only one dimension. In this two-stimulus task, if the standard diffusion decision model is fit to the data with only drift rate (evidence accumulation rate) differing among conditions, the model cannot fit the data. However, if either of one of two variability parameters is allowed to change with stimulus magnitude, the model can fit the data. This results in two models that are extremely constrained with about one tenth of the number of parameters than there are data points while at the same time the models account for accuracy and correct and error RT distributions. While both of these versions of the diffusion model can account for the observed data, the model that allows across-trial variability in drift to vary might be preferred for theoretical reasons. The diffusion model fits are compared to the leaky competing accumulator model which did not perform as well.

Aging and confidence judgments in item recognition.

We examined the effects of aging on performance in an item-recognition experiment with confidence judgments. A model for confidence judgments and response time (RTs; Ratcliff & Starns, 2013) was used to fit a large amount of data from a new sample of older adults and a previously reported sample of younger adults. This model of confidence judgments allows us to distinguish between changes evidence from memory and changes in decision-related components and it accounts for both RT distributions and response proportions. Older adults took longer to respond than younger adults, older adults exhibited a small decrease in the strength of evidence from memory compared with younger adults and a slight bias toward judging items as "old." The difference in RTs between the 2 age groups was primarily explained by the difference in the nondecision component. Although our small sample size makes the general conclusions about aging tentative, the results are consistent with other research examining the effects of aging in two-choice RT tasks and response-signal tasks, and the study demonstrates that confidence judgment choice proportion and RT distribution data from older adults can be fit with the response time and confidence 2 (RTCON2) model. (PsycINFO Database Record

A Single-Boundary Accumulator Model of Response Times in an Addition Verification Task.

Current theories of mathematical cognition offer competing accounts of the interplay between encoding and calculation in mental arithmetic. Additive models propose that manipulations of problem format do not interact with the cognitive processes used in calculation. Alternatively, interactive models suppose that format manipulations have a direct effect on calculation processes. In the present study, we tested these competing models by fitting participants' RT distributions in an arithmetic verification task with a single-boundary accumulator model (the shifted Wald distribution). We found that in addition to providing a more complete description of RT distributions, the accumulator model afforded a potentially more sensitive test of format effects. Specifically, we found that format affected drift rate, which implies that problem format has a direct impact on calculation processes. These data give further support for an interactive model of mental arithmetic.

A diffusion model approach to analyzing bilingual older adults’ performance on the Flanker task: The role of left DLPFC

A diffusion model approach to analyzing bilingual older adults’ performance on the Flanker task: The role of left DLPFC

Sustained Attention Ability Affects Simple Picture Naming

Sustained attention has previously been shown as a requirement for language production. However, this is mostly evident for difficult conditions, such as a dual-task situation. The current study provides corroborating evidence that this relationship holds even for simple picture naming. Sustained attention ability, indexed both by participants’ reaction times and individuals’ hit rate (the proportion of correctly detected targets) on a digit discrimination task, correlated with picture naming latencies. Individuals with poor sustained attention were consistently slower and their RT distributions were more positively skewed when naming pictures compared to individuals with better sustained attention. Additionally, the need to sustain attention was manipulated by changing the speed of stimulus presentation. Research has suggested that fast event rates tax sustained attention resources to a larger degree than slow event rates. However, in this study the fast event rate did not result in increased difficulty, neither for the picture naming task nor for the sustained attention task. Instead, the results point to a speed-accuracy trade-off in the sustained attention task (lower accuracy but faster responses in the fast than in the slow event rate), and to a benefit for faster rates in the picture naming task (shorter naming latencies with no difference in accuracy). Performance on both tasks was largely comparable, supporting previous findings that sustained attention is called upon during language production.

The Effect of Corrective Feedback on Performance in Basic Cognitive Tasks: An Analysis of RT Components.

The current work examines the effect of trial-by-trial feedback about correct and error responding on performance in two basic cognitive tasks: a classic Stroop task (n = 40) and a color-word matching task (n = 30). Standard measures of both RT and accuracy were examined in addition to measures obtained from fitting the ex-Gaussian distributional model to the correct RTs. For both tasks, RTs were faster in blocks of trials with feedback than in blocks without feedback, but this difference was not significant. On the other hand, with respect to the distributional analyses, providing feedback served to significantly reduce the size of the tails of the RT distributions. Such results suggest that, for conditions in which accuracy is fairly high, the effect of corrective feedback might either be to reduce the tendency to double-check before responding or to decrease the amount of attentional lapsing.