How to fit a response time distribution

Incremental structure building in the processing of ellipsis

This article presents the results of two experiments conducted to examine how ellipsis sites are processed during the processing of backward sluicing, which is superficially similar to non-sluicing wh-filler-gap dependencies. Previous studies on long-distance wh-filler-gap dependencies established that the processing of these dependencies is sensitive to the syntactic structure of materials within the dependency: CP vs. NP. Results from two maze experiments show that backward sluicing processing is sensitive to the same structural factors, confirming that the same processing mechanism underlies both constructions. We suggest that an active search mechanism is operating at the core for these structures and with the interaction of the ellipsis-specific mechanism, e.g., a word-by-word copying mechanism, the parser builds antecedent structure within the ellipsis site incrementally during the processing of backward sluicing.

Differential Functional Changes in Visual Performance during Acute Exposure to Microgravity Analogue and Their Potential Links with Spaceflight-Associated Neuro-Ocular Syndrome

BACKGROUND

Spaceflight-Associated Neuro-Ocular Syndrome (SANS) is a complex pathology threatening the health of astronauts, with incompletely understood causes and no current specific functional diagnostic or screening test. We investigated the use of the differential performance of the visual system (central vs. perimacular visual function) as a candidate marker of SANS-related pathology in a ground-based microgravity analogue.

METHODS

We used a simple reaction time (SRT) task to visual stimuli, presented in the central and perimacular field of view, as a measure of the overall performance of the visual function, during acute settings (first 10 min) of vertical, bed rest (BR), -6°, and -15° head-down tilt (HDT) presentations in healthy participants (n = 8). We built dose-response models linking the gravitational component to SRT distribution parameters in the central vs. perimacular areas.

RESULTS

Acute exposure to microgravity induces detectable changes between SRT distributions in the perimacular vs. central retina (increased mean, standard deviation, and tau component of the ex-Gaussian function) in HDT compared with vertical presentation.

CONCLUSIONS

Functional testing of the perimacular retina might be beneficial for the earlier detection of SANS-related ailments in addition to regular testing of the central vision. Future diagnostic tests should consider the investigation of the extra-macular areas, particularly towards the optic disc.

An extension of the shifted Wald model of human response times: Capturing the time dynamic properties of human cognition : Trial-varying Wald model

Despite the ubiquitous nature of evidence accumulation models in cognitive and experimental psychology, there has been a comparatively limited uptake of such techniques in the applied literature. While quantifying latent cognitive processing properties has significant potential for applied domains such as adaptive work systems, accumulator models often fall short in practical applications. Two primary reasons for these shortcomings are the complexities and time needed for the application of cognitive models, and the failure of current models to capture systematic trial-to-trial variability in parameters. In this manuscript, we develop a novel, trial-varying extension of the shifted Wald model to address these concerns. By leveraging conjugate properties of the Wald distribution, we derive computationally efficient solutions for threshold and drift parameters which can be updated instantaneously with new data. The resulting model allows the quantification of systematic variation in latent cognitive parameters across trials and we demonstrate the utility of such analyses through simulations and an exemplar application to an existing data set. The analytic nature of our solutions opens the door for real-world applications, significantly extending the reach of computational models of behavioral responses.

Benefits of multinomial processing tree models with discrete and continuous variables in memory research: an alternative modeling proposal to Juola et al. (2019)

Signal detection theory (SDT) and two-high threshold models (2HT) are often used to analyze accuracy data in recognition memory paradigms. However, when reaction times (RTs) and/or confidence levels (CLs) are also measured, they usually are analyzed separately or not at all as dependent variables (DVs). We propose a new approach to include these variables based on multinomial processing tree models for discrete and continuous variables (MPT-DC) with the aim to compare fits of SDT and 2HT models. Using Juola et al.'s (2019, Memory & Cognition, 47[4], 855-876) data we have found that including CLs and RTs reduces the standard errors of parameter estimates and accounts for interactions among accuracy, CLs, and RTs that classical versions of SDT and 2HT models do not. In addition, according to the simulations, there is an increase in the proportion of correct model selections when relevant DV are included. We highlight the methodological and substantive advantages of MPT-DC in the disentanglement of contributing processes in recognition memory.

We don't know what you did last summer. On the importance of transparent reporting of reaction time data pre-processing

In behavioral, cognitive, and social sciences, reaction time measures are an important source of information. However, analyses on reaction time data are affected by researchers' analytical choices and the order in which these choices are applied. The results of a systematic literature review, presented in this paper, revealed that the justification for and order in which analytical choices are conducted are rarely reported, leading to difficulty in reproducing results and interpreting mixed findings. To address this methodological shortcoming, we created a checklist on reporting reaction time pre-processing to make these decisions more explicit, improve transparency, and thus, promote best practices within the field. The importance of the pre-processing checklist was additionally supported by an expert consensus survey and a multiverse analysis. Consequently, we appeal for maximal transparency on all methods applied and offer a checklist to improve replicability and reproducibility of studies that use reaction time measures.

Differences in Ex-Gaussian Parameters from Response Time Distributions Between Individuals with and Without Attention Deficit/Hyperactivity Disorder: A Meta-analysis

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent neurodevelopmental disorders in childhood and adolescence. Differences in reaction times (RT) in cognitive tasks have been consistently observed between ADHD and typical participants. Instead of estimating means and standard deviations, fitting non-symmetrical distributions like the ex-Gaussian, characterized by three parameters (µ, σ, and τ), account for the whole RT distributions. A meta-analysis is performed with all the available literature using ex-Gaussian distributions for comparisons between individuals with ADHD and controls. Results show that τ and σ are generally greater for ADHD samples, while µ tends to be larger for typical groups but only for younger ages. Differences in τ are also moderated by ADHD subtypes. τ and σ show, respectively, quadratic and linear relationships with inter-stimulus intervals from Continuous Performance Test and Go/No Go tasks. Furthermore, tasks and cognitive domains influence the three parameters. Interpretations of ex-Gaussian parameters and clinical implications of these findings are also discussed. Fitting ex-Gaussian distributions to RT data is a useful way to explore differences between individuals with ADHD and healthy controls.

Combining reaction-time distributions to conserve shape

To improve the estimate of the shape of a reaction-time distribution, it is sometimes desirable to combine several samples, drawn from different sessions or different subjects. How should these samples be combined? This paper provides an evaluation of four combination methods, two that are currently in use (the bin-means histogram, often called "Vincentizing", and quantile averaging) and two that are new (linear-transform pooling and shape averaging). The evaluation makes use of a modern method for describing the shape of a distribution, based on L-moments, rather than the traditional method, based on central moments. Also provided is an introduction to shape descriptors based on L-moments, whose advantages over central moments-less biased and less sensitive to outliers-are demonstrated. Whether traditional or modern shape descriptions are employed, the combination methods currently in use, especially bin-means histograms, based on averaged bin means, prove to be substantially inferior to the new methods. Averaged bin-means themselves are less deficient when estimating differences between distribution shapes, as in delta plots, but are nonetheless inferior to linear-transform pooling.

Older Adults Show Intraindividual Variation in the Use of Predictive Processing

BACKGROUND

The use of prediction can aid language comprehension through preactivation of relevant word features. However, predictions can be wrong, and it has been proposed that resolving the mismatch between the predicted and presented item requires cognitive resources. Older adults tend not to predict and instead rely more on passive comprehension. Here, we tested, using an intraindividual approach, whether older adults consistently use this less demanding processing strategy while reading or whether they attempt to predict on some trials.

METHODS

We used a cross-task conflict paradigm. Younger and older participants self-paced to read sentences that ended with either an expected or unexpected word. Each sentence was then followed by a flanker stimulus that could be congruent or incongruent. We examined responses within and across the two tasks.

RESULTS

Unexpected words were in general read as quickly as expected words, indicating that typical processing of these words was similar. However, for both younger and older adults, there was a greater proportion of very slow trials for unexpected words, revealing different processing on a subset of trials. Critically, in older adults, these slowly read unexpected words engaged control, as seen in speeded responses to incongruent flanker stimuli.

CONCLUSION

Using a cross-task conflict paradigm, we showed that older adults are able to predict and engage cognitive resources to cope with prediction violations, but do not opt to use these processes consistently.

Quantifying Entropy in Response Times (RT) Distributions Using the Cumulative Residual Entropy (CRE) Function

Response times (RT) distributions are routinely used by psychologists and neuroscientists in the assessment and modeling of human behavior and cognition. The statistical properties of RT distributions are valuable in uncovering unobservable psychological mechanisms. A potentially important statistical aspect of RT distributions is their entropy. However, to date, no valid measure of entropy on RT distributions has been developed, mainly because available extensions of discrete entropy measures to continuous distributions were fraught with problems and inconsistencies. The present work takes advantage of the cumulative residual entropy (CRE) function-a well-known differential entropy measure that can circumvent those problems. Applications of the CRE to RT distributions are presented along with concrete examples and simulations. In addition, a novel measure of instantaneous CRE is developed that captures the rate of entropy reduction (or information gain) from a stimulus as a function of processing time. Taken together, the new measures of entropy in RT distributions proposed here allow for stronger statistical inferences, as well as motivated theoretical interpretations of psychological constructs such as mental effort and processing efficiency.

Examining reaction time variability on the stop-signal task in the ABCD study

OBJECTIVE

Reaction time variability (RTV) has been estimated using Gaussian, ex-Gaussian, and diffusion model (DM) indices. Rarely have studies examined interrelationships among these performance indices in childhood, and the use of reaction time (RT) computational models has been slow to take hold in the developmental psychopathology literature. Here, we extend prior work in adults by examining the interrelationships among different model parameters in the ABCD sample and demonstrate how computational models of RT can clarify mechanisms of time-on-task effects and sex differences in RTs.

METHOD

This study utilized trial-level data from the stop signal task from 8916 children (9-10 years old) to examine Gaussian, ex-Gaussian, and DM indicators of RTV. In addition to describing RTV patterns, we examined interrelations among these indicators, temporal patterns, and sex differences.

RESULTS

There was no one-to-one correspondence between DM and ex-Gaussian parameters. Nonetheless, drift rate was most strongly associated with standard deviation of RT and tau, while nondecisional processes were most strongly associated with RT, mu, and sigma. Performance worsened across time with changes driven primarily by decreasing drift rate. Boys were faster and less variable than girls, likely attributable to girls' wide boundary separation.

CONCLUSIONS

Intercorrelations among model parameters are similar in children as has been observed in adults. Computational approaches play a crucial role in understanding performance changes over time and can also clarify mechanisms of group differences. For example, standard RT models may incorrectly suggest slowed processing speed in girls that is actually attributable to other factors.

The mediating role of neurocognitive functions in the relation between physical competencies and academic achievement of primary school children

Previous studies into associations between physical, neurocognitive and academic skills have reported inconsistent results. This study aimed to get more insight into these relations by examining all three domains simultaneously, testing a complete mediational model including measures of physical competencies (cardiovascular fitness and motor skills), neurocognitive skills (attention, information processing, and core executive functions), and academic achievement (reading, mathematics, and spelling). Dutch primary school students (n = 891, 440 boys, mean age 9.17 years) were assessed on the Shuttle Run Test (cardiovascular fitness), items of the Körperkoordinationstest für Kinder and Bruininks-Oseretsky Test-II (fundamental motor skills), computerized neurocognitive tests, and standardized academic achievement tests. A multilevel structural equation model showed that physical competencies were only indirectly related to academic achievement, via specific neurocognitive functions depending on the academic domain involved. Results provide important implications, highlighting the importance of well-developed physical competencies in children.

Inhibition Predicts the Course of Depression and Anxiety Symptoms Among Adolescents: The Moderating Role of Familial Risk

ABSTRACT

Numerous theoretical models suggest that inhibition difficulties-the inability to moderate automatic responses-contribute to the onset and/or maintenance of internalizing symptoms. Inhibition deficits and internalizing disorders run in families and share overlapping genetic risk factors, suggesting that inhibition deficits may be particularly prognostic of internalizing symptoms in those with high familial risk. This study tested this hypothesis in a longitudinal sample during the transition from adolescence to early adulthood. As hypothesized, prospective associations between inhibition and anxiety and depressive symptoms 8 years later were moderated by familial risk for depression. Specifically, poorer inhibition prospectively predicted greater anxiety and depressive symptoms in those at high (but not low) familial risk for major depressive disorder. These findings provide preliminary support for impaired inhibition as an indicator of risk for later internalizing symptoms in those at high familial risk.

Relating a Spiking Neural Network Model and the Diffusion Model of Decision-Making

Many models of decision making assume accumulation of evidence to threshold as a core mechanism to predict response probabilities and response times. A spiking neural network model (Wang, 2002) instantiates these mechanisms at the level of biophysically-plausible pools of neurons with excitatory and inhibitory connections, and has numerous model parameters tuned by physiological measures. The diffusion model (Ratcliff, 1978) is a cognitive model that can be fitted to a range of behaviors and conditions. We investigated how parameters of the cognitive-level diffusion model relate to the parameters of a neural-level spiking model. In each simulated "experiment", we generated "data" from the spiking neural network by factorially combining a manipulation of choice difficulty (via the input to the spiking model) and a manipulation of one of the core parameters of the spiking model. We then fitted the diffusion model to these simulated data to observe how manipulation of each core spiking model parameter mapped on to fitted drift rate, response threshold, and non-decision time. Manipulations of parameters in the spiking model related to input sensitivity, threshold, and stimulus processing time mapped on to their conceptual analogues in the diffusion model, namely drift rate, threshold, and non-decision time. Manipulations of parameters in the spiking model with no direct analogue to the diffusion model, non-stimulus-specific background input, strength of recurrent excitation, and receptor conductances, mapped on to threshold in the diffusion model. We discuss implications of these results for interpretations of fits of the diffusion model to behavioral data.

Variability of Reaction Time as a Marker of Executive Function Impairments in Fibromyalgia

In addition to chronic widespread pain and depression and anxiety symptoms, patients with fibromyalgia frequently experience cognitive problems. This study investigated executive functions in fibromyalgia via a Go/No-Go task. To obtain comprehensive information about performance, traditional and ex-Gaussian parameters of reaction time (RT) variability were used, in addition to speed and accuracy indices. Ex-Gaussian parameters show an excellent fit to empirical RT distributions. Fifty-two female fibromyalgia patients and twenty-eight healthy controls participated. The task included 60 visual stimuli, which participants had to respond to (Go stimuli) or withhold the response to (No-Go stimuli). After 30 trials, the task rule changed, such that previous No-Go stimuli had to be responded to. Performance was indexed by the hit rate, false alarm rate, and mean (M) and intraindividual standard deviation (SD) of RT and the ex-Gaussian parameters mu, sigma, and tau. Mu and sigma indicate the M and SD of the Gaussian distribution; tau reflects the M and SD of the exponential function. Patients exhibited a lower hit rate, higher M RT, and higher tau than controls. Moreover, patients showed greater decrease of the hit rate after the change of task rule. In the entire sample, SD, sigma, and tau were inversely associated with the hit rate and positively associated with the false alarm rate. While the greater decline in hit rate after the change in task rule indicates deficient cognitive flexibility, the lack of any difference in false alarm rate suggests intact response inhibition. Higher M RT reflects reduced cognitive or motor speed. Increased tau in fibromyalgia indicates greater fluctuations in executive control and more frequent temporary lapses of attention. For the first time, this study demonstrated that indices of RT variability, in particular those derived from the ex-Gaussian function, may complement speed and accuracy parameters in the assessment of executive function impairments in fibromyalgia. Optimized assessment may facilitate the personalization of therapies aimed at improving the cognitive function of those with the disorder.

Acute effects of aerobic exercise on conflict suppression, response inhibition, and processing efficiency underlying inhibitory control processes: An ERP and SFT study

Aerobic exercise has been identified as an effective strategy for transiently enhancing inhibitory control, an ability to suppress irrelevant distractors while focusing on relevant information in facilitating the implementation of goal-directed behavior. The purpose of this study was to employ a go/no-go version of the redundant-target task and event-related potential to further determine whether inhibitory control at the perceptual and response levels as well as their underlying processing capacity and neuroelectric alterations are differentially affected by a single bout of aerobic exercise. Twenty-seven young adults completed the redundant-target task while electroencephalogram was recorded before and after one 20-min bout of moderate-intensity aerobic exercise and a sitting control condition on separate days in counterbalanced order. Although behavioral outcomes of mean-level performance did not differ between intervention conditions, time-related decreases in processing capacity for the faster responses were only observed following rest. Aerobic exercise resulted in maintained P3b amplitude from pretest to posttest for all trial types while decreased P3b amplitude from pretest to posttest during single-target and redundant-target trials was observed following rest. Further, the time-related changes in P3b amplitude were positively correlated with improvements in task performance following exercise. These findings suggest that a short bout of aerobic exercise selectively counteracts the time-related decrements in processing capacity as well as neuroelectric processing of attention and conflict suppression that contribute to behavioral outcomes of inhibitory control.

Bayesian adaptive model estimation to solve the speed accuracy tradeoff problem in psychophysical experiments

Most psychological experiments measure human cognitive function through the response time and accuracy of the response to a set of stimuli. Since response time and accuracy complement each other, it is often difficult to interpret cognitive performance based on only one dependent measurement and raises a speed-accuracy tradeoff (SAT) problem. In overcoming this problem, SAT experimental paradigms and models that integrate response time and accuracy have been proposed to understand information processing in human cognitive function. However, due to a lengthy SAT experiment for reliable model estimation, SAT experiments' practical limitations have been pointed out. Thus, these limitations call for an efficient technique to shorten the number of trials required to estimate the SAT function reliably. Instead of using a block's stimulus-onset asynchrony (SOA) accuracy with long block-based task trials, we introduced a Bayesian SAT function estimation using trial-by-trial response time and correctness, which makes SAT tasks flexible and easily extendable to multiple trials. We then proposed a Bayesian adaptive method to select optimal SOA by maximizing information gain to estimate model parameters. Simulation results showed that the proposed Bayesian adaptive estimation was highly efficient and robust for accuracy and precision of estimating SAT function by enabling "multiple-step ahead search."

Delta plots for conflict tasks: An activation-suppression race model

We describe a mathematically simple yet precise model of activation suppression that can explain the negative-going delta plots often observed in standard Simon tasks. The model postulates a race between the identification of the relevant stimulus attribute and the suppression of irrelevant location-based activation, with the irrelevant activation only having an effect if the irrelevant activation is still present at the moment when central processing of the relevant attribute starts. The model can be fitted by maximum likelihood to observed distributions of RTs in congruent and incongruent trials, and it provides good fits to two previously-reported data sets with plausible parameter values. R and MATLAB software for use with the model is provided.

Percentile rank pooling: A simple nonparametric method for comparing group reaction time distributions with few trials

Although many studies of reaction time (RT) focus on a single measure of central tendency such as the mean RT, a more detailed picture of the underlying processes can be gained by looking at full distributions of RTs. Unfortunately, for practical reasons it is sometimes difficult to obtain enough trials per participant in a condition of interest to construct such a distribution with existing methods. The purpose of this article is to propose a method of forming group RT distributions that can be used to compare the full distributions of RTs even in an infrequent condition with only a few trials per participant. In brief, the percentile ranks of each participant's infrequent-condition RTs are scored relative to a larger pool including that participant's RTs in other conditions, and a histogram of the infrequent-condition's percentile ranks is then formed by pooling across participants. The resulting histogram of infrequent-condition RT ranks shows where the RTs in that condition tend to fall relative to the other conditions, and this histogram can reveal systematic patterns in the infrequent-condition's RT distribution. To illustrate the method, I present histograms of the ranks of infrequent error RTs (~ 5% of trials), ranked relative to correct responses, in real data sets from Simon and lexical decision tasks.

Understanding Speed-Accuracy Processing Dynamics in Aphasia Using Response Time Modeling

People with aphasia demonstrate language impairments evident in both performance accuracy and processing speed, but the direct relationship between accuracy and speed requires further consideration. This article describes two recent attempts to make quantitative progress in this domain using response time modeling: the diffusion model (Ratcliff, 1978) applied to two-choice tasks and a multinomial ex-Gaussian model applied to picture naming. The diffusion model may be used to characterize core linguistic processing efficiency and speed-accuracy tradeoffs independently, and research suggests that maladaptive speed-accuracy tradeoffs lead to performance impairments in at least some people with aphasia. The multinomial ex-Gaussian response time model of picture naming provides a simple and straightforward way to estimate the optimal response time cutoffs for individual people with aphasia (i.e., the cutoff where additional time is unlikely to lead to a correct response). While response time modeling applied to aphasia research is at an early stage of development, both the diffusion model and multinomial ex-Gaussian response time model of picture naming show promise and should be further developed in future work. This article also provides preliminary recommendations for clinicians regarding how to conceptualize, identify, and potentially address maladaptive speed-accuracy tradeoffs for people with aphasia.

Cardiovascular fitness and executive functioning in primary school-aged children

Previous research in children has shown that higher cardiovascular fitness is related to better executive functioning. However, the available literature is hampered by methodological limitations. The present study investigates the relationship between cardiovascular fitness and executive functioning in a large sample of healthy children (N = 814). Cardiovascular fitness was assessed with estimated VO2Max from 20 m Shuttle Run Test performance. Executive functioning was assessed using a set of computerized neurocognitive tasks aimed at executive functions (working memory, motor inhibition, interference control) and lower-level neurocognitive functions (information processing and attention). Dependent measures derived from the neurocognitive tests were subjected to principal component analysis. Mixed model analyses tested the relation between cardiovascular fitness and neurocognitive functioning components. Results showed that children with higher cardiovascular fitness performed better on the neurocognitive function components Information Processing and Control, Visuospatial Working Memory and Attention Efficiency. The following measures contained in these components contributed to the observed relations: information processing measures, visuospatial working memory, and speed of alerting attention. No relationship was found between cardiovascular fitness and the other components: Verbal Working Memory, Attention Accuracy, and Interference Control. The present study suggests that there is a relationship between cardiovascular fitness and a specific set of executive functions and lower level neurocognitive functions. These findings highlight the importance of cardiovascular fitness for the overall health of school-aged children.

Analyzing Response Times and Other Types of Time-to-Event Data Using Event History Analysis: A Tool for Mental Chronometry and Cognitive Psychophysiology

In this Methods article, we discuss and illustrate a unifying, principled way to analyze response time data from psychological experiments—and all other types of time-to-event data. We advocate the general application of discrete-time event history analysis (EHA) which is a well-established, intuitive longitudinal approach to statistically describe and model the shape of time-to-event distributions. After discussing the theoretical background behind the so-called hazard function of event occurrence in both continuous and discrete time units, we illustrate how to calculate and interpret the descriptive statistics provided by discrete-time EHA using two example data sets (masked priming, visual search). In case of discrimination data, the hazard analysis of response occurrence can be extended with a microlevel speed-accuracy trade-off analysis. We then discuss different approaches for obtaining inferential statistics. We consider the advantages and disadvantages of a principled use of discrete-time EHA for time-to-event data compared to (a) comparing means with analysis of variance, (b) other distributional methods available in the literature such as delta plots and continuous-time EHA methods, and (c) only fitting parametric distributions or computational models to empirical data. We conclude that statistically controlling for the passage of time during data analysis is equally important as experimental control during the design of an experiment, to understand human behavior in our experimental paradigms.

The Effects of Aerobic Versus Cognitively Demanding Exercise Interventions on Executive Functioning in School-Aged Children: A Cluster-Randomized Controlled Trial

The authors performed a clustered randomized controlled trial to investigate the effects of an aerobic and a cognitively demanding exercise intervention on executive functions in primary-school-age children compared with the regular physical education program (N = 856). They hypothesized that both exercise interventions would facilitate executive functioning, with stronger effects for the cognitively demanding exercise group. The interventions were provided four times per week for 14 weeks. Linear mixed models were conducted on posttest neurocognitive function measures with baseline level as covariate. No differences were found between the exercise interventions and the control group for any of the measures. Independently of group, dose of moderate to vigorous physical activity was positively related to verbal working memory and attention abilities. This study showed that physical exercise interventions did not enhance executive functioning in children. Exposure to moderate to vigorous physical activity is a crucial aspect of the relationship between physical activity and executive functioning.

Interplay between state anxiety, heart rate variability, and cognition: An ex-Gaussian analysis of response times

The present study employed an ex-Gaussian model of response times (RTs) to elucidate the cognitive processes related to experimentally induced state anxiety (SA) and vagally mediated heart rate variability (vmHRV), an indicator of adaptive responses in both cognitive and affective domains. Participants (n = 110) completed a dual task composed of (i) a flanker attention and (2) working memory load task, while SA was induced by threat of noise. Electrocardiography was measured during the dual task and during four baseline periods in order to calculate vmHRV. RTs on the flanker task were fit to an ex-Gaussian distribution, which estimated three RT parameters: mu (Gaussian mean), sigma (Gaussian SD), and tau (combination of exponential mean and SD). First, findings indicate that threat of noise was associated with reductions in mu and tau, suggesting that SA might improve attention and motor responding. Second, higher resting vmHRV was associated with lower tau (averaged across conditions) and stronger threat-related decreases in tau. Third, intra-individual decreases in vmHRV were accompanied by concomitant decreases in tau. These findings support roles for trait and state vagal control in guiding adaptive anxiety-related (and anxiety-unrelated) attentional responses. Findings are consistent with extant theories that emphasize functional interrelations among emotion, cognition, and vagal function.

Neural correlates of cognitive processing capacity in elite soccer players

Although great progress has been made in our understanding of perceptual-cognitive expertise in team sports, the neurocognitive mechanisms underlying such cognitive advantage in the face of multiple, sometimes conflicting, channels of information are not well understood. Two electroencephalographic indices associated with perceptual decisions, the P3 component of event-related potential and alpha inter-trial phase coherence (ITPC), were measured and compared across elite soccer players and non-athletic controls while performing a redundant-target task. Specifically, we adopted an effective diagnostic tool, Systems Factorial Technology, to assess participants' workload capacity. Soccer players exhibited larger workload capacity while making faster decisions compared with controls. Moreover, this larger workload capacity was associated with modulations of P3 and alpha ITPC when processing two targets relative to one target and one distractor, an effect that was not observed in controls. Together, the present findings offer a possible mechanistic explanation of perceptual-cognitive expertise in the context of team sports.

Bridging sensory and language theories of dyslexia: Toward a multifactorial model

Competing theories of dyslexia posit that reading difficulties arise from impaired visual, auditory, phonological, or statistical learning mechanisms. Importantly, many theories posit that dyslexia reflects a cascade of impairments emanating from a single “core deficit”. Here we report two studies evaluating core deficit and multifactorial models. In Study 1, we use publicly available data from the Healthy Brain Network to test the accuracy of phonological processing measures for predicting dyslexia diagnosis and find that over 30% of cases are misclassified (sensitivity = 66.7%; specificity = 68.2%). In Study 2, we collect a battery of psychophysical measures of visual motion processing and standardized measures of phonological processing in 106 school‐aged children to investigate whether dyslexia is best conceptualized under a core‐deficit model, or as a disorder with heterogenous origins. Specifically, by capitalizing on the drift diffusion model to analyze performance on a visual motion discrimination experiment, we show that deficits in visual motion processing, perceptual decision‐making, and phonological processing manifest largely independently. Based on statistical models of how variance in reading skill is parceled across measures of visual processing, phonological processing, and decision‐making, our results challenge the notion that a unifying deficit characterizes dyslexia. Instead, these findings indicate a model where reading skill is explained by several distinct, additive predictors, or risk factors, of reading (dis)ability.

Studying the dynamics of visual search behavior using RT hazard and micro-level speed-accuracy tradeoff functions: A role for recurrent object recognition and cognitive control processes

Thanks to the work of Anne Treisman and many others, the visual search paradigm has become one of the most popular paradigms in the study of visual attention. However, statistics like mean correct response time (RT) and percent error do not usually suffice to decide between the different search models that have been developed. Recently, to move beyond mean performance measures in visual search, RT histograms have been plotted, theoretical waiting time distributions have been fitted, and whole RT and error distributions have been simulated. Here we promote and illustrate the general application of discrete-time hazard analysis to response times, and of micro-level speed-accuracy tradeoff analysis to timed response accuracies. An exploratory analysis of published benchmark search data from feature, conjunction, and spatial configuration search tasks reveals new features of visual search behavior, such as a relatively flat hazard function in the right tail of the RT distributions for all tasks, a clear effect of set size on the shape of the RT distribution for the feature search task, and individual differences in the presence of a systematic pattern of early errors. Our findings suggest that the temporal dynamics of visual search behavior results from a decision process that is temporally modulated by concurrently active recurrent object recognition, learning, and cognitive control processes, next to attentional selection processes.

Literacy skill and intra-individual variability in eye-fixation durations during reading: Evidence from a diverse community-based adult sample

To understand the effects of literacy on fundamental processes involved in reading, we report a secondary data analysis examining individual differences in global eye-movement measures and first-pass eye-movement distributions in a diverse sample of community-dwelling adults aged 16 to 64. Participants (n = 80) completed an assessment battery probing verbal and non-verbal cognitive abilities and read simple two-sentence passages while their eye movements were recorded. Analyses were focused on characterising the effects of literacy skill on both global indices of eye-fixation distributions and distributional differences in the sensitivity to lexical features. Global reading measures showed that lower literate adults read more slowly on average. However, distributional analyses of fixation durations revealed that the first-pass fixation durations of adults with lower literacy skill were not slower in general (i.e., there was no shift in the fixation duration distribution among lower literate adults). Instead, lower literacy was associated with greater intra-individual variability in first-pass fixation durations, including an increased proportion of extremely long fixations, differentially skewing the distribution of both first-fixation and gaze durations. Exploratory repeated-measures quantile regression analyses of gaze duration revealed differentially greater influences of word length among lower literate readers and greater activation of phonological and orthographic neighbours among higher literate readers, particularly in the tail of the distribution. Collectively, these findings suggest that literacy skill in adulthood is associated with systematic differences in both global and lexically driven eye-movement control during reading.

The Worst Performance Rule, or the Not-Best Performance Rule? Latent-Variable Analyses of Working Memory Capacity, Mind-Wandering Propensity, and Reaction Time

The worst performance rule (WPR) is a robust empirical finding reflecting that people's worst task performance shows numerically stronger correlations with cognitive ability than their average or best performance. However, recent meta-analytic work has proposed this be renamed the "not-best performance" rule because mean and worst performance seem to predict cognitive ability to similar degrees, with both predicting ability better than best performance. We re-analyzed data from a previously published latent-variable study to test for worst vs. not-best performance across a variety of reaction time tasks in relation to two cognitive ability constructs: working memory capacity (WMC) and propensity for task-unrelated thought (TUT). Using two methods of assessing worst performance-ranked-binning and ex-Gaussian-modeling approaches-we found evidence for both the worst and not-best performance rules. WMC followed the not-best performance rule (correlating equivalently with mean and longest response times (RTs)) but TUT propensity followed the worst performance rule (correlating more strongly with longest RTs). Additionally, we created a mini-multiverse following different outlier exclusion rules to test the robustness of our findings; our findings remained stable across the different multiverse iterations. We provisionally conclude that the worst performance rule may only arise in relation to cognitive abilities closely linked to (failures of) sustained attention.

Decomposing the composite face effect: Evidence for non-holistic processing based on the ex-Gaussian distribution

Composite faces fuse the top and bottom halves from two different faces to create a powerful illusion of a novel face. It has been argued that composite faces are processed holistically, namely that the constituent face parts are perceived as a template, rather than independent features. This study sought to uncover the locus of the composite face effect by relating its empirical reaction time distributions to theoretical ex-Gaussian parameters. The results showed that the composite face effect for unfamiliar (Experiment 1) and familiar (Experiment 2) faces is generated by pure changes in the exponential component of the ex-Gaussian distribution. This held true for both partial and complete design measures. The exponential component has been attributed to working memory and attentional processes. The results suggest the involvement of attentional and working memory processes in the composite face effect and in the perception of faces in general. They cast doubts on the holistic nature of face processing. The results also provide important constraints on future computational theories of the effect.

Differential effects of knowledge and aging on the encoding and retrieval of everyday activities

We deconstruct continuous streams of action into smaller, meaningful events. Research has shown that the ability to segment continuous activity into such events and remember their contents declines with age; however, knowledge improves with age. We investigated how young and older adults use knowledge to more efficiently encode and later remember information from everyday events by having participants view a series of self-paced slideshows depicting everyday activities. For some activities, older adults produce more normative scripts than do young adults (older adult activities) and for other activities, young adults produce more normative scripts than do older adults (young adult activities). Overall, participants viewed event boundaries longer than within events (i.e., the event boundary advantage) replicating prior research (e.g., Hard, Recchia, & Tversky, 2011). Importantly, older adults demonstrated the boundary advantage for the older adult activities but not the young adult activities, and they also had better recognition memory for the older adult activities than the young adult activities. We also found that the magnitude of a participant's boundary advantage was associated with better memory, but only for the less knowledgeable activities. Results indicate that older adults use their intact knowledge to better encode and remember everyday activities, but that knowledge and event segmentation may have independent influences on event memory.

How Much Time Do People With Aphasia Need to Respond During Picture Naming? Estimating Optimal Response Time Cutoffs Using a Multinomial Ex-Gaussian Approach

Purpose Aphasia is a language disorder caused by acquired brain injury, which generally involves difficulty naming objects. Naming ability is assessed by measuring picture naming, and models of naming performance have mostly focused on accuracy and excluded valuable response time (RT) information. Previous approaches have therefore ignored the issue of processing efficiency, defined here in terms of optimal RT cutoff, that is, the shortest deadline at which individual people with aphasia produce their best possible naming accuracy performance. The goals of this study were therefore to (a) develop a novel model of aphasia picture naming that could accurately account for RT distributions across response types; (b) use this model to estimate the optimal RT cutoff for individual people with aphasia; and (c) explore the relationships between optimal RT cutoff, accuracy, naming ability, and aphasia severity. Method A total of 4,021 naming trials across 10 people with aphasia were scored for accuracy and RT onset. Data were fit using a novel ex-Gaussian multinomial RT model, which was then used to characterize individual optimal RT cutoffs. Results Overall, the model fitted the empirical data well and provided reliable individual estimates of optimal RT cutoff in picture naming. Optimal cutoffs ranged between approximately 5 and 10 s, which has important implications for assessment and treatment. There was no direct relationship between aphasia severity, naming RT, and optimal RT cutoff. Conclusion The multinomial ex-Gaussian modeling approach appears to be a promising and straightforward way to estimate optimal RT cutoffs in picture naming in aphasia. Limitations and future directions are discussed.

Parallel probability density approximation

Probability density approximation (PDA) is a nonparametric method of calculating probability densities. When integrated into Bayesian estimation, it allows researchers to fit psychological processes for which analytic probability functions are unavailable, significantly expanding the scope of theories that can be quantitatively tested. PDA is, however, computationally intensive, requiring large numbers of Monte Carlo simulations in order to attain good precision. We introduce Parallel PDA (pPDA), a highly efficient implementation of this method utilizing the Armadillo C++ and CUDA C libraries to conduct millions of model simulations simultaneously in graphics processing units (GPUs). This approach provides a practical solution for rapidly approximating probability densities with high precision. In addition to demonstrating this method, we fit a piecewise linear ballistic accumulator model (Holmes, Trueblood, & Heathcote, 2016) to empirical data. Finally, we conducted simulation studies to investigate various issues associated with PDA and provide guidelines for pPDA applications to other complex cognitive models.

A new nonparametric test for the race model inequality

The race model inequality (RMI), as first introduced by Miller (Cognitive Psychology, 14, 247-279, 1982), entails an upper bound on the amount of statistical facilitation for reaction times (RTs) attainable by a race model within the redundant-signals paradigm. A violation of RMI may be considered as empirical evidence for a coactivation model rather than a race model. Here, we introduce a novel nonparametric procedure for evaluating the RMI for single participant analysis. The statistical procedure is based on a new probabilistic representation that highlights some neglected, but important distributional features of the RMI. In particular, we show how the reconstructed distribution function under maximal statistical facilitation for a race model is characterized by a specific truncated-type property. The results of two Monte Carlo simulation studies suggest that our procedure efficiently controls for type I error with reasonable power. Finally, unlike previous proposals for single participant analysis (e.g., Maris and Maris (Journal of Mathematical Psychology 47, 507-514, 2003)), our approach is also more consistent with the typical way to collect RT data in experimental works. R script functions for running the statistical analysis on single participant data are made freely available to the readers on a dedicated web server.

Some do and some don't? Accounting for variability of individual difference structures

A prevailing notion in experimental psychology is that individuals' performance in a task varies gradually in a continuous fashion. In a Stroop task, for example, the true average effect may be 50 ms with a standard deviation of say 30 ms. In this case, some individuals will have greater effects than 50 ms, some will have smaller, and some are forecasted to have negative effects in sign-they respond faster to incongruent items than to congruent ones! But are there people who have a true negative effect in Stroop or any other task? We highlight three qualitatively different effects: negative effects, null effects, and positive effects. The main goal of this paper is to develop models that allow researchers to explore whether all three are present in a task: Do all individuals show a positive effect? Are there individuals with truly no effect? Are there any individuals with negative effects? We develop a family of Bayesian hierarchical models that capture a variety of these constraints. We apply this approach to Stroop interference experiments and a near-liminal priming experiment where the prime may be below and above threshold for different people. We show that most tasks people are quite alike-for example everyone has positive Stroop effects and nobody fails to Stroop or Stroops negatively. We also show a case that under very specific circumstances, we could entice some people to not Stroop at all.

Drift-diffusion explains response variability and capacity for tracking objects

Being able to track objects that surround us is key for planning actions in dynamic environments. However, rigorous cognitive models for tracking of one or more objects are currently lacking. In this study, we asked human subjects to judge the time to contact (TTC) a finish line for one or two objects that became invisible shortly after moving. We showed that the pattern of subject responses had an error variance best explained by an inverse Gaussian distribution and consistent with the output of a biased drift-diffusion model. Furthermore, we demonstrated that the pattern of errors made when tracking two objects showed a level of dependence that was consistent with subjects using a single decision variable for reporting the TTC for two objects. This finding reveals a serious limitation in the capacity for tracking multiple objects resulting in error propagation between objects. Apart from explaining our own data, our approach helps interpret previous findings such as asymmetric interference when tracking multiple objects.

Multi-factor analysis in language production: Sequential sampling models mimic and extend regression results

For multi-factor analyses of response times, descriptive models (e.g., linear regression) arguably constitute the dominant approach in psycholinguistics. In contrast empirical cognitive models (e.g., sequential sampling models, SSMs) may fit fewer factors simultaneously, but decompose the data into several dependent variables (a multivariate result), offering more information to analyze. While SSMs are notably popular in the behavioural sciences, they are not significantly developed in language production research. To contribute to the development of this modelling in language, we (i) examine SSMs as a measurement modelling approach for spoken word activation dynamics, and (ii) formally compare SSMs to the default method, regression. SSMs model response activation or selection mechanisms in time, and calculate how they are affected by conditions, persons, and items. While regression procedures also model condition effects, it is only in respect to the mean RT, and little work has been previously done to compare these approaches. Through analyses of two language production experiments, we show that SSMs reproduce regression predictors, and further extend these effects through a multivariate decomposition (cognitive parameters). We also examine a combined regression-SSM approach that is hierarchical Bayesian, which can jointly model more conditions than classic SSMs, and importantly, achieve by-item modelling with other conditions. In this analysis, we found that spoken words principally differed from one another by their activation rates and production times, but not their thresholds to be activated.

Dysfunctional Neural Processes Underlying Context Processing Deficits in Schizophrenia

BACKGROUND

People with schizophrenia (PSZ) have profound deficits in context processing, an executive process that guides adaptive behaviors according to goals and stored contextual information. Although various neural processes are involved in context processing and are affected in PSZ, the core underlying neural dysfunction is unclear.

METHODS

To determine the relative importance of neural dysfunctions within prefrontal cognitive control, sensory activity, and motor activity to context processing deficits in PSZ, we examined event-related potentials (ERPs) in 60 PSZ and 51 healthy control subjects during an optimal context processing task. We also analyzed the Ex-Gaussian reaction time distribution to examine abnormalities in motor control variability in PSZ.

RESULTS

Compared with healthy control subjects, PSZ had lower response accuracy and greater variability in their normal reaction times during high context processing demands. Latencies of normal and slow responses were generally increased in PSZ. High context processing-related reductions in frontal ERPs were indicative of specific deficits in proactive and reactive cognitive controls in PSZ, while ERPs associated with visual and motor processes were reduced regardless of context processing demands, indicating generalized visuomotor deficits. In contrast to previous studies, we found that diminished frontal responses reflective of proactive control of the contextual cue, rather than visual responses of cue encoding, predicted response accuracy deficits in PSZ. In addition, probe-related ERP components of motor preparation, prefrontal reactive control, and frontomotor interaction predicted Ex-Gaussian indices of reaction time instability in PSZ.

CONCLUSIONS

Prefrontal proactive and reactive control deficits associated with failures in using mental representation likely underlie context processing deficits in PSZ.

Are model parameters linked to processing stages? An empirical investigation for the ex-Gaussian, ex-Wald, and EZ diffusion models

In previous research, the parameters of the ex-Gaussian distribution have been subject to a wide variety of interpretations. The present study investigated whether the ex-Gaussian model is capable of distinguishing effects on separate processing stages (i.e., pre-motor vs. motor). In order to do so, we used datasets where the locus of effect was quite clear. Specifically, we analyzed data from experiments comparing hand vs. foot responses-presumably differing in the motor stage-and from experiments in which the lateralized readiness potential was used to localize experimental effects into premotor vs. motor processes. Moreover, we broadened the scope to two other descriptive RT models: the ex-Wald and EZ diffusion models. To the extent possible with each of these models, we reanalyzed the RT data of 19 clearly localized experimental effects from 12 separate experiments reported in seven previously published articles. Unfortunately, we did not find a clear pattern of results for any of the models, with no clear link between effects on one of the model's parameters and effects on different processing stages. The present results suggest that one should resist the temptation to associate specific processing stages with individual parameters of the ex-Gaussian, ex-Wald, and EZ diffusion models.

Retrieval dynamics of recognition and rejection

Recognition memory is often viewed as the end-product of discrete cognitive events, involving the combination of latent operations such as the assessment of memory strength, the decision time, and the memory judgement. Recently, researchers have begun using the physical dynamics of memory retrieval to provide insight into the dynamic, possibly non-discrete, processes that underlie memory decisions. In this study, the underlying distributional properties of targets and lures were manipulated by populating lists with items drawn from either homogeneous or heterogeneous word frequency and context variability ranges. In all conditions, participants' x-, y-mouse coordinates were recorded as they processed test items, allowing estimates of response dynamics (e.g., initial deviation and area under the curve [AUC]), and eventual old/new responses. The stimulus manipulations affected the distribution shapes and, to a greater degree, the placements of subjective confidence thresholds. We observed tight correspondences between confidence and AUC for both hits and correct rejections. We interpret these results within dynamic models of recognition memory.

Systems Factorial Technology provides new insights on the other-race effect

The other-race effect refers to the difficulty of discriminating between faces from ethnic and racial groups other than one's own. This effect may be caused by a slow, feature-by-feature, analytic process, whereas the discrimination of own-race faces occurs faster and more holistically. However, this distinction has received inconsistent support. To provide a critical test, we employed Systems Factorial Technology (Townsend & Nozawa in Journal of Mathematical Psychology, 39, 321-359, 1995), which is a powerful tool for analyzing the organization of mental networks underlying perceptual processes. We compared Taiwanese participants' face discriminations of both own-race (Taiwanese woman) and other-race (Caucasian woman) faces according to the faces' nose-to-mouth separation and eye-to-eye separation. We found evidence for weak holistic processing (parallel processing) coupled with the strong analytic property of a self-terminating stopping rule for own-race faces, in contrast to strong analytic processing (serial self-terminating processing) for other-race faces, supporting the holistic/analytic hypothesis.

The role of retrieval during study: Evidence of reminding from self-paced study time

The reminding effect (Tullis, Benjamin, & Ross, Journal of Experimental Psychology: General, 143[4], 1526-1540, 2014) describes the increase in recall of a studied word when a related word is presented later in the study list. However, because the process of reminding is thought to occur during study, measures of test performance are indirect indicators of the process of reminding and are subject to influences that arise during testing. The present research seeks evidence of reminding during encoding. In two experiments, self-paced study times were used to index the online process of reminding. In Experiment 1, pairs of repeated words, related words, and unrelated words were included in a study list. Study times were shorter for words related to prior words in the list, but only when the lag between those two words was short. Relatedness affected study time by inspiring a reduction in the threshold for termination of study for related words under massed conditions. Experiment 2 replicated the reduction in study time for related words and further showed that the study time allotted to an associate of an earlier item predicted better memory for that earlier word on a cued-recall test. In this experiment, an advantage in memory was observed for related words, and self-paced study time of one word during encoding was predictive of later memory for a related word. These results suggest a link between the action of reminding at study, as indexed by changes in the distribution of study time, and later benefits to remembering, as revealed by the reminding effect.

Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.

Reduced Target Facilitation and Increased Distractor Suppression During Mind Wandering

Abstract. The perceptual decoupling hypothesis suggests a general mechanism that while mind wandering, our attention is detached from our environment, resulting in diminished processing of external stimuli. This study focused on examining two possible specific mechanisms: the global suppression of all external stimuli, and a combination of reduced target facilitation and increased distractor suppression. An attentional capture task was used in which certain trials measured distractor suppression effects and others assessed target facilitation effects. The global suppression account predicts negative impacts on both types of trials, while the combined mechanisms of reduced target facilitation and increased distractor suppression suggest that only target-present trials would be affected. Results showed no cost of mind wandering on target-absent trials, but significant distractor suppression and target facilitation effects during mind wandering on target-present trials. These findings suggest that rather than perceptual decoupling globally suppressing all stimuli, it is more selective, falling in line with evidence on strong top-down modulation.

Scoring Alternatives for Mental Speed Tests: Measurement Issues and Validity for Working Memory Capacity and the Attentional Blink Effect

Research suggests that the relation of mental speed with working memory capacity (WMC) depends on complexity and scoring methods of speed tasks and the type of task used to assess capacity limits in working memory. In the present study, we included conventional binding/updating measures of WMC as well as rapid serial visual presentation paradigms. The latter allowed for a computation of the attentional blink (AB) effect that was argued to measure capacity limitations at the encoding stage of working memory. Mental speed was assessed with a set of tasks and scored by diverse methods, including response time (RT) based scores, as well as ex-Gaussian and diffusion model parameterization. Relations of latent factors were investigated using structure equation modeling techniques. RT-based scores of mental speed yielded substantial correlations with WMC but only weak relations with the AB effect, while WMC and the AB magnitude were independent. The strength of the speed-WMC relation was shown to depend on task type. Additionally, the increase in predictive validity across RT quantiles changed across task types, suggesting that the worst performance rule (WPR) depends on task characteristics. In contrast to the latter, relations of speed with the AB effect did not change across RT quantiles. Relations of the model parameters were consistently found for the ex-Gaussian tau parameter and the diffusion model drift rate. However, depending on task type, other parameters showed plausible relations as well. The finding that characteristics of mental speed tasks determined the overall strength of relations with WMC, the occurrence of a WPR effect, and the specific pattern of relations of model parameters, implies that mental speed tasks are not exchangeable measurement tools. In spite of reflecting a general factor of mental speed, different speed tasks possess different requirements, supporting the notion of mental speed as a hierarchical construct.

Individual differences in syntactic processing: Is there evidence for reader-text interactions?

There remains little consensus about whether there exist meaningful individual differences in syntactic processing and, if so, what explains them. We argue that this partially reflects the fact that few psycholinguistic studies of individual differences include multiple constructs, multiple measures per construct, or tests for reliable measures. Here, we replicated three major syntactic phenomena in the psycholinguistic literature: use of verb distributional statistics, difficulty of object-versus subject-extracted relative clauses, and resolution of relative clause attachment ambiguities. We examine whether any individual differences in these phenomena could be predicted by language experience or general cognitive abilities (phonological ability, verbal working memory capacity, inhibitory control, perceptual speed). We find correlations between individual differences and offline, but not online, syntactic phenomena. Condition effects on reading time were not consistent within individuals, limiting their ability to correlate with other measures. We suggest that this might explain controversy over individual differences in language processing.