Diffusion models in experimental psychology: a practical introduction

Information accumulation on the item versus source test of source monitoring: Insights from diffusion modeling

Source monitoring involves attributing previous experiences (e.g., studied words as items) to their origins (e.g., screen positions as sources). The present study aimed toward a better understanding of temporal aspects of item and source processing. Participants made source decisions for recognized items either in succession (i.e., the standard format) or in separate test blocks providing independent measures of item and source decision speed. Comparable speeds of item and source decision across the test formats would suggest a full separation between item and source processing, whereas different speeds would imply their (partial) temporal overlap. To test these alternatives, we used the drift rate parameter of the diffusion model (Ratcliff, Psychological Review, 85, 59-108, 1978). We examined whether the drift rates, together with the other parameters, assessed separately for the item and source decision varied as a function of the test format. Threshold separation and nondecision time differed between the test formats, but item and source decision speeds represented by drift rates did not change significantly. Thus, despite facilitation on the source decision when the item decision was immediately followed by a test for source memory than when item and source were tested in separate blocks, findings did not suggest that source information already begins accumulating in the item test in the standard format. We discuss the temporal sequence of item and source processing in light of different assumptions about the contribution of familiarity and recollection.

Age-Related Differences in Decision-Making: Evidence Accumulation is More Gradual in Older Age

Older adults tend to exhibit longer response times than younger adults in choice tasks across cognitive domains, such as perception, attention, and memory. The diffusion model has emerged as a standard model for analyzing age differences in choice behavior. Applications of the diffusion model to choice data from younger and older adults indicate that age-related slowing is driven by a more cautious response style and slower non-decisional processes, rather than by age differences in the rate of information accumulation. The Lévy flight model, a new evidence accumulation model that extends the diffusion model, was recently developed to account for differences in response times for correct and error responses. In the Lévy flight model, larger jumps in evidence accumulation can be accommodated compared to the diffusion model. It is currently unknown whether younger and older adults differ with respect to the jumpiness of evidence accumulation. In the current study, younger and older adults (N = 40 per age group) completed a letter-number-discrimination task. Results indicate that older adults show a more gradual (less "jumpy") pattern of evidence accumulation compared to younger adults. Implications for research on cognitive aging are discussed.

The temporal profile of self-prioritization

Personal relevance exerts a powerful influence on decisional processing, such that arbitrary stimuli associated with the self are classified more rapidly than identical material linked with other people. Notwithstanding numerous demonstrations of this facilitatory effect, it remains unclear whether self-prioritization is a temporally stable outcome of decision-making. Accordingly, using a shape-label matching task in combination with computational modeling, the current experiment investigated this matter. The results were informative. First, regardless of the target of comparison (i.e., friend or stranger), self-prioritization was a persistent product of decision-making across the testing session. Second, a variant of the standard drift diffusion model in which decisional boundaries collapsed gradually over the course of the task best fit the observed data. Third, whereas the efficiency of stimulus processing increased for other-related stimuli during the task, it decreased for self-related material. Collectively, these findings advance understanding of the temporal profile of self-prioritization.

Inhibition of cued but not executed task sets depends on cue-task compatibility and practice

In task switching, processing a task cue is thought to activate the corresponding task representation ("task set"), thereby allowing for advance task preparation. However, the contribution of preparatory processes to the emergence of n-2 repetition costs as index of task set inhibition processes is debated. The present study investigated whether merely preparing for a task activates a corresponding task set, which needs to be inhibited in order to switch to a different task. To this end, we presented so-called task cue-only trials in trial n-2 and assessed subsequent n-2 repetition costs. The results revealed n-2 repetition costs following a task cue-only, but only for compatible cues with a transparent cue-task relation and only at the beginning of the experiment. In contrast, n-2 repetition costs following task execution in trial n-2 were absent. In a second experiment, we sought to rule out that the presence of n-2 repetition costs following a task cue-only and the corresponding absence following task execution were the consequence of a decay of task sets. This second experiment replicated the result pattern of the first experiment, with n-2 repetition costs following a task cue-only being present only at the beginning of the experiment and only for compatible cues. Hence, cue-induced task set inhibition effects depended on cue-task compatibility and practice. Furthermore, merely prepared task sets were more likely inhibited than executed task sets.

When 2 become 1: Autistic simultaneity judgements about asynchronous audiovisual speech

It has been proposed that autistic people experience a temporal distortion whereby the temporal binding window of multisensory integration is extended. Research to date has focused on autistic children so whether these differences persist into adulthood remains unknown. In addition, the possibility that the previous observations have arisen from between-group differences in response bias, rather than perceptual differences, has not been addressed. Participants completed simultaneity judgements of audiovisual speech stimuli across a range of stimulus-onset asynchronies. Response times and accuracy data were fitted to a drift-diffusion model so that the drift rate (a measure of processing efficiency) and starting point (response bias) could be estimated. In Experiment 1, we tested a sample of non-autistic adults who completed the Autism Quotient questionnaire. Autism Quotient score was not correlated with either drift rate or response bias, nor were there between-group differences when splitting based on the first and third quantiles of scores. In Experiment 2, we compared the performance of autistic with a group of non-autistic adults. There were no between-group differences in either drift rate or starting point. The results of this study do not support the previous suggestion that autistic people have an extended temporal binding window for audiovisual speech. In addition, exploratory analysis revealed that operationalising the temporal binding window in different ways influenced whether a group difference was observed, which is an important consideration for future work.

Age-related differences in resting-state, task-related, and structural brain connectivity: graph theoretical analyses and visual search performance

Previous magnetic resonance imaging (MRI) research suggests that aging is associated with a decrease in the functional interconnections within and between groups of locally organized brain regions (modules). Further, this age-related decrease in the segregation of modules appears to be more pronounced for a task, relative to a resting state, reflecting the integration of functional modules and attentional allocation necessary to support task performance. Here, using graph-theoretical analyses, we investigated age-related differences in a whole-brain measure of module connectivity, system segregation, for 68 healthy, community-dwelling individuals 18-78 years of age. We obtained resting-state, task-related (visual search), and structural (diffusion-weighted) MRI data. Using a parcellation of modules derived from the participants' resting-state functional MRI data, we demonstrated that the decrease in system segregation from rest to task (i.e., reconfiguration) increased with age, suggesting an age-related increase in the integration of modules required by the attentional demands of visual search. Structural system segregation increased with age, reflecting weaker connectivity both within and between modules. Functional and structural system segregation had qualitatively different influences on age-related decline in visual search performance. Functional system segregation (and reconfiguration) influenced age-related decline in the rate of visual evidence accumulation (drift rate), whereas structural system segregation contributed to age-related slowing of encoding and response processes (nondecision time). The age-related differences in the functional system segregation measures, however, were relatively independent of those associated with structural connectivity.

Causal computations of supplementary motor area on spatial impulsivity

Spatial proximity to important stimuli often induces impulsive behaviour. How we overcome impulsive tendencies is what determines behaviour to be adaptive. Here, we used virtual reality to investigate whether the spatial proximity of stimuli is causally related to the supplementary motor area (SMA) functions. In two experiments, we set out to investigate these processes using a virtual environment that recreates close and distant spaces to test the causal contributions of the SMA in spatial impulsivity. In an online first experiment (N = 93) we validated and measured the influence of distant stimuli using a go/no-go task with close (21 cm) or distant stimuli (360 cm). In experiment 2 (N = 28), we applied transcranial static magnetic stimulation (tSMS) over the SMA (double-blind, crossover, sham-controlled design) to test its computations in controlling impulsive tendencies towards close vs distant stimuli. Reaction times and error rates (omission and commission) were analysed. In addition, the EZ Model parameters (a, v, Ter and MDT) were computed. Close stimuli elicited faster responses compared to distant stimuli but also exhibited higher error rates, specifically in commission errors (experiment 1). Real stimulation over SMA slowed response latencies (experiment 2), an effect mediated by an increase in decision thresholds (a). Current findings suggest that impulsivity might be modulated by spatial proximity, resulting in accelerated actions that may lead to an increase of inaccurate responses to nearby objects. Our study also provides a first starting point on the role of the SMA in regulating spatial impulsivity.

Long-term motor training enhances functional connectivity between semantic and motor regions in an effector-specific manner: evidence from elite female football athletes

The relation between the action verb semantic processing and sensorimotor experience remains controversial. In this study, we examined whether plasticity changes in brain are specifically related to semantic processing of foot action verbs when long-term motor training is mainly aimed at the foot. To address this question, we acquired resting-state functional magnetic resonance imaging scans and behavioral data from a verb two-choice task from female expertise football players and football novices. We compared the resting-state functional connectivity (rsFC) differences between experts and novices using motor execution regions and general semantic regions (left anterior temporal lobe, lATL) as seed, and explored the neural correlates of behavioral performance. Here, the drift rate (v) parameter of the drift diffusion model (DDM) was used to capture the semantic processing capability. We found experts showed increased correlation between lATL subregions and important brain regions for motor processing, including supplementary motor area (SMA), bilateral paracentral lobule (PL), superior parietal lobule and inferior parietal lobule, in contrast to novices. Further predictive model analysis showed the FC found in rsFC analysis can significantly predict drift rate of foot action verb in both experts and novices, but not drift rate of hand action verb. Our findings therefore establish a connection between effector-related semantic processing and the plasticity changes in brain functional connectivity, attributable to long-term foot-related motor training. This provides evidence supporting the view that semantic processing is fundamentally rooted in the sensorimotor system.

The common factor of executive functions measures nothing but speed of information uptake

There is an ongoing debate about the unity and diversity of executive functions and their relationship with other cognitive abilities such as processing speed, working memory capacity, and intelligence. Specifically, the initially proposed unity and diversity of executive functions is challenged by discussions about (1) the factorial structure of executive functions and (2) unfavorable psychometric properties of measures of executive functions. The present study addressed two methodological limitations of previous work that may explain conflicting results: The inconsistent use of (a) accuracy-based vs. reaction time-based indicators and (b) average performance vs. difference scores. In a sample of 148 participants who completed a battery of executive function tasks, we tried to replicate the three-factor model of the three commonly distinguished executive functions shifting, updating, and inhibition by adopting data-analytical choices of previous work. After addressing the identified methodological limitations using drift-diffusion modeling, we only found one common factor of executive functions that was fully accounted for by individual differences in the speed of information uptake. No variance specific to executive functions remained. Our results suggest that individual differences common to all executive function tasks measure nothing more than individual differences in the speed of information uptake. We therefore suggest refraining from using typical executive function tasks to study substantial research questions, as these tasks are not valid for measuring individual differences in executive functions.

Clarifying the longitudinal factor structure, temporal stability, and construct validity of Go/No-Go task-related neural activation across adolescence and young adulthood

This study aimed to clarify the psychometric properties and development of Go/No-Go (GNG) task-related neural activation across critical periods of neurobiological maturation by examining its longitudinal stability, factor structure, developmental change, and associations with a computational index of task-general cognitive control. A longitudinal sample (N=289) of adolescents from the Michigan Longitudinal Study was assessed at four time-points (mean number of timepoints per participant=2.05; standard deviation=0.89) spanning early adolescence (ages 10-13) to young adulthood (22-25). Results suggested that regional neural activations from the "successful inhibition" (SI>GO) and "failed inhibition" (FI>GO; error-monitoring) contrasts are each described well by a single general factor. Neural activity across both contrasts showed developmental increases throughout adolescence that plateau in young adulthood. Neural activity metrics evidenced low temporal stability across this period of marked developmental change, and the SI>GO factor showed no relations with a behavioral index of cognitive control. The FI>GO factor displayed stronger criterion validity in the form of significant, positive associations with behaviorally measured cognitive control. Findings emphasize the utility of well-validated psychometric methods and longitudinal data for clarifying the measurement properties of functional neuroimaging metrics and improving measurement practices in developmental cognitive neuroscience.

Insight into differing decision-making strategies that underlie cognitively effort-based decision making using computational modeling in rats

RATIONALE

The rat cognitive effort task (rCET), a rodent model of cognitive rather than physical effort, requires animals to choose between an easy or hard visuospatial discrimination, with a correct hard choice more highly rewarded. Like in humans, there is stable individual variation in choice behavior. In previous reports, animals were divided into two groups-workers and slackers-based on their mean preference for the harder option. Although these groups differed in their response to pharmacological challenges, the rationale for using this criterion for grouping was not robust.

METHODS

We collated experimental data from multiple cohorts of male and female rats performing the rCET and used a model-based framework combining drift diffusion modeling with cluster analysis to identify the decision-making processes underlying variation in choice behavior.

RESULTS

We verified that workers and slackers are statistically different groups but also found distinct intra-group profiles. These subgroups exhibited dissociable performance during the attentional phase, linked to distinct decision-making profiles during choice. Reanalysis of previous pharmacology data using this model-based framework showed that serotonergic drug effects were explained by changes in decision boundaries and non-decision times, while scopolamine's effects were driven by changes in decision starting points and rates of evidence accumulation.

CONCLUSIONS

Modeling revealed the decision-making processes that are associated with cognitive effort costs, and how these differ across individuals. Reanalysis of drug data provided insight into the mechanisms through which different neurotransmitter systems impact cognitively effortful attention and decision-making processes, with relevance to multiple psychiatric disorders.

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.

Reduced categorical learning of faces in dyslexia

The perception of phonological categories in dyslexia is less refined than in typically developing (TD) individuals. Traditionally, this characteristic was considered unique to phonology, yet many studies showed non-phonological perceptual difficulties. Importantly, measuring the dynamics of cortical adaptation, associated with category acquisition, revealed a broadly distributed faster decay of cortical adaptation. Taken together, these observations suggest that the acquisition of perceptual categories in dyslexia may be slower across modalities. To test this, we tested adult individuals with developmental dyslexia (IDDs) and TDs on learning of two unknown faces, yielding face-specific categorization. Initial accuracy was similar in the two groups, yet practice-induced increase in accuracy was significantly larger in TDs. Modeling the learning process (using Drift Diffusion Model) revealed that TDs' steeper learning results from a larger increase in their effective face-specific signal. We propose that IDDs' slower item-specific categorical learning of unknown faces indicates that slower categorical learning in dyslexia is a core, domain-general difficulty.

Behavioral impulse and time pressure jointly influence intentional inhibition: evidence from the Free Two-Choice Oddball task

Intentional inhibition is a crucial component of self-regulation, yet it is under-researched, because it is difficult to study without external stimuli or overt behaviors. Although Free-Choice tasks have been developed, it remains unclear how two key design features (i.e., behavioral impulse and time pressure) affect their sensitivity to intentional inhibition. To investigate this, the present study developed a Free Two-Choice Oddball task, which generated both an inhibition rate index and a response time (RT) index. Two experiments were conducted to systematically manipulate the ratio of the reactive standard to oddball trials and reaction time limit, inducing diverse behavioral impulses and different time pressures. The following findings were obtained from the critical Free-Choice trials. In the equal ratio condition, participants demonstrated comparable RTs for both the standard and oddball responses. In the moderate-ratio condition, participants exhibited longer RTs for the oddball than standard responses under low- but not high-time pressure. In the high-ratio condition, while RTs for the oddball responses were longer than those for the standard responses under both the high- and low-time pressures, participants displayed a decreased inhibition rate under the high-time pressure compared to the low-time pressure. Finally, participants exhibited a reduced inhibition rate in the high-ratio condition compared to the moderate-ratio condition. Together, these findings suggest that Free-Choice tasks can reflect intentional inhibition under specific conditions, and intentional inhibition is susceptible to both behavioral impulse and time pressure, while also establishing the theoretical and methodological foundations for subsequent research.

Exposure to temporal variability promotes subsequent adaptation to new temporal regularities

Noise is intuitively thought to interfere with perceptual learning; However, human and machine learning studies suggest that, in certain contexts, variability may reduce overfitting and improve generalizability. Whereas previous studies have examined the effects of variability in learned stimuli or tasks, it is hitherto unknown what are the effects of variability in the temporal environment. Here, we examined this question in two groups of adult participants (N = 40) presented with visual targets at either random or fixed temporal routines and then tested on the same type of targets at a new nearly-fixed temporal routine. Findings reveal that participants of the random group performed better and adapted quicker following a change in the timing routine, relative to participants of the fixed group. Corroborated with eye-tracking and computational modeling, these findings suggest that prior exposure to temporal variability promotes the formation of new temporal expectations and enhances generalizability in a dynamic environment. We conclude that noise plays an important role in promoting perceptual learning in the temporal domain: rather than interfering with the formation of temporal expectations, noise enhances them. This counterintuitive effect is hypothesized to be achieved through eliminating overfitting and promoting generalizability.

Reward-based modulation of task-switching performance: a diffusion model analysis

Investigating the interface between motivation and cognitive control, we conducted two task switching experiments (N = 96 each) with reward manipulation where participants switched between three different tasks. We measured N-2 task repetition costs, which denote the performance decrement in N-2 task repetition sequences (ABA) relative to N-2 task switch sequences (CBA), and which are presumed to be a marker of inhibitory control in task switching. Participants in the reward group received performance-contingent reward in the second phase of each experiment, and in the second experiment they were additionally penalized for errors. Reward thresholds were determined individually based on participants' performance during the first phase of each experiment. Participants in the control group did not receive any reward. The reward manipulation led to faster performance in the reward group relative to the control group. Diffusion modeling revealed that the reward manipulation induced an increase in drift rate parameter, consistent with dopamine-based enhancement of attentional focus under reward. Contrary to our expectations, no robust evidence for a reward-based modulation of N-2 repetition costs was found across the two experiments. N-2 task repetition costs were small in both experiments, and possibly, a larger amount of inhibitory control is needed in order to obtain empirical evidence for a reward-related modulation thereof. However, additional analyses suggested that reward may not interact with inhibitory control on the task level at all.

Broadening of attention dilates the pupil

Inconclusive evidence suggests that the pupil is more dilated when the breadth of attention is broad compared to narrow. To further investigate this relationship, we recorded pupil size from healthy volunteers while inducing trial-wise changes in breadth of attention using a shape-discrimination task where participants had to remember the location of a gap in a small or a large circle. A visual search task with targets presented at different distances from the centre of the screen was used to behaviourally assess the success of the manipulation of breadth of attention. Data were analysed using a generalised additive mixed model to test the experimental effects on pupil size after controlling for the effects of gaze location and eye vergence. The results showed that the pupil was more dilated in the broad-breadth-of-attention condition compared to the narrow-breadth-of-attention condition. However, the effect of attentional breadth on visual search performance was not mediated by pupil size, suggesting that more research is needed to understand the functional role of pupil dilation in relation to breadth of attention.

Social norms shape visual appearance: Taking a closer look at the link between social norm learning and perceptual decision-making

One of the most fundamental questions in social psychology is whether norms can change individuals' minds by shaping the visual appearance of stimuli. This question was first raised by Muzafer Sherif (1935). Drawing on the extended social reinforcement account (Germar and Mojzisch, 2019), we aimed to provide a rigorous test of the hypothesis that norm learning leads to a persistent perceptual bias and, hence, to a change in the visual appearance of stimuli. From a methodological perspective, we used both a diffusion model approach and the method of adjustment, a well-established technique from psychophysics and vision research. The results of Experiments 1-3 show that norm effects on perceptual decision-making are robustly replicable, and are due to genuine social influence, that is, they cannot be explained by non-social priming, contingency learning effects (Experiments 1 and 2) or anchoring effects (Experiment 3). Most importantly, by using a psychophysical approach, Experiment 4 shows, for the first time, that social norm learning alters individuals' point of subjective equality and, hence, the visual appearance of stimuli.

Quantitative susceptibility mapping of brain iron in healthy aging and cognition

Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that can assess the magnetic properties of cerebral iron in vivo. Although brain iron is necessary for basic neurobiological functions, excess iron content disrupts homeostasis, leads to oxidative stress, and ultimately contributes to neurodegenerative disease. However, some degree of elevated brain iron is present even among healthy older adults. To better understand the topographical pattern of iron accumulation and its relation to cognitive aging, we conducted an integrative review of 47 QSM studies of healthy aging, with a focus on five distinct themes. The first two themes focused on age-related increases in iron accumulation in deep gray matter nuclei versus the cortex. The overall level of iron is higher in deep gray matter nuclei than in cortical regions. Deep gray matter nuclei vary with regard to age-related effects, which are most prominent in the putamen, and age-related deposition of iron is also observed in frontal, temporal, and parietal cortical regions during healthy aging. The third theme focused on the behavioral relevance of iron content and indicated that higher iron in both deep gray matter and cortical regions was related to decline in fluid (speed-dependent) cognition. A handful of multimodal studies, reviewed in the fourth theme, suggest that iron interacts with imaging measures of brain function, white matter degradation, and the accumulation of neuropathologies. The final theme concerning modifiers of brain iron pointed to potential roles of cardiovascular, dietary, and genetic factors. Although QSM is a relatively recent tool for assessing cerebral iron accumulation, it has significant promise for contributing new insights into healthy neurocognitive aging.

Static and dynamic functional connectome reveals reconfiguration profiles of whole-brain network across cognitive states

Assessment of functional connectivity (FC) has revealed a great deal of knowledge about the macroscale spatiotemporal organization of the brain network. Recent studies found task-versus-rest network reconfigurations were crucial for cognitive functioning. However, brain network reconfiguration remains unclear among different cognitive states, considering both aggregate and time-resolved FC profiles. The current study utilized static FC (sFC, i.e., long timescale aggregate FC) and sliding window-based dynamic FC (dFC, i.e., short timescale time-varying FC) approaches to investigate the similarity and alterations of edge weights and network topology at different cognitive loads, particularly their relationships with specific cognitive process. Both dFC/sFC networks showed subtle but significant reconfigurations that correlated with task performance. At higher cognitive load, brain network reconfiguration displayed increased functional integration in the sFC-based aggregate network, but faster and larger variability of modular reorganization in the dFC-based time-varying network, suggesting difficult tasks require more integrated and flexible network reconfigurations. Moreover, sFC-based network reconfigurations mainly linked with the sensorimotor and low-order cognitive processes, but dFC-based network reconfigurations mainly linked with the high-order cognitive process. Our findings suggest that reconfiguration profiles of sFC/dFC networks provide specific information about cognitive functioning, which could potentially be used to study brain function and disorders.

Neural superstatistics for Bayesian estimation of dynamic cognitive models

Mathematical models of cognition are often memoryless and ignore potential fluctuations of their parameters. However, human cognition is inherently dynamic. Thus, we propose to augment mechanistic cognitive models with a temporal dimension and estimate the resulting dynamics from a superstatistics perspective. Such a model entails a hierarchy between a low-level observation model and a high-level transition model. The observation model describes the local behavior of a system, and the transition model specifies how the parameters of the observation model evolve over time. To overcome the estimation challenges resulting from the complexity of superstatistical models, we develop and validate a simulation-based deep learning method for Bayesian inference, which can recover both time-varying and time-invariant parameters. We first benchmark our method against two existing frameworks capable of estimating time-varying parameters. We then apply our method to fit a dynamic version of the diffusion decision model to long time series of human response times data. Our results show that the deep learning approach is very efficient in capturing the temporal dynamics of the model. Furthermore, we show that the erroneous assumption of static or homogeneous parameters will hide important temporal information.

Neurocognitive Mechanisms Underlying Attention Bias Towards Pain: Evidence From a Drift-Diffusion Model and Event-Related Potentials

Although combining computational modeling with event-related potentials (ERPs) can precisely characterize neurocognitive processes involved in attention bias, it has yet to be applied in the context of pain. Here, a hierarchical drift-diffusion model (DDM) along with ERPs was used to characterize the neurocognitive mechanisms underlying attention bias towards pain. A spatial cueing paradigm was adopted, in which the locations of targets were either validly or invalidly predicted by spatial cues related to pain or nonpain signals. DDM-derived nondecision time was shorter for targets validly cued by pain signals than by nonpain signals, thus indicating speeded attention engagement towards pain; drift rate was slower for targets invalidly cued by pain signals than by nonpain signals, reflecting slower attention disengagement from pain. The facilitated engagement towards pain was partially mediated by the enhanced lateralization of cue-evoked N1 amplitudes, which relate to the bottom-up, stimulus-driven processes of detecting threatening signals. On the other hand, the retarded disengagement from pain was partially mediated by the enhanced target-evoked anterior N2 amplitudes, which relate to the top-down, goal-driven processes of conflict monitoring and behavior regulating. These results demonstrated that engagement and disengagement components of pain-related attention bias are governed by distinct neurocognitive mechanisms. However, it remains possible that the findings are not pain-specific, but rather, are related to threat or aversiveness in general. This deserves to be further examined by adding a control stimulus modality. PERSPECTIVE: This study characterized the neurocognitive processes involved in attention bias towards pain through combining a hierarchical DDM and ERPs. Our results revealed distinctive neurocognitive mechanisms underlying engagement and disengagement components of attention bias. Future studies are warranted to examine whether our findings are pain-specific or not.

Changing the incentive structure of social media platforms to halt the spread of misinformation

The powerful allure of social media platforms has been attributed to the human need for social rewards. Here, we demonstrate that the spread of misinformation on such platforms is facilitated by existing social 'carrots' (e.g., 'likes') and 'sticks' (e.g., 'dislikes') that are dissociated from the veracity of the information shared. Testing 951 participants over six experiments, we show that a slight change to the incentive structure of social media platforms, such that social rewards and punishments are contingent on information veracity, produces a considerable increase in the discernment of shared information. Namely, an increase in the proportion of true information shared relative to the proportion of false information shared. Computational modeling (i.e., drift-diffusion models) revealed the underlying mechanism of this effect is associated with an increase in the weight participants assign to evidence consistent with discerning behavior. The results offer evidence for an intervention that could be adopted to reduce misinformation spread, which in turn could reduce violence, vaccine hesitancy and political polarization, without reducing engagement.

Modeling Eye Movements During Decision Making: A Review

This article reviews recent advances in the psychometric and econometric modeling of eye-movements during decision making. Eye movements offer a unique window on unobserved perceptual, cognitive, and evaluative processes of people who are engaged in decision making tasks. They provide new insights into these processes, which are not easily available otherwise, allow for explanations of fundamental search and choice phenomena, and enable predictions of future decisions. We propose a theoretical framework of the search and choice tasks that people commonly engage in and of the underlying cognitive processes involved in those tasks. We discuss how these processes drive specific eye-movement patterns. Our framework emphasizes the central role of task and strategy switching for complex goal attainment. We place the extant literature within that framework, highlight recent advances in modeling eye-movement behaviors during search and choice, discuss limitations, challenges, and open problems. An agenda for further psychometric modeling of eye movements during decision making concludes the review.

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.

Computational approaches to modeling gambling behaviour: Opportunities for understanding disordered gambling

Computational modeling has become an important tool in neuroscience and psychiatry research to provide insight into the cognitive processes underlying normal and pathological behavior. There are two modeling frameworks, reinforcement learning (RL) and drift diffusion modeling (DDM), that are well-developed in cognitive science, and have begun to be applied to Gambling Disorder. RL models focus on explaining how an agent uses reward to learn about the environment and make decisions based on outcomes. The DDM is a binary choice framework that breaks down decision making into psychologically meaningful components based on choice reaction time analyses. Both approaches have begun to yield insight into aspects of cognition that are important for, but not unique to, gambling, and thus relevant to the development of Gambling Disorder. However, these approaches also oversimplify or neglect various aspects of decision making seen in real-world gambling behavior. Gambling Disorder presents an opportunity for 'bespoke' modeling approaches to consider these neglected components. In this review, we discuss studies that have used RL and DDM frameworks to investigate some of the key cognitive components in gambling and Gambling Disorder. We also include an overview of Bayesian models, a methodology that could be useful for more tailored modeling approaches. We highlight areas in which computational modeling could enable progression in the investigation of the cognitive mechanisms relevant to gambling.

Age-related differences in frontoparietal activation for target and distractor singletons during visual search

Age-related decline in visual search performance has been associated with different patterns of activation in frontoparietal regions using functional magnetic resonance imaging (fMRI), but whether these age-related effects represent specific influences of target and distractor processing is unclear. Therefore, we acquired event-related fMRI data from 68 healthy, community-dwelling adults ages 18-78 years, during both conjunction (T/F target among rotated Ts and Fs) and feature (T/F target among Os) search. Some displays contained a color singleton that could correspond to either the target or a distractor. A diffusion decision analysis indicated age-related increases in sensorimotor response time across all task conditions, but an age-related decrease in the rate of evidence accumulation (drift rate) was specific to conjunction search. Moreover, the color singleton facilitated search performance when occurring as a target and disrupted performance when occurring as a distractor, but only during conjunction search, and these effects were independent of age. The fMRI data indicated that decreased search efficiency for conjunction relative to feature search was evident as widespread frontoparietal activation. Activation within the left insula mediated the age-related decrease in drift rate for conjunction search, whereas this relation in the FEF and parietal cortex was significant only for individuals younger than 30 or 44 years, respectively. Finally, distractor singletons were associated with significant parietal activation, whereas target singletons were associated with significant frontoparietal deactivation, and this latter effect increased with adult age. Age-related differences in frontoparietal activation therefore reflect both the overall efficiency of search and the enhancement from salient targets.

Utility of Diffusion Modeling of Cogstate Brief Battery Test Performance in Detecting Mild Cognitive Impairment

Cognitive testing data are essential to the diagnosis of mild cognitive impairment (MCI), and computerized cognitive testing, such as the Cogstate Brief Battery, has proven helpful in efficiently identifying harbingers of dementia. This study provides a side-by-side comparison of traditional Cogstate outcomes and diffusion modeling of these outcomes in predicting MCI diagnosis. Participants included 257 older adults (160 = normal cognition; 97 = MCI). Results showed that both traditional Cogstate and diffusion modeling analyses predicted MCI diagnosis with acceptable accuracy. Cogstate measures of recognition learning and working memory accuracy and diffusion modeling variable of decision-making efficiency (drift rate) and nondecisional time were most predictive of MCI. While participants with normal cognition demonstrated a change in response caution (boundary separation) when transitioning tasks, participants with MCI did not evidence this change.

Performance-contingent reward increases the use of congruent distracting information

In conflict tasks like the Simon task, participants are instructed to respond to a task-relevant target dimension while ignoring additional distracting information. In the Simon task the distracting spatial information can be congruent or incongruent with the task-relevant target information, causing a congruency effect. As seen in the proportion congruency effect and the congruency sequence effect, this congruency effect is larger in mostly congruent blocks and following congruent trials, respectively. Common theories suggest that when the proportion of incongruent trials is high or after an incongruent trial, focus on the task-relevant target information is increased and distracting information is inhibited. In two experiments, we investigated how reward modulates these phenomena. Specifically, performance-contingent reward - but not non-contingent reward - increased the usage of the distracting information in mostly congruent blocks or following congruent trials, while the adaptation to incongruency (i.e., mostly incongruent blocks or preceding incongruent trials) was the same in all conditions. Additional diffusion model analyses found that this effect of performance-contingent reward was captured by the drift rate parameter. These results suggest an increased focus on the target information by incongruent trials independent from reward, while the adaptation to (mostly) congruent trials characterized by increased usage of distracting information can be motivationally boosted. That is, performance-contingent reward increases the use of congruent distracting information beyond a mere relaxation of the increased target-focus following (mostly) congruent trials.

Task Switching: On the Relation of Cognitive Flexibility with Cognitive Capacity

The task-switching paradigm is deemed a measure of cognitive flexibility. Previous research has demonstrated that individual differences in task-switch costs are moderately inversely related to cognitive ability. However, current theories emphasize multiple component processes of task switching, such as task-set preparation and task-set inertia. The relations of task-switching processes with cognitive ability were investigated in the current study. Participants completed a task-switching paradigm with geometric forms and a visuospatial working memory capacity (WMC) task. The task-switch effect was decomposed with the diffusion model. Effects of task-switching and response congruency were estimated as latent differences using structural equation modeling. Their magnitudes and relations with visuospatial WMC were investigated. Effects in the means of parameter estimates replicated previous findings, namely increased non-decision time in task-switch trials. Further, task switches and response incongruency had independent effects on drift rates, reflecting their differential effects on task readiness. Findings obtained with the figural tasks employed in this study revealed that WMC was inversely related to the task-switch effect in non-decision time. Relations with drift rates were inconsistent. Finally, WMC was moderately inversely related to response caution. These findings suggest that more able participants either needed less time for task-set preparation or that they invested less time for task-set preparation.

Cross-modal interactions at the audiovisual cocktail-party revealed by behavior, ERPs, and neural oscillations

Theories of attention argue that objects are the units of attentional selection. In real-word environments such objects can contain visual and auditory features. To understand how mechanisms of selective attention operate in multisensory environments, in this pre-registered study, we created an audiovisual cocktail-party situation, in which two speakers (left and right of fixation) simultaneously articulated brief numerals. In three separate blocks, informative auditory speech was presented (a) alone or paired with (b) congruent or (c) uninformative visual speech. In all blocks, subjects localized a pre-defined numeral. While audiovisual-congruent and uninformative speech improved response times and speed of information uptake according to diffusion modeling, an ERP analysis revealed that this did not coincide with enhanced attentional engagement. Yet, consistent with object-based attentional selection, the deployment of auditory spatial attention (N2ac) was accompanied by visuo-spatial attentional orienting (N2pc) irrespective of the informational content of visual speech. Notably, an N2pc component was absent in the auditory-only condition, demonstrating that a sound-induced shift of visuo-spatial attention relies on the availability of audio-visual features evolving coherently in time. Additional exploratory analyses revealed cross-modal interactions in working memory and modulations of cognitive control.

Identifying the duration of emotional stimulus presentation for conscious versus subconscious perception via hierarchical drift diffusion models

To investigate subliminal priming effects, different durations for stimulus presentation are applied ranging from 8 to 30 ms. This study aims to select an optimal presentation span whichleads to a subconscious processing. 40 healthy participants rated emotional faces (sad, neutral or happy expression) presented for 8.3 ms, 16.7 ms and 25 ms. Alongside subjective and objectivestimulus awareness, task performance was estimated via hierarchical drift diffusion models. Participants reported stimulus awareness in 65 % of the 25 ms trials,in 36 % of 16.7 ms trials, and in 2.5 % of 8.3 ms trials.Emotion-dependent responses were reflected in decreased performance (drift rates, accuracy)during sad trials. The detection rate (probability of making a correct response) during 8.3 ms was 12.2 % and slightly above chance level (33.333 % for three response options) during 16.7 ms trials (36.8 %). The experiments suggest a presentation time of 16.7 ms as optimal for subconscious priming. An emotion-specific response was detected during 16.7 ms while the performanceindicates a subconscious processing.

Does aging amplify the rule-based efficiency effect in action selection?

When it comes to the selection of adequate movements, people may apply varying strategies. Explicit if-then rules, compared to implicit prospective action planning, can facilitate action selection in young healthy adults. But aging alters cognitive processes. It is unknown whether older adults may similarly, profit from a rule-based approach to action selection. To investigate the potential effects of aging, the Rule/Plan Motor Cognition (RPMC) paradigm was applied to three different age groups between 31 and 90 years of age. Participants selected grips either instructed by a rule or by prospective planning. As a function of age, we found a general increase in a strategy-specific advantage as quantified by the difference in reaction time between plan- and rule-based action selection. However, in older age groups, these differences went in both directions: some participants initiated rule-based action selection faster, while for others, plan-based action selection seemed more efficient. The decomposition of reaction times into speed of the decision process, action encoding, and response caution components suggests that rule-based action selection may reduce action encoding demands in all age groups. There appears a tendency for the younger and middle age groups to have a speed advantage in the rule task when it comes to information accumulation for action selection. Thus, one influential factor determining the robustness of the rule-based efficiency effect across the lifespan may be presented by the reduced speed of information uptake. Future studies need to further specify the role of these parameters for efficient action selection.

The role of task-relevant and task-irrelevant information in congruency sequence effects: Applying the diffusion model for conflict tasks

In conflict tasks, such as the Simon, Eriksen flanker, or Stroop task, the congruency effect is often reduced after an incongruent compared to a congruent trial: the congruency sequence effect (CSE). It was suggested that the CSE may reflect increased processing of task-relevant information and/or suppression of task-irrelevant information after experiencing an incongruent relative to a congruent trial. In the present study, we contribute to this discussion by applying the Diffusion Model for Conflict tasks (DMC) framework in the context of CSEs to flanker and Simon tasks. We argue that DMC independently models the task-relevant and task-irrelevant information and thus is a first good candidate for disentangling their unique contributions. As a first approach, we fitted DMC conjointly or separately to previously congruent or incongruent trials, using four empirical flanker and two Simon data sets. For the flanker task, we fitted the classical DMC version. For the Simon task, we fitted a generalized DMC version which allows the task-irrelevant information to undershoot when swinging back to zero. After considering the model fits, we present a second approach, where we implemented a cognitive control mechanism to simulate the influence of increased processing of task-relevant information or increased suppression of task-irrelevant information. Both approaches demonstrate that the suppression of task-irrelevant information is essential to create the typical CSE pattern. Increased processing of task-relevant information, however, could rarely describe the CSE accurately.

Electrophysiological correlates of self-prioritization

Personally relevant stimuli exert a powerful influence on social cognition. What is not yet fully understood, however, is how early in the processing stream self-relevance influences decisional operations. Here we used a shape-label matching task in conjunction with electroencephalography and computational modeling to explore this issue. A theoretically important pattern of results was observed. First, a standard self-prioritization effect emerged indicating that responses to self-related items were faster and more accurate than responses to other-related stimuli. Second, a hierarchical drift diffusion model analysis revealed that this effect was underpinned by the enhanced uptake of evidence from self-related stimuli. Third, self-other discrimination during matching trials was observed at both early posterior N1 and late centro-parietal P3 components. Fourth, whereas the N1 was associated with the rate of information accumulation during decisional processing, P3 activity was linked with the evidential requirements of response selection. These findings elucidate the electrophysiological correlates of self-prioritization.

Duration discrimination: A diffusion decision modeling approach

The human ability to discriminate the duration of two subsequently presented stimuli is often studied with tasks that involve a comparison between a standard stimulus (with fixed duration) and comparison stimuli (with varying durations). The performance in such tasks is influenced by the presentation order of these successively presented stimuli. The so-called Type A effect refers to the impact of presentation order on the point of subjective equality. The Type B effect describes effects of presentation order on the just-noticeable-difference. Cognitive models that account for these context effects assume that participants' duration estimation is influenced by the history of previously encountered stimuli. For example, the internal reference model assumes that the magnitude of a "typical" stimulus is represented by an internal reference. This internal reference evolves throughout an experiment and is updated on every trial. Different recent models have in common that they describe how the internal reference is computed but are agnostic to the decision process itself. In this study, we develop a new model that incorporates the mechanisms of perceptual discrimination models into a diffusion model. The diffusion model focuses on the dynamics of the decision process itself and accounts for choice and response times based on a set of latent cognitive variables. We show that our model accurately predicts the accuracy and response time distribution in a classical duration discrimination task. Further, model parameters were sensitive to the Type A and B effect. The proposed model opens up new opportunities for studying human discrimination performance (e.g., individual differences).

Parallel Acquisition of Uncorrelated Sequences does Not Provide Firm Evidence for a Modular Sequence-Learning System

Dual-systems theories of sequence learning assume that sequence learning may proceed within a unidimensional learning system that is immune to cross-dimensional interference because information is processed and represented in dimension-specific, encapsulated modules. Important evidence for such modularity comes from studies investigating the absence or presence of interference between multiple uncorrelated sequences (e.g., a sequence of color stimuli and a sequence of motor keypresses). Here we question the premise that the parallel acquisition of uncorrelated sequences provides convincing evidence for a modularized learning system. In contrast, we demonstrate that parallel acquisition of multiple uncorrelated sequences is well predicted by a computational model that assumes a single learning system with joint representations of stimulus and response features.

Staggered Onsets of Processing Relevant and Irrelevant Stimulus Features Produce Different Dynamics of Congruency Effects

The dynamics of congruency effects in conflict tasks can be analyzed by means of delta plots which depict the reaction-time differences between incongruent and congruent conditions across the quantiles of the reaction-time distributions. Delta plots exhibit a variety of different shapes. Here we test the hypothesis that staggered onsets of processing task-relevant and task-irrelevant features for response selection (together with a declining influence of the irrelevant feature) produce such variety. For this purpose, staggered onsets were implemented in two extensions of the Leaky, Competing Accumulator model. We show the cardinal capability of these models to produce different shapes of delta plots with different assumptions about temporal offsets between processing relevant and irrelevant stimulus features. Applying the models to experimental data, we first show that they can reproduce the delta plots observed with a conflict task with stimulus size as the irrelevant feature. For this task congruency effects are delayed and appear only at longer reaction times. Second, we fit the models to the results of two new Simon-task experiments with an experimentally controlled temporal offset in addition to the internal one. The experimentally induced variations of the shape of delta plots for this task could be reasonably well fitted by one of the two models that assumed an early start of response selection as soon as either the relevant or the irrelevant stimulus feature becomes available. We conclude that delta plots are crucially shaped by staggered onsets of processing relevant and irrelevant features for response selection.

Decision times in orthographic processing: a cross-linguistic study

Reading comparisons across transparent and opaque orthographies indicate critical differences that may reveal the mechanisms involved in orthographic decoding across orthographies. Here, we address the role of criterion and speed of processing in accounting for performance differences across languages. We used binary tasks involving orthographic (words-pseudowords), and non-orthographic materials (female-male faces), and analyzed results based on Ratcliff's Diffusion model. In the first study, 29 English and 28 Italian university students were given a lexical decision test. English observers made more errors than Italian observers while showing generally similar reaction times. In terms of the diffusion model, the two groups differed in the decision criterion: English observers used a lower criterion. There was no overall cross-linguistic difference in processing speed, but English observers showed lower values for words (and a smaller lexicality effect) than Italians. In the second study, participants were given a face gender judgment test. Female faces were identified slower than the male ones with no language group differences. In terms of the diffusion model, there was no difference between groups in drift rate and boundary separation. Overall, the new main finding concerns a difference in decision criterion limited to the orthographic task: English individuals showed a more lenient criterion in judging the lexicality of the items, a tendency that may explain why, despite lower accuracy, they were not slower. It is concluded that binary tasks (and the Diffusion model) can reveal cross-linguistic differences in orthographic processing which would otherwise be difficult to detect in standard single-word reading tasks.

Intra-Subject Variability, Intelligence, and ADHD Traits in a Community-Based Sample

OBJECTIVE

The present study investigates the predictive validity of intra-subject variability (ISV) for ADHD traits in a community-based sample and the stability of the relationship between ISV and fluid intelligence (gf) across the continuum of ADHD traits.

METHOD

Age-residualized data from 426 participants (8-18 years, 6% ADHD) was used to investigate whether ex-Gaussian and DDM parameters derived from simple choice-reaction-time tasks can predict continuously assessed ADHD traits. Multiple-Group-Analyses and Latent-Moderated-Structural-Equations were used to test whether ADHD traits moderate the relationship between ISV and gf.

RESULTS

σ and μ of the ex-Gaussian model as well as DDM parameters drift rate (v) and boundary separation (a) significantly predicted general ADHD traits, while τ predicted attention difficulties specifically. Across the ADHD continuum, σ and v were significant predictors of gf.

CONCLUSION

The results confirm the link between ISV and ADHD. The relationship between ISV and gf appears stable across the ADHD continuum.

The effect of perceptual expectation on processing gain, attention and the perceptual decision bias in children and adolescents with Autism Spectrum Disorder (ASD)

Perceptual expectations influence perception, attention and the perceptual decision bias during visuospatial orienting, which is impaired in individuals with Autism Spectrum Disorder (ASD). In this study, we investigated whether during visuospatial orienting, perceptual expectations in ASD differentially influence perception, attention and the perceptual decision bias relative to neurotypical controls (NT). Twenty-three children and adolescents with ASD and 23 NT completed a visuospatial orienting task, which compared the effect of a valid relative to an invalid perceptual expectation on target detection (cue validity effect). Group differences were calculated regarding the cue validity effect on neural correlates of processing gain (N1a amplitude) and attention (N1pc amplitude), the perceptual decision bias and mean reaction time (RT). In ASD relative to NT, findings showed a reduced processing gain for validly relative to invalidly cued targets and increased attentional response following invalidly relative to validly cued targets. Increased attention correlated with faster performance across groups. Increased processing correlated with a higher perceptual decision bias and faster mean RT in NT, but not in ASD. Results suggest that during visuospatial orienting, perceptual expectations in ASD may drive changes in sensory processing and stimulus-driven attention, which may differentially guide behavioural responses.

A practical introduction to using the drift diffusion model of decision-making in cognitive psychology, neuroscience, and health sciences

Recent years have seen a rapid increase in the number of studies using evidence-accumulation models (such as the drift diffusion model, DDM) in the fields of psychology and neuroscience. These models go beyond observed behavior to extract descriptions of latent cognitive processes that have been linked to different brain substrates. Accordingly, it is important for psychology and neuroscience researchers to be able to understand published findings based on these models. However, many articles using (and explaining) these models assume that the reader already has a fairly deep understanding of (and interest in) the computational and mathematical underpinnings, which may limit many readers' ability to understand the results and appreciate the implications. The goal of this article is therefore to provide a practical introduction to the DDM and its application to behavioral data - without requiring a deep background in mathematics or computational modeling. The article discusses the basic ideas underpinning the DDM, and explains the way that DDM results are normally presented and evaluated. It also provides a step-by-step example of how the DDM is implemented and used on an example dataset, and discusses methods for model validation and for presenting (and evaluating) model results. Supplementary material provides R code for all examples, along with the sample dataset described in the text, to allow interested readers to replicate the examples themselves. The article is primarily targeted at psychologists, neuroscientists, and health professionals with a background in experimental cognitive psychology and/or cognitive neuroscience, who are interested in understanding how DDMs are used in the literature, as well as some who may to go on to apply these approaches in their own work.

Lying on the Dissection Table: Anatomizing Faked Responses

Research has shown that even experts cannot detect faking above chance, but recent studies have suggested that machine learning may help in this endeavor. However, faking differs between faking conditions, previous efforts have not taken these differences into account, and faking indices have yet to be integrated into such approaches. We reanalyzed seven data sets (N = 1,039) with various faking conditions (high and low scores, different constructs, naïve and informed faking, faking with and without practice, different measures [self-reports vs. implicit association tests; IATs]). We investigated the extent to which and how machine learning classifiers could detect faking under these conditions and compared different input data (response patterns, scores, faking indices) and different classifiers (logistic regression, random forest, XGBoost). We also explored the features that classifiers used for detection. Our results show that machine learning has the potential to detect faking, but detection success varies between conditions from chance levels to 100%. There were differences in detection (e.g., detecting low-score faking was better than detecting high-score faking). For self-reports, response patterns and scores were comparable with regard to faking detection, whereas for IATs, faking indices and response patterns were superior to scores. Logistic regression and random forest worked about equally well and outperformed XGBoost. In most cases, classifiers used more than one feature (faking occurred over different pathways), and the features varied in their relevance. Our research supports the assumption of different faking processes and explains why detecting faking is a complex endeavor.

Context-dependent amygdala-prefrontal connectivity during the dot-probe task varies by irritability and attention bias to angry faces

Irritability, defined as proneness to anger, is among the most common reasons youth are seen for psychiatric care. Youth with irritability demonstrate aberrant processing of anger-related stimuli; however, the neural mechanisms remain unknown. We applied a drift-diffusion model (DDM), a computational tool, to derive a latent behavioral metric of attentional bias to angry faces in youth with varying levels of irritability during functional magnetic resonance imaging (fMRI). We examined associations among irritability, task behavior using a DDM-based index for preferential allocation of attention to angry faces (i.e., extra-decisional time bias; Δt₀), and amygdala context-dependent connectivity during the dot-probe task. Our transdiagnostic sample, enriched for irritability, included 351 youth (ages 8-18; M = 12.92 years, 51% male, with primary diagnoses of either attention deficit/hyperactivity disorder [ADHD], disruptive mood dysregulation disorder [DMDD], an anxiety disorder, or healthy controls). Models accounted for age, sex, in-scanner motion, and co-occurring symptoms of anxiety. Youth and parents rated youth's irritability using the Affective Reactivity Index. An fMRI dot-probe task was used to assess attention orienting to angry faces. In the angry-incongruent vs. angry-congruent contrast, amygdala connectivity with the bilateral inferior frontal gyrus (IFG), insula, caudate, and thalamus/pulvinar was modulated by irritability level and attention bias to angry faces, Δt₀, all ts₃₅₀ > 4.46, ps < 0.001. In youth with high irritability, elevated Δt₀ was associated with a weaker amygdala connectivity. In contrast, in youth with low irritability, elevated Δt₀ was associated with stronger connectivity in those regions. No main effect emerged for irritability. As irritability is associated with reactive aggression, these results suggest a potential neural regulatory deficit in irritable youth who have elevated attention bias to angry cues.

Task cue influences on lexical decision performance and masked semantic priming effects: The role of cue-task compatibility

Recent research demonstrated that mere presentation of a task cue influences subsequent unconscious semantic priming by attentional sensitization of related processing pathways. The direction of this influence depended on task-set dominance. Dominant task sets with a compatible cue-task mapping were supposed to be rapidly suppressed, while weak task sets showed more sustainable activation. Building on this research, we manipulated cue-task compatibility as instance of task-set dominance in two experiments and tested how masked semantic priming was influenced by actually performing the cued task (induction-task trials) or by mere cue presentation (task cue-only trials). In induction-task trials, the results of earlier research were replicated; semantic priming was larger following a semantic induction task compared to a perceptual induction task. In task cue-only trials, priming effects were reversed compared to induction-task trials in both experiments. Priming was larger for a perceptual compared to a semantic task set in task cue-only trials, indicating suppression of task sets following mere cue presentation in preparation for the upcoming lexical decision task. This notion of an inhibition of task sets after mere cue presentation was further supported by switching-related costs and changes of task-set implementation throughout the experiment. The absence of a moderator role of cue-task compatibility for task cue effects on priming in the present study suggests that the precise time course of task-set activation and inhibition in response to task cues as a function of cue-task compatibility might depend on specific experimental settings.

Social norm learning from non-human agents can induce a persistent perceptual bias: A diffusion model approach

Seminal studies on social influence (Asch, 1956; Sherif, 1935) were based on face-to-face interactions between humans. Nowadays, computer-mediated communication is steadily becoming ubiquitous, and we are increasingly influenced by non-human agents, such as algorithms, robots, and chatbots. The present research aimed to answer two important questions: Can non-human agents exert social influence in a persistent manner and, thus, contribute to the emergence of social norms? And if this is the case, is social influence exerted by non-human agents mediated by the same or by different cognitive mechanisms as social influence exerted by human agents? To answer these questions, we used an online version of an established paradigm in research on social norm learning. To examine the cognitive underpinnings of social influence, we used a diffusion model approach. Our results provide strong evidence for the notion that non-human agents can induce persistent social influence outside an immediate group context and, hence, can contribute to the emergence of social norms. Furthermore, results from our diffusion model analyses support the notion that social influence exerted by non-human agents is mainly mediated by the same cognitive mechanisms as social influence exerted by human agents.

Ahead of the (ROC) Curve: A Statistical Approach to Utilizing Ex-Gaussian Parameters of Reaction Time in Diagnosing ADHD Across Three Developmental Periods

INTRODUCTION

Performance on executive function (EF) tasks is only modestly predictive of a diagnosis of Attention Deficit Hyperactivity Disorder (ADHD), despite the common assumption that EF deficits are ubiquitous to the disorder. The current study sought to determine whether ex-Gaussian parameters of simple reaction time are better able to discriminate between children and adults with and without ADHD, compared with traditional measures of inhibitory control.

METHODS

Receiver Operating Characteristic (ROC) analyses and the area under the curve (AUC) were used to examine the ability of performance on two commonly used tasks of inhibitory control (i.e. stop signal reaction time (SSRT) and go-no-go tasks) to predict ADHD status in preschool (N = 108), middle childhood (N = 309), and young adulthood (N = 133).

RESULTS

Across all samples, SSRT, go-no-go percentage of failed inhibits, and standard deviation of reaction (SDRT) time to "go" trials, all successfully discriminated between individuals with and without ADHD. Ex-Gaussian decomposition of the RT distribution indicated that both larger tau and larger sigma drove findings for SDRT. Contrary to predictions, traditional measures of inhibitory control were equal if not better predictors of ADHD status than ex-Gaussian parameters.

CONCLUSIONS

Findings support ongoing work to quantify the separate contributions of cognitive subprocesses that drive task performance, which in turn is critical to developing and improving process-based approaches in clinical assessment.

Unraveling the cognitive correlates of heart rate variability with the drift diffusion model

The Neurovisceral Integration Model posits a link between resting vagally mediated heart rate variability (vmHRV) and cognitive control. Empirical support for this link is mixed, potentially due to coarse performance metrics such as mean response time (RT). To clarify this issue, we tested the relationships between resting vmHRV and refined estimates of cognitive control- as revealed by the ex-Gaussian model of RT and, to a greater extent, the drift diffusion model (DDM, a computational model of two-choice performance). Participants (N = 174) completed a five-minute resting baseline while ECG was collected followed by a Simon spatial conflict task. The root mean square of successive differences in interbeat intervals was calculated to index resting vmHRV. Resting vmHRV was unrelated to Simon's mean RT and accuracy rates, but was inversely related to the ex-Gaussian parameter reflecting slow RTs (tau); however, this finding was attenuated after adjustment for covariates. High resting vmHRV was related to faster drift rates and slower non-decision times, DDM parameters reflecting goal-directed cognition and sensorimotor processes, respectively. The DDM effects survived covariate adjustment and were specific to incongruent trials (i.e., when cognitive control demands were high). Findings suggest a link between vmHRV and cognitive control vis-a-vis drift rate, and potentially, a link between vmHRV and motoric inhibition vis-a-vis non-decision time. These cognitive correlates would have been missed with reliance on traditional performance. Findings are discussed with respect to the inhibitory processes that promote effective performance in high vmHRV individuals.

People perception and stereotype-based responding: task context matters

Whether group impact social perception is a topic of renewed theoretical and empirical interest. In particular, it remains unclear when and how the composition of a group influences a core component of social cognition-stereotype-based responding. Accordingly, exploring this issue, here we investigated the extent to which different task requirements moderate the stereotype-related products of people perception. Following the presentation of same-sex groups that varied in facial typicality (i.e., high or low femininity/masculinity), participants had to report either the gender-related status of target words (i.e., a group-irrelevant gender-classification task) or whether the items were stereotypic or counter-stereotypic with respect to the preceding groups (i.e., a group-relevant stereotype-status task). Critically, facial typicality only impacted performance in the stereotype-status task. A further computational analysis (i.e., Diffusion Model) traced this effect to the combined operation of stimulus processing and response biases during decision-making. Specifically, evidence accumulation was faster when targets followed groups that were high (vs. low) in typicality and these arrays also triggered a stronger bias toward stereotypic (vs. counter-stereotypic) responses. Collectively, these findings elucidate when and how group variability influences people perception.