A drift-diffusion model of temporal generalization outperforms existing models and captures modality differences and learning effects

Decades of research show that people from adverse environments tend to score lower on cognitive tasks. These findings have been associated with deficits in various cognitive abilities, which has led to the proliferation of deficit models. These models emphasize the negative effects of chronic stress on social and cognitive development. More recently, research has started to focus on the ways in which adversity exposure may lead to adaptations specific cognitive abilities and strategies. Such adaptations could potentially lead to enhancements in abilities that are useful for solving the unique challenges posed by adverse environments, such as threat detection. A better integration of deficit and adaptation perspectives is important both for basic science and the development of interventions. Despite their importance, deficit and adaptation perspectives are not well-integrated. This dissertation argues that one reason for this might be that research from both perspectives tends to focus on raw performance measures, such as response times and accuracy. However, these measures have two important limitations. First, performance on EF tasks is not just influenced by specific EF abilities, but also by other cognitive processes, such as response caution. Second, performance on EF tasks is additionally influenced by general processes that shape performance across multiple cognitive tasks. These limitations hinder our understanding of how adversity shapes cognitive abilities. To address the first limitation, this dissertation uses Drift Diffusion Modeling (DDM). The DDM explains response times and accuracy on tasks that require binary decision-making as a combination of (1) the speed with which someone accumulates information (Drift rate), (2) the amount of information someone needs before making a decision (Boundary separation), and (3) the speed of non-decisional processes, such as stimulus encoding and respons execution (Non-decision time). By applying DDM to empirical task data, we can obtain participant-level estimates of these three cognitive processes. To address the second limitation, this dissertation uses structural equation modeling. This technique allows us to investigate the extent to which performance on EF tasks is shaped by task-specific processes versus task-general processes. This dissertation shows that adversity researchers may overestimate the association between adversity and specific EF abilities. We find that negative associations between adversity and drift rates are mostly driven by general processing speed. After correcting for general factors, we find little to no evidence for associations between adversity and specific EF abilities. Finally, we show that people with more adversity exposure sometimes use different strategies compared to people with less adversity exposure. These findings show that researchers should account for the fact that performance on EF tasks cannot be explained by specific EF abilities alone. Instead, they should tease apart the distinct cognitive processes that affect performance to better understand how adversity shapes cognitive development. Ideally, studies would include two or more tasks per EF ability in order to estimate abilities on a latent level. Cognitive modeling can be a valuable technique for the next generation of adversity researchers.

The evidence accumulation model is a widely used cognitive model of human decision-making, which assumes that decision-makers continuously gather and integrate information into evidence relevant to the decision and make a decision once the accumulated evidence reaches a predefined threshold. With the increasing popularity of evidence accumulation model, some researchers claim it has reached a theoretical plateau and can be considered as the standard model for analyzing response time and choices. However, the theoretical assumptions underlying these models lack rigorous testing. As an example, the drift-diffusion model (DDM) is an instantiation of evidence accumulation and has five underlying assumptions: (1) The universality of evidence accumulation; (2) the selectivity of evidence accumulation; (3) linear integration of evidence with noise; (4) a constant decision criterion; and (5) decision-making is independent of motor execution. DDM has been widely used in cognitive tasks, such as value-based decision-making, and social decision-making, probably due to the availability of user-friendly software for parameter estimation. However, only a few studies systematically examined to what extent these five assumptions of DDM were supported by empirical studies. To fill the gap, we reviewed studies that tested these five assumptions.For the first assumption of DDM, the universality of evidence accumulation, we only found direct evidence from studies that employed perceptual decision-making tasks. For other studies that used DDM for modeling, such as value-based decision-making or social decision-making, we found few studies that directly tested the existence of evidence accumulation. The second assumption, the selectivity of evidence accumulation, suggested that only information related to the goal would contribute to evidence accumulation. We did not find empirical data supporting this assumption except for O’Connell et al. However, evidence from conflict tasks (e.g., flanker task) suggested that information irrelevant to the goal may also be incorporated into the evidence accumulation. Data from conflict tasks inspired new models under evidence accumulation model and called for further investigation into the mechanism related to the selectivity of evidence. The third and fourth assumptions constitute the core assumptions of DDM, i.e., “evidence accumulate-to-bound”. Regarding the third assumption, which posits that evidence with noise is accumulated linearly, supporting data were found from animal studies and human EEG studies that employed perceptual decision-making. However, human EEG data from value-based decision-making tasks has challenged the validity of this assumption. The fourth assumption, that the decision criterion is constant, is controversial and has been challenged by several other evidence accumulation models, such as collapsing boundary models. The last assumption, that decision-making is independent of motor execution, has also been questioned by empirical data from both animal studies and human behavioral and electromyography data, despite support from EEG recording.In summary, we found that, while the standard DDM is commonly used in many sub-fields of psychology and neuroscience, empirical studies that directly tested five assumptions of DDM were mainly from perceptual decision-making tasks. Also, we found that challenging these assumptions often resulted in new computational models. These findings call for studies to test these assumptions and develop new models. Besides these findings suggest that researchers should be cautious when interpreting the parameters estimated from standard DDM. Finally, our review suggests that increasing transparency in model assumptions will accelerate the revision of models and theories, and ultimately deepen our understanding of human cognitive processes.

BackgroundToward establishing behavioral biomarkers of dementia, clinical studies have shown promising results for differentiating patient groups by mathematically modeling their decision‐making processes during task performance (O’Callaghan et al., 2021; Ratcliff et al., 2022). The aim of our preclinical study was to include decision‐based modeling into the behavioral analysis of a prodromal rat model of Alzheimer’s disease (AD); an approach that we predicted would reveal genotype‐ and sex‐specific behavioral effects that were not evident in the standard assessments of task performance.MethodMale/female wildtype and transgenic Fischer 344 rats (TgAPP, which over‐express pathogenic human amyloid precursor protein, but do not spontaneously develop β‐amyloid plaques) performed a two‐alternative forced‐choice task to visually discriminate a steady versus flashing light cue. In addition to measuring performance accuracy, the rats’ reaction times were fit using an ExGauss function to assess the variability of the distribution; an important metric because increased reaction time variability is linked to age‐related cognitive decline in humans. Consistent with past studies on dementia patients, the rats’ decision‐making processes were analyzed using a drift diffusion model (DDM), which computed their rate of evidence accumulation (drift), their threshold to make decisions (bounds), as well as their initial sensory processing and final motor execution (non‐decision time).ResultBoth male and female TgAPP rats performed the visual discrimination task at a modestly lower percent accuracy compared to wildtypes; however, only the female TgAPP rats showed slower reaction times, including increased variability in their timing to make decisions. Extending these genotype‐ and sex‐specific results, the DDM analysis revealed (1) slower evidence accumulation in both TgAPP sexes; (2) increased decision‐making thresholds in females compared to males, suggestive of increased response caution, and; (3) increased non‐decision times only in the TgAPP female rats.ConclusionWe show that DDM is a useful tool for revealing changes in cognitive function in a prodromal animal model of AD that were otherwise not evident using standard task metrics. Ultimately, by combining this computational approach with other biomarkers (e.g. molecular; neurophysiological), we can enhance our understanding of the earliest stages of disease progression and improve the translational potential of preclinical research.

Crowdsourcing involves the use of annotated labels with unknown reliability to estimate ground truth labels in datasets. A common task in crowdsourcing involves estimating reliabilities of annotators (such as through the sensitivities and specificities of annotators in the binary label setting). In the literature, beta or dirichlet distributions are typically imposed as priors on annotator reliability. In this study, we investigated the use of a neuroscientifically validated model of decision making, known as the drift-diffusion model, as a prior on the annotator labeling process. Two experiments were conducted on synthetically generated data with non-linear (sinusoidal) decision boundaries. Variational inference was used to predict ground truth labels and annotator related parameters. Our method performed similarly to a state-of-the-art technique (SVGPCR) in prediction of crowdsourced data labels and prediction through a crowdsourced-generated Gaussian process classifier. By relying on a neuroscientifically validated model of decision making to model annotator behavior, our technique opens the avenue of predicting neuroscientific biomarkers of annotators, expanding the scope of what may be learnt about annotators in crowdsourcing tasks.

Children aged 5 and 8 years and adults were tested on a temporal generalization task with a standard duration of 600 ms in a condition with or without corrective feedback. In all conditions, the participants produced orderly temporal generalization gradients, although these were flatter in the younger children, especially in the no-feedback condition. Nevertheless, the results show that the feedback increased the steepness of the generalization gradient in all age groups and in a greater extent in the younger children. Our clock-based model suggested that feedback reduces the variability of the memory representation of the standard duration but also the probability of random responses in the 5-year-olds.

Performance in an escape task induces fos-like immunoreactivity in a specific area of the motor cortex of the rat

Chapter 100 - Concurrent fNIRS and TMS for Neurocognitive Enhancement on a Speed-of-Processing Task

This study investigated the effect of forgetting of the standard duration on temporal discrimination in a generalization task. In two experiments, participants were given a temporal generalization task with or without a retention delay between the learning of the standard duration and the testing of the comparison durations. During this delay, they either performed or did not perform an interference task. Results failed to reveal any effect of 15-min and 24-h retention delays on time judgments (Experiment 1). However, when an interference task was performed during the 15-min delay (Experiment 2), there was a subjective shortening effect, indicating that the standard duration was judged shorter with than without an interference task. These findings suggest that when an interference task occurs immediately after initial temporal encoding, it affects the process of consolidation in reference memory.

Models of gambling disorder, along with other addiction-related conditions, identify impulsive traits as a key component to developing challenging behaviors. This is supported by empirical findings indicating that individuals with gambling disorder exhibit poorer response inhibition, a facet of impulsivity. However, studies on individual differences in inhibition often find weak correlations between different inhibition tasks, suggesting that cognitive processes other than a general inhibitory control ability may contribute to task performance, and by extension, to gambling. The current study applied cognitive modeling to dissociate the cognitive processes involved in response inhibition tasks and examined which cognitive processes are predictive of gambling severity. A total of 422 participants completed the Stroop, Go/No-go and Stop-Signal tasks alongside the Problem Gambling Severity Index (PGSI) questionnaire. The drift diffusion model was used to decompose traditional task performance data into parameters which were then grouped into four distinct cognitive processes: inhibitory control, general processing speed, response caution, and perceptual/motor speed. Preregistered regression analyses indicate that lower caution, rather than inhibition, is associated with higher gambling severity. Whereas previous research had focused on inhibitory control as a risk factor for gambling behaviors, as well as a target for potential interventions (e.g. training apps), these findings suggest rather that the strategic processes underlying decision making – caution – are important to consider.

Acquisition of a behavioral task is influenced by many factors. The relative timing of stimuli is such a factor and is especially relevant for tasks relying on short-term memory, like working memory paradigms, because of the constant evolution and decay of neuronal activity evoked by stimuli. Here, we assess two aspects of stimulus timing on the acquisition of an olfactory delayed nonmatch-to-sample (DNMS) task. We demonstrate that head-fixed male mice learn to perform the task more quickly when the initial training uses a shorter sample-test odor delay without detectable loss of generalizability. Unexpectedly, we observed a slower task acquisition when the odor–reward interval was shorter. The effect of early reward timing was accompanied by a shortening of reaction times and more frequent sporadic licking. Analysis of this result using a drift-diffusion model indicated that a primary consequence of early reward delivery is a lowered threshold to act, or a lower decision bound. Because an accurate performance with a lower decision bound requires greater discriminability in the sensory representations, this may underlie the slower learning rate with early reward arrival. Together, our results reflect the possible effects of stimulus timing on stimulus encoding and its consequence on the acquisition of a complex task.SIGNIFICANCE STATEMENT This study describes how head-fixed mice acquire a working memory task (olfactory delayed nonmatch-to-sample task). We simplified and optimized the stimulus timing, allowing robust and efficient training of head-fixed mice. Unexpectedly, we found that early reward timing leads to slower learning. Analysis of this data using a computational model (drift-diffusion model) revealed that the reward timing affects the behavioral threshold, or how quickly animals respond to a stimulus. But, to still be accurate with early reaction times, the sensory representation needs to become even more refined. This may explain the slower learning rate with early reward timing.

Pigs in modern farming practice may be exposed to a number of stressors, including social stressors such as mixing or isolation. This may potentially affect both cognitive abilities and stress physiology of the animals. We tested the hypothesis that overnight social isolation in pigs impairs performance in a cognitive holeboard (HB) task (Experiment 1) and the Pig Gambling Task (PGT) (Experiment 2), a decision-making task inspired by the Iowa Gambling Task. In addition, we tested the effect of overnight social isolation on salivary cortisol levels. A within-subjects approach was used in which performance in the two behavioral tasks and cortisol levels were first determined during normal social housing, followed by performance and cortisol levels after experiencing stress induced by overnight social isolation. A total of 19 female pigs with a birth weight closest to their respective litter average was selected from 10 different litters and placed in two pens after weaning. Following habituation, pigs were trained in the HB task, starting at 10 weeks of age. Then, the pigs were isolated overnight, five individuals per night, at 15, 16, and 17 weeks of age. Between these three isolations, social housing and training in the HB continued. Starting 6 weeks after the end of the HB experiment, at approximately 23 weeks of age, the pigs were trained in the PGT. The effects of overnight social isolation on performance in this task were assessed once, when the pigs were 25 weeks old. Salivary cortisol was measured from samples collected 15 min after the start of isolation and at the end of the isolation period and compared to baseline values collected before the start of social isolation. Our results did not confirm the hypothesis that isolation impaired HB performance and decision-making in the PGT. Unexpectedly, overnight social isolation decreased cortisol levels below baseline values, an effect that was not associated with changes in performance of the behavioral tasks. We hypothesized that the housing and testing conditions may have prepared the animals to cope efficiently with stress.

When producing creative ideas (i.e., ideas that are original and useful) two main processes occur: ideation, where people brainstorm ideas, and evaluation, where they decide if the ideas are creative or not. While much is known about the ideation phase, the cognitive processes involved in creativity evaluation are less clear. In this article, we present a novel modeling approach for the evaluation phase of creativity. We apply the drift diffusion model (DDM) to the Creative-or-Not task (CON-task) to study the cognitive basis of evaluation and to examine individual differences in the extent to which people take originality and utility into account when evaluating creative ideas. The CON-task is a timed decision-making task where participants indicate whether they find uses for certain objects creative or not (e.g., using a book as a buoy). The different uses vary on the two creativity dimensions "originality" and "utility." In two studies (n = 293, 17,806 trials; n = 152, 9,291 trials), we found that stimulus originality was strongly related to participants' drift rates but found only weak evidence for an association between stimulus utility and the drift rate. However, participants differed substantially in the effects of originality and utility. Furthermore, the implicit weights assigned to originality and utility on the CON-task were associated with self-reported importance ratings of originality and utility and with divergent thinking performance in the Alternative Uses task (AUT). This research provides a cognitive modeling approach to creativity evaluation and underlines the importance of communicating rating criteria in divergent thinking tasks to ensure a fair assessment of creative ability. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Problematic short-form video users (PSVU) usually exhibit deficits in inhibitory control, which has been attributed to an imbalance between the goal-directed and habitual systems. However, the cognitive processes underlying this association remain unclear. From an information-processing perspective, this study employed the drift–diffusion model (DDM) to examine the link between inhibitory control deficits and a dual-system imbalance in PSVU. Thirty PSVU and twenty-eight matched controls completed a go/no-go task and a contingency degradation task. DDM was applied to model latent information-processing mechanisms from go/no-go performance. Habitual tendencies were assessed using ratio scores across contingency degradation conditions. Compared with healthy counterparts, PSVU showed a higher false-alarm rate and lower boundary separation in the go/no-go task. No significant group differences were found in other DDM parameters. In the contingency degradation task, PSVU showed a stubborn ratio score during action-outcome congruence transitions, which correlated positively with the boundary separation index. These findings suggest that, rather than abnormal information accumulation processes or response bias, inhibitory control deficits in PSVU arise from a more impulsive decision-making pattern, associated with insensitivity to task-setting changes. The study provided novel implications for intervention in behavioral addictions.

Many previous studies on visual search have reported inter-trial effects, that is, observers respond faster when some target property, such as a defining feature or dimension, or the response associated with the target repeats versus changes across consecutive trial episodes. However, what processes drive these inter-trial effects is still controversial. Here, we investigated this question using a combination of Bayesian modeling of belief updating and evidence accumulation modeling in perceptual decision-making. In three visual singleton (‘pop-out’) search experiments, we explored how the probability of the response-critical states of the search display (e.g., target presence/absence) and the repetition/switch of the target-defining dimension (color/ orientation) affect reaction time distributions. The results replicated the mean reaction time (RT) inter-trial and dimension repetition/switch effects that have been reported in previous studies. Going beyond this, to uncover the underlying mechanisms, we used the Drift-Diffusion Model (DDM) and the Linear Approach to Threshold with Ergodic Rate (LATER) model to explain the RT distributions in terms of decision bias (starting point) and information processing speed (evidence accumulation rate). We further investigated how these different aspects of the decision-making process are affected by different properties of stimulus history, giving rise to dissociable inter-trial effects. We approached this question by (i) combining each perceptual decision making model (DDM or LATER) with different updating models, each specifying a plausible rule for updating of either the starting point or the rate, based on stimulus history, and (ii) comparing every possible combination of trial-wise updating mechanism and perceptual decision model in a factorial model comparison. Consistently across experiments, we found that the (recent) history of the response-critical property influences the initial decision bias, while repetition/switch of the target-defining dimension affects the accumulation rate, likely reflecting an implicit ‘top-down’ modulation process. This provides strong evidence of a disassociation between response- and dimension-based inter-trial effects.

It has been proposed that accuracy in time perception is related to interoceptive accuracy and vagal activity. However, studies investigating time perception in the supra-second range have provided mixed results, and few studies have investigated the sub-second range. Moreover, there is a lack of studies investigating the relationship between precision in time perception and interoceptive accuracy. A recent meta-analytic review of neuroimaging studies proposed a dynamic interaction between two types of timing processing—an endogenous time keeping mechanism and the use of exogenous temporal cues. Interoceptive accuracy may affect both accuracy and precision of primary temporal representations, as they are generated based on the endogenous time keeping mechanism. Temporal accuracy may vary when adapted to the environmental context. In contrast, temporal precision contains some constant noise, which may maintain the relationship with interoceptive accuracy. Based on these assumptions, we hypothesized that interoceptive accuracy would be associated with temporal precision in the sub-second range, while vagal activity would be associated with temporal accuracy. We used the temporal generalization task, which allowed us to calculate the indices of temporal accuracy and temporal precision in line with the existing research, and also compute the index of participants’ sensitivity according to the signal detection theory. Specifically, we investigated whether (1) interoceptive accuracy would correlate with temporal accuracy, temporal precision, or sensitivity and (2) resting-state vagal activity would correlate with temporal accuracy, temporal precision, or sensitivity. The results indicated that interoceptive accuracy was positively correlated with temporal precision as well as sensitivity, but not with temporal accuracy, in the sub-second range time perception. Vagal activity was negatively correlated only with sensitivity. Furthermore, we found a moderation effect of sensitivity on the relationship between vagal activity and perceived duration, which affected the association between vagal activity and temporal accuracy. These findings suggest the importance of precision as an aspect of time perception, which future studies should further explore in relation to interoception and vagal activity, and of the moderation effects of factors such as participants’ sensitivity in this context.