Drift Rate Parameter Research Articles

Psychometrics of drift-diffusion model parameters derived from the Eriksen flanker task: Reliability and validity in two independent samples.

The flanker task is a widely used measure of cognitive control abilities. Drift-diffusion modeling of flanker task behavior can yield separable parameters of cognitive control-related subprocesses, but the parameters' psychometrics are not well-established. We examined the reliability and validity of four behavioral measures: (1) raw accuracy, (2) reaction time (RT) interference, (3) NIH Toolbox flanker score, and (4) two drift-diffusion model (DDM) parameters-drift rate and boundary separation-capturing evidence accumulation efficiency and speed-accuracy trade-off, respectively. Participants from two independent studies - one cross-sectional (N = 381) and one with three timepoints (N = 83) - completed the flanker task while electroencephalography data were collected. Across both studies, drift rate and boundary separation demonstrated comparable split-half and test-retest reliability to accuracy, RT interference, and NIH Toolbox flanker score, but better incremental convergent validity with psychophysiological measures (i.e., the error-related negativity; ERN) and neuropsychological measures of cognitive control than the other behavioral indices. Greater drift rate (i.e., faster and more accurate responses) to congruent and incongruent stimuli, and smaller boundary separation to incongruent stimuli were related to 1) larger ERN amplitudes (in both studies) and 2) faster and more accurate inhibition and set-shifting over and above raw accuracy, reaction time, and NIH Toolbox flanker scores (in Study 1). Computational models, such as DDM, can parse behavioral performance into subprocesses that exhibit comparable reliability to other scoring approaches, but more meaningful relationships with other measures of cognitive control. The application of these computational models may be applied to existing data and enhance the identification of cognitive control deficits in psychiatric disorders.

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.

Reliability and Validity of Ecological Momentary Assessment Response Time-Based Measures of Emotional Clarity: Secondary Data Analysis.

Emotional clarity has often been assessed with self-report measures, but efforts have also been made to measure it passively, which has advantages such as avoiding potential inaccuracy in responses stemming from social desirability bias or poor insight into emotional clarity. Response times (RTs) to emotion items administered in ecological momentary assessments (EMAs) may be an indirect indicator of emotional clarity. Another proposed indicator is the drift rate parameter, which assumes that, aside from how fast a person responds to emotion items, the measurement of emotional clarity also requires the consideration of how careful participants were in providing responses. This paper aims to examine the reliability and validity of RTs and drift rate parameters from EMA emotion items as indicators of individual differences in emotional clarity. Secondary data analysis was conducted on data from 196 adults with type 1 diabetes who completed a 2-week EMA study involving the completion of 5 to 6 surveys daily. If lower RTs and higher drift rates (from EMA emotion items) were indicators of emotional clarity, we hypothesized that greater levels (ie, higher clarity) should be associated with greater life satisfaction; lower levels of neuroticism, depression, anxiety, and diabetes distress; and fewer difficulties with emotion regulation. Because prior literature suggested emotional clarity could be valence specific, EMA items for negative affect (NA) and positive affect were examined separately. Reliability of the proposed indicators of emotional clarity was acceptable with a small number of EMA prompts (ie, 4 to 7 prompts in total or 1 to 2 days of EMA surveys). Consistent with expectations, the average drift rate of NA items across multiple EMAs had expected associations with other measures, such as correlations of r=-0.27 (P<.001) with depression symptoms, r=-0.27 (P=.001) with anxiety symptoms, r=-0.15 (P=.03) with emotion regulation difficulties, and r=0.63 (P<.001) with RTs to NA items. People with a higher NA drift rate responded faster to NA emotion items, had greater subjective well-being (eg, fewer depression symptoms), and had fewer difficulties with overall emotion regulation, which are all aligned with the expectation for an emotional clarity measure. Contrary to expectations, the validities of average RTs to NA items, the drift rate of positive affect items, and RTs to positive affect items were not strongly supported by our results. Study findings provided initial support for the validity of NA drift rate as an indicator of emotional clarity but not for that of other RT-based clarity measures. Evidence was preliminary because the sample size was not sufficient to detect small but potentially meaningful correlations, as the sample size of the diabetes EMA study was chosen for other more primary research questions. Further research on passive emotional clarity measures is needed.

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.

Error modulates categorization of subsecond durations in multitasking contexts.

Monitoring errors consumes limited cognitive resources and can disrupt subsequent task performance in multitasking scenarios. However, there is a dearth of empirical evidence concerning this interference with prospective estimation of time. In this study, we sought to investigate this issue through a serial multitasking experiment, employing a temporal bisection task as the primary task. We introduced two task contexts by implementing two different concurrent tasks. In one context, participants were tasked with discriminating the size difference between two visual items, while in the other context, they were required to judge the temporal order of similar visual items. The primary task remained the same for the entire experiment. Psychophysical metrics, including subjective bias (determined by the bisection point) and temporal sensitivity (measured by the Weber ratio), in addition to reaction time, remained unaltered in the primary task regardless of the perceptual context exerted by the concurrent tasks. However, commission of error in the concurrent tasks (i.e., non-specific errors) led to a right-ward shift in the bisection point, indicating underestimation of time after errors. Applying a drift-diffusion framework for temporal decision making, we observed alterations in the starting point and drift rate parameters, supporting the error-induced underestimation of time. The error-induced effects were all diminished with increasing a delay between the primary and concurrent task, indicating an adaptive response to errors at a trial level. Furthermore, the error-induced shift in the bisection point was diminished in the second half of the experiment, probably because of a decline in error significance and subsequent monitoring response. These findings indicate that non-specific errors impact the prospective estimation of time in multitasking scenarios, yet their effects can be alleviated through both local and global reallocation of cognitive resources from error processing to time processing.

Using a Drift Diffusion Model to Validate the Quantification of Style Prototypicality as Assessed by the Viewers of Paintings

Abstract When appreciating a painting, people often classify it into a style. The extent to which the painting is regarded as a typical example of the style is called its style prototypicality. The authors propose a method of quantifying style prototypicalities and conduct an experiment to validate this method using the drift rate parameter of the drift diffusion model. This parameter is calculated using participants’ decision-making response times. The authors find a positive correlation (r = .88, p &amp;lt; .001) between the drift rates and the quantified prototypicalities for the paintings used in this study, confirming the psychological appropriateness of the proposed quantification method.

Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-making.

Perceptual decisions about sensory input are influenced by fluctuations in ongoing neural activity, most prominently driven by attention and neuromodulator systems. It is currently unknown if neuromodulator activity and attention differentially modulate perceptual decision-making and/or whether neuromodulatory systems in fact control attentional processes. To investigate the effects of two distinct neuromodulatory systems and spatial attention on perceptual decisions, we pharmacologically elevated cholinergic (through donepezil) and catecholaminergic (through atomoxetine) levels in humans performing a visuo-spatial attention task, while we measured electroencephalography (EEG). Both attention and catecholaminergic enhancement improved decision-making at the behavioral and algorithmic level, as reflected in increased perceptual sensitivity and the modulation of the drift rate parameter derived from drift diffusion modeling. Univariate analyses of EEG data time-locked to the attentional cue, the target stimulus, and the motor response further revealed that attention and catecholaminergic enhancement both modulated pre-stimulus cortical excitability, cue- and stimulus-evoked sensory activity, as well as parietal evidence accumulation signals. Interestingly, we observed both similar, unique, and interactive effects of attention and catecholaminergic neuromodulation on these behavioral, algorithmic, and neural markers of the decision-making process. Thereby, this study reveals an intricate relationship between attentional and catecholaminergic systems and advances our understanding about how these systems jointly shape various stages of perceptual decision-making.

Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-making

Perceptual decisions about sensory input are influenced by fluctuations in ongoing neural activity, most prominently driven by attention and neuromodulator systems. It is currently unknown if neuromodulator activity and attention differentially modulate perceptual decision-making and/or whether neuromodulatory systems in fact control attentional processes. To investigate the effects of two distinct neuromodulatory systems and spatial attention on perceptual decisions, we pharmacologically elevated cholinergic (through donepezil) and catecholaminergic (through atomoxetine) levels in humans performing a visuo-spatial attention task, while we measured electroencephalography (EEG). Both attention and catecholaminergic enhancement improved decision-making at the behavioral and algorithmic level, as reflected in increased perceptual sensitivity and the modulation of the drift rate parameter derived from drift diffusion modeling. Univariate analyses of EEG data time-locked to the attentional cue, the target stimulus, and the motor response further revealed that attention and catecholaminergic enhancement both modulated pre-stimulus cortical excitability, cue- and stimulus-evoked sensory activity, as well as parietal evidence accumulation signals. Interestingly, we observed both similar, unique, and interactive effects of attention and catecholaminergic neuromodulation on these behavioral, algorithmic, and neural markers of the decision-making process. Thereby, this study reveals an intricate relationship between attentional and catecholaminergic systems and advances our understanding about how these systems jointly shape various stages of perceptual decision-making.

41 Adaptive Implementation of Cognitive Control in School-Aged Children with ADHD: A Diffusion-Model Analysis

Objective:Because cognitive resources are limited, models of cognitive control predict that additional control is engaged only if it improves task performance. Increased response caution, which occurs when individuals increase the threshold of information needed before making a decision, is one example of cognitive control adaptation. While previous studies have measured increased response caution via increased reaction time, the diffusion model can be used to derive a boundary separation parameter that directly indexes response caution and eliminates capturing alternative influences on reaction time. This study aims to determine if school-aged children, either with or without ADHD, show adaptive changes in response caution during a set-shifting task. These groups have demonstrated mixed results when analyzing reaction time, so this study utilizes diffusion modeling to measure response caution more directly. The set-shifting task presents switches in a random order such that they cannot be predicted; therefore, increasing response caution is only adaptive following errors, called post-error slowing (PES), but not following switch trials. It is predicted that children will show increased response caution only when adaptive. If child with ADHD adapt their response caution fundamentally differently, then there will be individual differences in change in boundary separation.Participants and Methods:Children ages 8-12 with (n=193) and without (n=70) ADHD completed the Navon set-shifting task. Participants saw one of four global shapes made up of local shapes and were asked to identify one or the other based upon the background color. Of the 144 trials, 70 presented a switch between global and local. Trials were presented in the same randomized order for all participants, self-paced, and followed by feedback on correctness. The diffusion model parameters boundary separation (a), drift rate (v), and nondecision time (Ter) were estimated by condition, including a) post-error versus after correct and b) post-switch versus post-same. For PES analyses, only participants with a sufficient number of errors for modeling were included (ADHD n=113, control n=19).Results:Participants were slower on trials immediately following errors (F(1, 130)=119.76, p&lt;.001, n2=.48) and switches (F(1, 261)=154.93, p&lt;.001, n2=.37). In PES, slowing was attributable to increased boundary separation, F(1, 130)=16.11, p&lt;.001, n2=.11, as well as slower drift rate and longer nondecision time (both p&lt;.01, n2 &gt;.05). However, as predicted, post-switch slowing was only attributable slower drift rate and longer nondecision time (both p&lt;.001, n2 &gt;.10), not increased boundary separation, F(1, 261)=0.77, p=.38, n2&lt;.01. Overall, children with ADHD had slower drift rates (F(1, 261)=4.63, p&lt;.001, n2=.10) and narrower boundary separation (F(1, 261)=10.56, p=.001, n2=.04). However, there were no ADHD x trial-type interactions for PES or post-switch (both p&gt;.33, n2&lt;.01).Conclusions:School-aged children demonstrated increased response caution following errors, but not following switches. This demonstrates an adaptive use of cognitive control. The diffusion model was crucial in determining this, as reaction time slowed following switches for reasons unrelated to cognitive control. Additionally, although children with ADHD demonstrated slower drift rates and narrower boundary separation overall, they showed no differences when adapting response caution.

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.

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-modulated Sensitivity to Vocal Pitch in the Dorsal Premotor Cortex during Multitalker Speech Recognition.

It has long been known that listening to speech activates inferior frontal (pre-)motor regions in addition to a more dorsal premotor site (dPM). Recent work shows that dPM, located adjacent to laryngeal motor cortex, responds to low-level acoustic speech cues including vocal pitch, and the speech envelope, in addition to higher-level cues such as phoneme categories. An emerging hypothesis is that dPM is part of a general auditory-guided laryngeal control circuit that plays a role in producing speech and other voluntary auditory-vocal behaviors. We recently reported a study in which dPM responded to vocal pitch during a degraded speech recognition task, but only when speech was rated as unintelligible; dPM was more robustly modulated by the categorical difference between intelligible and unintelligible speech. Contrary to the general auditory-vocal hypothesis, this suggests intelligible speech is the primary driver of dPM. However, the same pattern of results was observed in pitch-sensitive auditory cortex. Crucially, vocal pitch was not relevant to the intelligibility judgment task, which may have facilitated processing of phonetic information at the expense of vocal pitch cues. The present fMRI study (n = 25) tests the hypothesis that, for a multitalker task that emphasizes pitch for talker segregation, left dPM and pitch-sensitive auditory regions will respond to vocal pitch regardless of overall speech intelligibility. This would suggest that pitch processing is indeed a primary concern of this circuit, apparent during perception only when the task demands it. Spectrotemporal modulation distortion was used to independently modulate vocal pitch and phonetic content in two-talker (male/female) utterances across two conditions (Competing, Unison), only one of which required pitch-based segregation (Competing). A Bayesian hierarchical drift-diffusion model was used to predict speech recognition performance from patterns of spectrotemporal distortion imposed on each trial. The model's drift rate parameter, a d'-like measure of performance, was strongly associated with vocal pitch for Competing but not Unison. Using a second Bayesian hierarchical model, we identified regions where behaviorally relevant acoustic features were related to fMRI activation in dPM. We regressed the hierarchical drift-diffusion model's posterior predictions of trial-wise drift rate, reflecting the relative presence or absence of behaviorally relevant acoustic features from trial to trial, against trial-wise activation amplitude. A significant positive association with overall drift rate, reflecting vocal pitch and phonetic cues related to overall intelligibility, was observed in left dPM and bilateral auditory cortex in both conditions. A significant positive association with "pitch-restricted" drift rate, reflecting only the relative presence or absence of behaviorally relevant pitch cues, regardless of the presence or absence of phonetic content (intelligibility), was observed in left dPM, but only in the Competing condition. Interestingly, the same effect was observed in bilateral auditory cortex but in both conditions. A post hoc mediation analysis ruled out the possibility that decision load was responsible for the observed pitch effects. These findings suggest that processing of vocal pitch is a primary concern of the auditory-cortex-dPM circuit, although during perception core pitch, processing is carried out by auditory cortex with a potential modulatory influence from dPM.

Mutual interference in working memory updating: A hierarchical Bayesian model

We propose a hierarchical Bayesian model for working memory updating. This model accounts for both the accuracy of the responses and the reaction times (RT) in the memory updating paradigm, which is a commonly used paradigm to measure working memory capacity. We adapt a mutual interference model from Oberauer and Kliegl (2006) to explain responses. Oberauer and Kliegl (2006) used a Boltzmann equation framework based on the activation levels of items stored in working memory to quantify the probability of correct response at the final recall step after memory updating. We expand the original framework with a Markov chain structure, so that the model accounts for the probabilities of all possible responses, correct or incorrect, at both the intermediate steps during memory updating and the final recall step after memory updating. We use a Wald diffusion process to characterize RT, where the drift rate parameters are associated with the activation levels of items in working memory. This model allows us to investigate the mechanisms underlying choices and RTs in the memory updating paradigm under a joint theoretical framework. A simulation study shows the effectiveness of this model, and posterior predictive distributions and out-of-sample validations show that this model gives a good account of empirical working memory updating findings. We apply the model to two published data sets. The first data set, from Oberauer and Kliegl (2001), examined age differences in working memory. Results from our model reveal an increased level of mutual interference, less use of memory trace information, and potentially less pre-activation of memorized items in older adults compared to younger adults. The second data set, from De Simoni and von Bastian (2018), investigated transfer effects of working memory training. Results from our model reveal a potential transfer effect in the speed of information accumulation, where training in one working memory task may improve the information processing speed in another.

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.

Motor speed does not impact the drift rate: a computational HDDM approach to differentiate cognitive and motor speed

The drift diffusion model (DDM) is a widely applied computational model of decision making that allows differentiation between latent cognitive and residual processes. One main assumption of the DDM that has undergone little empirical testing is the level of independence between cognitive and motor responses. If true, widespread incorporation of DDM estimation into applied and clinical settings could ease assessment of whether response disruption occurs due to cognitive or motor slowing. Across two experiments, we manipulated response force (motor speed) and set size to evaluate whether drift rates are independent of motor slowing or if motor slowing impacts the drift rate parameter. The hierarchical Bayesian drift diffusion model was used to quantify parameter estimates of drift rate, boundary separation, and non-decision time. Model comparison revealed changes in set size impacted the drift rate while changes in response force did not impact the drift rate, validating independence between drift rates and motor speed. Convergent validity between parameter estimates and traditional assessments of processing speed and motor function were weak or absent. Widespread application, including neurocognitive assessment where confounded changes in cognitive and motor slowing are pervasive, may provide a more process-pure measurement of information processing speed, leading to advanced disease-symptom management.

Incentive motivation improves numerosity discrimination in children and adolescents

We recently showed that incentive motivation improves the precision of the Approximate Number System (ANS) in young adults. To shed light on the development of incentive motivation, the present study investigated whether this effect and its underlying mechanisms may also be observed in younger samples. Specifically, seven-year-old children (n = 23; 12 girls) and 14-year-old adolescents (n = 30; 15 girls) performed a dot comparison task with monetary reward incentives. Both age groups showed higher accuracy in a reward compared to a neutral condition and, similarly, higher processing efficiency as revealed by the drift rate parameter of the EZ-diffusion model. Furthermore, in line with the Incentive Salience Hypothesis, phasic pupil dilations—indicating the activation of the brain’s salience network—were greater in incentivized trials in both age groups. Together these finding suggest that incentive modulation improves numerosity discrimination in children and adolescents by enhancing the perceptual saliency of numerosity information. However, the observed reward anticipation effects were less pronounced in children relative to adolescents. Furthermore, unlike previous findings regarding young adults, the decision thresholds of children and adolescents were not raised by the monetary reward, which may indicate a more protracted development of incentive regulation of response caution than perceptual evidence accumulation.

Reciprocal associations between implicit attitudes and drinking in emerging adulthood.

Implicit alcohol attitudes are considered important in the etiology of drinking, and theory posits reciprocal associations between them. Research testing reciprocal associations between implicit attitudes (using the Implicit Association Task, IAT) and drinking is limited by a failure to consider multiple processes influencing performance on the IAT and to disaggregate within- and between-person effects. The current study addressed these limitations by using a diffusion model to analyze IAT data and Latent Curve Models with Structured Residuals to test reciprocal associations. The sample included 314 emerging adults from the community (52% female; predominantly non-Hispanic Caucasian (76%) or African American (15%)) assessed annually for three years. Differences between IAT conditions in the drift rate parameter of the EZ-diffusion model (vΔ) were used as an alternative to traditional response-time-based indices from the IAT (d-scores). Differences in drift rate have been found to index implicit attitudes effectively. Within-person reciprocal associations were supported, but between-person associations were not. Positive implicit alcohol attitudes (vΔ) were prospectively associated with heavy drinking, which was positively associated with subsequent positive implicit alcohol attitudes. We found that positive implicit alcohol attitudes and heavy drinking reinforce each other in a negative cascade within individuals. The results highlight the importance of disaggregating within- and between-person prospective effects when testing dual process models and suggest that the diffusion model may be a fruitful approach to enhance the construct validity of IAT assessed implicit attitudes.

Cognitive efficiency beats top-down control as a reliable individual difference dimension relevant to self-control

Top-down control of responses is a key construct in cognitive science that is thought to be critical for self-control. It is typically measured by subtracting performance in experimental conditions in which top-down control is theoretically present against performance in matched conditions in which it is assumed to be absent. Recently, however, subtraction-based metrics of top-down control have been criticized for having low test-retest reliability, weak intercorrelations, and little relation to self-report measures of self-control. Concurrently, there is growing evidence that task-general cognitive efficiency, indexed by the drift rate parameter of the diffusion model (Ratcliff, 1978), constitutes a cohesive, reliable individual difference dimension relevant to self-control. However, no previous studies have directly compared latent factors for top-down control (derived from subtraction metrics) with factors for task-general efficiency “head-to-head” in the same sample in terms of their cohesiveness, temporal stability, and relation to self-control. In this re-analysis of a large open data set (Eisenberg et al., 2019; N = 522), we find that top-down control metrics fail to form cohesive latent factors, that the resulting factors have poor temporal stability, and that they exhibit tenuous connections to questionnaire measures of self-control. In contrast, cognitive efficiency measures—drawn from conditions of the same tasks that both are, and are not, assumed to demand top-down control—form a robust, temporally stable factor that correlates with questionnaire measures of self-control. These findings suggest that task-general efficiency is a central individual difference dimension relevant to self-control. Moreover, they go beyond recent measurement-based critiques of top-down control metrics, and instead suggest problems with key theoretical assumptions that have long guided this research paradigm.

Impaired sensory evidence accumulation and network function in Lewy body dementia.

Deficits in attention underpin many of the cognitive and neuropsychiatric features of Lewy body dementia. These attention-related symptoms remain difficult to treat and there are many gaps in our understanding of their neurobiology. An improved understanding of attention-related impairments can be achieved via mathematical modelling approaches, which identify cognitive parameters to provide an intermediate level between observed behavioural data and its underlying neural correlate. Here, we apply this approach to identify the role of impaired sensory evidence accumulation in the attention deficits that characterize Lewy body dementia. In 31 people with Lewy body dementia (including 13 Parkinson’s disease dementia and 18 dementia with Lewy bodies cases), 16 people with Alzheimer’s disease, and 23 healthy controls, we administered an attention task whilst they underwent functional 3 T MRI. Using hierarchical Bayesian estimation of a drift-diffusion model, we decomposed task performance into drift rate and decision boundary parameters. We tested the hypothesis that the drift rate—a measure of the quality of sensory evidence accumulation—is specifically impaired in Lewy body dementia, compared to Alzheimer’s disease. We further explored whether trial-by-trial variations in the drift rate related to activity within the default and dorsal attention networks, to determine whether altered activity in these networks was associated with slowed drift rates in Lewy body dementia. Our results revealed slower drift rates in the Lewy body dementia compared to the Alzheimer’s disease group, whereas the patient groups were equivalent for their decision boundaries. The patient groups were reduced relative to controls for both parameters. This highlights sensory evidence accumulation deficits as a key feature that distinguishes attention impairments in Lewy body dementia, consistent with impaired ability to efficiently process information from the environment to guide behaviour. We also found that the drift rate was strongly related to activity in the dorsal attention network across all three groups, whereas the Lewy body dementia group showed a divergent relationship relative to the Alzheimer’s disease and control groups for the default network, consistent with altered default network modulation being associated with impaired evidence accumulation. Together, our findings reveal impaired sensory evidence accumulation as a specific marker of attention problems in Lewy body dementia, which may relate to large-scale network abnormalities. By identifying impairments in a specific sub-process of attention, these findings will inform future exploratory and intervention studies that aim to understand and treat attention-related symptoms that are a key feature of Lewy body dementia.

Speeding up Time: Hierarchical Bayesian Drift Diffusion Modelling Evidence for Accelerating Temporal Accumulation

Abstract Time perception is malleable ‒ it can be made to speed up and slow down by various experimental manipulations including the presentation of a sequence of auditory clicks and also angry facial expressions. Recent evidence supports the idea that auditory click trains increase accumulation of evidence across time. Here, we test this idea for both angry expressions and auditory clicks by modelling response times (and choice responses) using Bayesian Hierarchical Drift Diffusion Modelling. Two separate groups of participants (Experiment 1; n = 29; Experiment 2; n = 38) judged the duration of angry and neutral facial expressions preceded by either a 3-s sequence of auditory clicks or silence. In both experiments, standard psychophysical analyses showed that both clicks and angry expressions lengthened the perception of time. The original finding came from the analyses of the Drift Diffusion Modelling parameter that represents the speed of information accumulation ‒ the drift rate parameter. Drift rates grew in magnitude with the duration of the face and moreover this effect was larger when the faces were either preceded by clicks or appeared angry ‒ evidence for accelerating temporal accumulation. This novel insight would not have been possible from traditional psychophysical analyses and therefore, the results highlight the potential value of Bayesian Hierarchical Drift Diffusion Modelling as a tool for understanding how we perceive time.