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Phasic pupillary responses were used to track the active maintenance of information in working memory (WM). In seven experiments participants performed various change detection tasks while their pupils were continuously recorded. Across the experiments phasic pupillary responses increased as the number of maintained items increased up to around 4–5 items consistent with behavioral estimates of capacity. Combining data across experiments demonstrated that phasic pupillary responses were related to behavioral estimates of capacity. Furthermore, phasic pupillary responses demonstrated WM load-dependent relations only when active maintenance was required. When instructed to passively stare at the items or to drop items from WM, the pupil remained near baseline levels. These phasic pupillary responses also tracked the time course of maintenance demonstrating sustained responses early in the delay period, but declined thereafter. Finally, phasic pupillary responses tracked selection processes at encoding (filtering and pre-cues), but did not suggest evidence for item removal following retro-cues. These results are consistent with the notion that maintaining items in WM requires the allocation of effortful attention and further suggest that phasic pupillary responses can be used to track the active maintenance of items in WM. [ABSTRACT FROM AUTHOR]

There has been great interest in using working memory (WM) training regimens as an alternative treatment for ADHD, but it has recently been concluded that existing training regimens may not be optimally designed because they target the primary memory component but not the secondary component of WM capacity. This conclusion requires the ability to accurately measure changes in primary and secondary memory abilities over time. The immediate free recall task has been used in previous studies to measure these changes; however, one concern with these tasks is that the recall order required on training exercises may influence the recall strategy used during free recall, which may in turn influence the relative number of items recalled from primary and secondary memory. To address this issue, previous training studies have explicitly controlled recall strategy before and after training. However, the necessity of controlling for recall strategies has not been explicitly tested. The present study investigated the effects of forward-serial-order training on free recall performance under conditions in which recall strategy was not controlled using a sample of adolescents with ADHD. Unlike when recall order was controlled, the main findings showed selective improvement of the secondary memory component (as opposed to the primary memory component) when recall order was uncontrolled. This finding advances our understanding of WM training by highlighting the importance of controlling for recall strategies when free recall tasks are used to measure changes in the primary and secondary components of WM across time. [ABSTRACT FROM AUTHOR]

Individuals encounter problems daily wherein varying numbers of constraints require delimitation of memory to target goal-satisfying information. Multiply-constrained problems, such as the compound remote associates, are commonly used to study this type of problem solving. Since their development, multiply-constrained problems have been theoretically and empirically related to creative thinking, analytical problem solving, insight problem solving, and a multitude of other cognitive abilities. In the present study, we empirically evaluated the range of cognitive abilities previously associated with multiply-constrained problem solving to assess common versus unique predictive variance (i.e., working memory, attention control, episodic and semantic memory, and fluid and crystallized intelligence). Additionally, we sought to determine whether problem-solving ability and self-reported strategy adoption (analytical or insightful) were task specific or task general through the use of novel multiply-constrained problem-solving tasks (TriBond and Location Bond). Performance across these tasks was shown to be domain general, solutions derived through insightful strategies were more often correct than those derived through analytical strategies, and crystallized intelligence was the sole cognitive ability that provided unique predictive value after accounting for all other abilities. [ABSTRACT FROM AUTHOR]

In two experiments, individual differences in working memory capacity (WMC), lapses of attention, and error monitoring were examined. Participants completed multiple WMC tasks along with a version of the Stroop task. During the Stroop, pupil diameter was continuously monitored. In both experiments, error phasic pupillary responses were larger than phasic pupillary responses associated with correct incongruent and correct congruent trials. WMC and indicators of lapses of attention were correlated with error pupillary response, suggesting that high WMC and low lapse individuals had enhanced error monitoring abilities compared with low WMC and high lapse individuals. Furthermore, in Experiment 2 error awareness abilities were associated with WMC, lapses of attention, and the error phasic pupillary responses. Importantly, individual differences in the susceptibility to lapses of attention largely accounted for the relationship between WMC and error monitoring in both experiments. Collectively, these results suggest that WMC is related to error monitoring abilities, but this association is largely due to individual differences in the ability to consistently maintain task engagement and avoid lapses of attention. [ABSTRACT FROM AUTHOR]

Attention capture is an important mechanism that can be important for alerting one to danger, but other times, it is expedient to block distracting information from intrusion. In this experiment, we used an additional singleton paradigm to measure attention capture. Rather than solely using the subtraction method to measure the capture effect, we incorporated eye tracking to provide potentially more reliable measures of overt attention. We calculated multiple dependent variables based on the scan path and estimated a capture effect for each participant using linear mixed effects modeling, which yielded a more reliable measure than the subtraction method. The eye-tracking measures were in fact more reliable than other reaction time indicators of capture. Surprisingly, the reaction time effect was not correlated with dwell time on the distractor, distraction probability, or probability of the first saccade landing on the distractor, but the more reliable mixed model capture effect correlated with dwell time. Finally, we measured individual differences in working memory capacity and attention control with an independent set of measures. Neither working memory capacity nor attention control correlated with either reaction time capture effect, but dwell time on the distractor and verification time were negatively correlated with both. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Introduction: Sustaining attention is a notoriously difficult task as shown in a recent experiment where reaction times (RTs) and pupillometry data were recorded from 350 subjects in a 30-min vigilance task. Subjects were also presented with different types of goal, feedback, and reward., Methods: In this study, we revisit this experimental data and solve three families of machine learning problems: (i) RT-regression problems, to predict subjects' RTs using all available data, (ii) RT-classification problems, to classify responses more broadly as attentive, semi-attentive, and inattentive, and (iii) to predict the subjects' experimental conditions from physiological data., Results: After establishing that regressing RTs is in general a difficult task, we achieve better results classifying them in broader categories. We also successfully disambiguate subjects who received goals and rewards from those who did not. Finally, we quantify changes in accuracy when coarser features (averaged throughout multiple trials) are used. Interestingly, the machine learning pipeline selects different features depending on their resolution, suggesting that predictive physiological features are also resolution-specific., Discussion: These findings highlight the potential of machine learning to advance research on sustained attention and behavior, particularly in studies incorporating pupillometry or other physiological measurements, offering new avenues for understanding and analysis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Fernando, Robison and Maia.)

Three experiments with the psychomotor vigilance task examined whether presenting content-free cues, feedback, and points would reduce lapses of sustained attention. In all three experiments, behavioral lapses of attention (particularly slow reaction times) were reduced with the motivation manipulations compared with control conditions, but self-reports of off-task thinking (e.g., mind-wandering) were unaffected. Pupillary responses (preparatory and phasic) also tended to be larger with the different manipulations compared to control conditions. Collectively, the results are consistent with attentional effort models, suggesting that sustained attention was improved and lapses of attention reduced owing to participants in the motivation conditions mobilizing more attentional effort than participants in the control conditions. These results are consistent with recent research, which suggests that the locus coeruleus norepinephrine system is associated with the mobilization of effort., Competing Interests: Declarations. Conflicts of interest/Competing interests: None. Ethics approval: Approved University of Oregon Institutional Review Board. Consent to participate: All participants consented to participate. Consent for publication: Not applicable., (© 2024. The Psychonomic Society, Inc.)

One mechanism by which transcranial direct current stimulation (tDCS) has been proposed to improve attention is by transcutaneous stimulation of cranial nerves, thereby activating the locus coeruleus (LC). Specifically, placement of the electrodes over the frontal bone and mastoid is thought to facilitate current flow across the face as a path of least resistance. The face is innervated by the trigeminal nerve, and the trigeminal nerve is interconnected with the LC. In this study, we tested whether stimulating the trigeminal nerve impacts indices of LC activity and performance on a sustained attention task. We replicated previous research that shows deterioration in task performance, increases in the rate of task-unrelated thoughts, and reduced pupil responses due to time on task irrespective of tDCS condition (sham, anodal, and cathodal stimulation). Importantly, tDCS did not influence pupil dynamics (pretrial or stimulus-evoked), self-reported attention state, nor task performance in active versus sham stimulation conditions. The findings reported here are consistent with theories about arousal centered on a hypothesized link between LC activity indexed by pupil size, task performance, and self-reported attention state but fail to support hypotheses that tDCS over the trigeminal nerve influences indices of LC function., (© 2024. The Psychonomic Society, Inc.)

In three experiments, we examined the effects of goal-setting on sustained attention and attention lapses. We measured both behavioral task performance and subjective attentional states during a four -choice reaction time task (Experiments 1 and 2 administered online; Experiment 3 conducted in-person). Experiment 1 compared a vague goal versus a specific goal. The specific goal reduced lapses in the form of long response times (RTs) but did not impact task-unrelated thoughts. Experiment 2 expanded on E1 by making the specific goal progressively harder. Behavioral lapses (i.e., long RTs) were reduced in the harder-over-time goal condition compared to the control condition. Additionally, while RTs increased with time-on-task in the control condition, RTs in the harder-over-time goal condition remained stable with time-on-task. Experiment 3 aimed to replicate the results of E2 in-person and adjusted the difficulty of the harder-over-time goals to be slightly harder. The results largely replicated E2. Overall, setting specific and difficult task goals led to a reduction in lapses of attention and increased sustained attention performance., (© 2023. The Psychonomic Society, Inc.)

Latent variable analyses of cognitive abilities are among the major means by which cognitive psychologists test theories regarding the structure of human cognition. Models are fit to observed variance-covariance structures, and the fit of those models are compared to assess the merits of competing theories. However, an often unconsidered and potentially important methodological issue is the precise sequence in which tasks are delivered to participants. Here we empirically tested whether differences in task sequences systematically affect the observed factor structure. A large sample (N = 587) completed a battery of 12 cognitive tasks measuring four constructs: working memory, long-term memory, attention control, and fluid intelligence. Participants were assigned to complete the assessment in one of three sequences: fixed and grouped by construct vs. fixed and interleaved across constructs vs. random by participant. We generated and tested two hypotheses: grouping task sequences by construct (i.e., administering clusters of tasks measuring a cognitive construct consecutively) would (1) systematically increase factor loadings and (2) systematically decrease interfactor correlations. Neither hypothesis was supported. The measurement models were largely invariant across the three conditions, suggesting that latent variable analyses are robust to such subtle methodological differences as task sequencing., (© 2023. The Psychonomic Society, Inc.)

We used pupillometry during a 2-back task to examine individual differences in the intensity and consistency of attention and their relative role in a working memory task. We used sensitivity, or the ability to distinguish targets (2-back matches) and nontargets, as the measure of task performance; task-evoked pupillary responses (TEPRs) as the measure of attentional intensity; and intraindividual pretrial pupil variability as the measure of attentional consistency. TEPRs were greater on target trials compared with nontarget trials, although there was no difference in TEPR magnitude when participants answered correctly or incorrectly to targets. Importantly, this effect interacted with performance: high performers showed a greater separation in their TEPRs between targets and nontargets, whereas there was little difference for low performers. Further, in regression analysis, larger TEPRs on target trials predicted better performance, whereas larger TEPRs on nontarget trials predicted worse performance. Sensitivity positively correlated with average pretrial pupil diameter and negatively correlated with intraindividual variability in pretrial pupil diameter. Overall, we found evidence that both attentional intensity (TEPRs) and consistency (pretrial pupil variation) predict performance on an n-back working memory task., (© 2024. The Psychonomic Society, Inc.)

There has been debate regarding the correlation between baseline/resting state measures of pupil diameter and cognitive abilities such as working memory capacity and fluid intelligence. A positive correlation between baseline pupil diameter and cognitive ability has been cited as evidence for a role of the locus coeruleus-norepinephrine (LC-NE) and its functional connection with cortical networks as a reason for individual differences in fluid intelligence (Tsukahara & Engle, Proceedings of the National Academy of Sciences, 118(46), e2110630118, 2021a). Several recent attempts to replicate this correlation have failed. The current studies make another attempt and find substantial evidence against a positive correlation between pupil diameter and intelligence. Given the data from the current studies in combination with other recent failures to replicate, we conclude that individual differences in baseline pupil diameter should not be used as evidence for a role of the LC-NE system in goal-directed cognitive activity., (© 2023. The Psychonomic Society, Inc.)

The current set of studies examined the relationship among working memory capacity, attention control, fluid intelligence, and pupillary correlates of tonic arousal regulation and phasic responsiveness in a combined sample of more than 1,000 participants in two different age ranges (young adults and adolescents). Each study was designed to test predictions made by two recent theories regarding the role of the locus coeruleus-norepinephrine (LC-NE) system in determining individual differences in cognitive ability. The first theory, proposed by Unsworth and Robison (2017a), posits two important individual differences: the moment-to-moment regulation of tonic arousal, and the phasic responsiveness of the system to goal-relevant stimuli. The second theory, proposed by Tsukahara and Engle (2021a), argues that people with higher cognitive abilities have greater functional connectivity between the LC-NE system and cortical networks at rest. These two theories are not mutually exclusive, but they make different predictions. Overall, we found no evidence consistent with a resting-state theory. However, phasic responsiveness was consistently correlated with working memory capacity, attention control, and fluid intelligence, supporting a prediction made by Unsworth and Robison (2017a). Tonic arousal regulation was not correlated with working memory or fluid intelligence and was inconsistently correlated with attention control, which offers only partial support for Unsworth and Robison's (2017a) second prediction., (© 2023. The Psychonomic Society, Inc.)

Two experiments compared both average performance and changes in performance across time in abrupt- and gradual-onset sustained attention tasks. Experiment 1 compared abrupt- and gradual-onset digits. In conditions where the digits onset and offset abruptly and appeared only briefly, similar to typical conditions in the Sustained Attention to Response Task (SART), participants committed more errors on no-go trials and responded faster overall, indicative of a shift in the speed/accuracy tradeoff toward speed. When the digits abruptly onset but remained on-screen for a longer period of time, there were no differences in no-go error rates, hit rates, or reaction time (RT) variability, but participants still emitted faster RTs overall. Experiment 2 compared abrupt- and gradual-onset images. Similar to Experiment 1, abrupt-onset, short-duration images induced more no-go errors and faster RTs, but also more RT variability and reduced hit rates. In the abrupt-onset, long-duration condition, again the only performance difference was a decrease in average RTs. We discuss implications for using these two types of tasks in sustained attention research., (© 2022. The Psychonomic Society, Inc.)

Eight experiments ( N = 2,003) assessed the relation between working memory capacity (WMC) and performance on the antisaccade task. Experiments 1-5 and 7 examined individual differences in aspects of goal management processes occurring during the preparatory delay of the antisaccade task. WMC tended to interact with delay interval suggesting that high WMC individuals better prepared for the upcoming trial by activating the task goal to a higher level than low WMC individuals (although these effects were generally small). Experiments 3a, 4, and 7 further demonstrated that individual differences in the consistency of attention (i.e., lapses of attention) were partially important for the relation between WMC and antisaccade performance. Experiment 5 demonstrated that knowledge of the likelihood of target location increased overall performance, but did not interact with WMC. Experiment 6 manipulated stimulus onset asynchrony and suggested that speed factors are also likely important for the relation between WMC and antisaccade performance. Finally, structural equation models in Experiment 7 suggested that lapses of attention and speed factors partially accounted for the relation between WMC and antisaccade, but WMC still accounted for unique variance in antisaccade. Collectively, the results suggest that multiple factors (goal activation, consistency of attention, and speed factors) contribute to the relation between variation in WMC and performance on the antisaccade task. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The present study examined individual differences in 3 cognitive abilities: attention control (AC), working memory capacity (WMC), and fluid intelligence (gF) as they relate the tendency to experience task-unrelated thoughts (TUTs) and the regulation of arousal. Cognitive abilities were measured with a battery of 9 laboratory tasks, TUTs were measured via thought probes inserted into 2 tasks, and arousal regulation was measured via pupillometry. Recent theorizing (Unsworth & Robison, 2017b) suggests that 1 reason why some people experience relatively frequent TUTs and relatively poor cognitive performance-especially AC and WMC-is that they exhibit dysregulated arousal. Here, we examined how arousal regulation might predict both AC and WMC, but also higher-order cognitive abilities like gF. Further, we examine direct and indirect associations with these abilities via a mediating influence of TUT. Participants who reported more TUTs also tended to exhibit poorer AC, lower WMC, and lower gF. Arousal dysregulation correlated with more TUTs and lower AC. However, there was no direct correlation between arousal regulation and WMC, nor between arousal regulation and gF. The association between arousal regulation and gF was indirect via TUT. We discuss the implications of the results in light of the arousal regulation theory of individual differences and directions for future research. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The present study is the first to examine individual differences in long-term memory, arousal dysregulation, and intensity of attention within the same experiment. Participants (N = 106) completed 28 lists of an immediate free-recall task while their pupil diameter was recorded via an eye-tracker during the encoding period. Two main pupillary measures were extracted: intraindividual variability in pre-list pupil diameter and evoked pupillary responses during item encoding. Variability in pre-list pupil diameter served as a measure of arousal dysregulation, and evoked pupillary responses served as a measure of intensity of attention. Based on prior work, we hypothesized that there would be a positive association between intensity of attention and recall ability, and that there would be a negative association between arousal dysregulation and recall ability. Collectively these two measures accounted for 19% of interindividual variance in recall, with 5% attributable uniquely to intensity of attention and 12% attributable uniquely to arousal regulation. The findings demonstrate that there are sources of individual differences in long-term memory that can be revealed via pupillometry, notably the amount of effort deployed during item encoding and the degree to which people exhibit dysregulated arousal. Both findings are consistent with recent theorizing regarding the role of the locus coeruleus (LC)-norepinephrine (NE) system's role in goal-directed cognition. Specifically, the LC governs both moment-to-moment arousal and NE release to cortical regions subserving cognitive processing. Among people for whom this system operates most optimally, long-term memory retention is superior., (© 2022. The Psychonomic Society, Inc.)

The study of human reaction time (RT) is invaluable not only to understand the sensory-motor functions but also to translate brain signals into machine comprehensible commands that can facilitate augmentative and alternative communication using brain-computer interfaces (BCI). Recent developments in sensor technologies, hardware computational capabilities, and neural network models have significantly helped advance biomedical signal processing research. This study is an attempt to utilize state-of-the-art resources to explore the relationship between human behavioral responses during perceptual decision-making and corresponding brain signals in the form of electroencephalograms (EEG). In this paper, a generalized 3D convolutional neural network (CNN) architecture is introduced to estimate RT for a simple visual task using single-trial multi-channel EEG. Earlier comparable studies have also employed a number of machine learning and deep learning-based models, but none of them considered inter-channel relationships while estimating RT. On the contrary, the use of 3D convolutional layers enabled us to consider the spatial relationship among adjacent channels while simultaneously utilizing spectral information from individual channels. Our model can predict RT with a root mean square error of 91.5 ms and a correlation coefficient of 0.83. These results surpass all the previous results attained from different studies.Clinical relevance Novel approaches to decode brain signals can facilitate research on brain-computer interfaces (BCIs), psychology, and neuroscience, enabling people to utilize assistive devices by root-causing psychological or neuromuscular disorders.

The estimation of the visual stimulus-based reaction time (RT) using subtle and complex information from the brain signals is still a challenge, as the behavioral response during perceptual decision making varies inordinately across trials. Several investigations have tried to formulate the estimation based on electroencephalogram (EEG) signals. However, these studies are subject-specific and limited to regression-based analysis. In this paper, for the first time to our knowledge, a generalized model is introduced to estimate RT using single-trial EEG features for a simple visual reaction task, considering both regression and classification-based approaches. With the regression-based approach, we could predict RT with a root mean square error of 111.2 ms and a correlation coefficient of 0.74. A binary and a 3-class classifier model were trained, based on the magnitude of RT, for the classification approach. Accuracy of 79% and 72% were achieved for the binary and the 3-class classification, respectively. Limiting our study to only high and low RT groups, the model classified the two groups with an accuracy of 95%. Relevant EEG channels were evaluated to localize the part of the brain significantly responsible for RT estimation, followed by the isolation of important features.Clinical relevance- Electroencephalogram (EEG) signals can be used in Brain-computer interfaces (BCIs), enabling people with neuromuscular disorders like brainstem stroke, amyotrophic lateral sclerosis, and spinal cord injury to communicate with assistive devices. However, advancements regarding EEG signal analysis and interpretation are far from adequate, and this study is a step forward.