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The current study examined pupillary correlates of fluctuations and lapses of sustained attention. Participants performed a sustained attention task with either a varied ISI or a fixed ISI (fixed at 2 or 8 sec) while pupil responses were continuously recorded. The results indicated that performance was worse when the ISI was varied or fixed at 8 sec compared with when the ISI was fixed at 2 sec, suggesting that varied or long ISI conditions require greater intrinsic alertness compared with constant short ISIs. In terms of pupillary responses, the results demonstrated that slow responses (indicative of lapses) were associated with greater variability in tonic pupil diameter, smaller dilation responses during the ISI, and subsequently smaller dilation responses to stimulus onset. These results suggest that lapses of attention are associated with lower intrinsic alertness, resulting in a lowered intensity of attention to task-relevant stimuli. Following a lapse of attention, performance, tonic pupil diameter, and phasic pupillary responses, all increased, suggesting that attention was reoriented to the task. These results are consistent with the notion that pupillary responses track fluctuations in sustained attention.

Individual differences in baseline oculometrics (baseline pupil diameter, spontaneous eye blink rate, fixation stability), and their relation with cognitive abilities, personality traits, and self-report assessments were examined. Participants performed a baseline eye measure in which they were instructed to stare at a fixation point onscreen for 5 min. Following the baseline eye measure, participants completed a questionnaire asking what they were thinking about during the baseline eye measure. Participants also completed various cognitive ability measures assessing working memory capacity, attention control, and off-task thinking. Finally, participants completed a number of questionnaires assessing personality, Attention Deficit/Hyperactivity Disorder symptomology, mind wandering, and morningness-eveningness. Overall, the vast majority of correlations with the baseline eye measures were weak and nonsignificant, suggesting that these associations may not be very robust. The results also demonstrated the importance of examining what participants are thinking about during the baseline measure. These results add to the growing body of findings suggesting inconsistent relations between different baseline eye measures and various individual differences constructs.

Individual differences in lapses of attention were examined in the present study. Participants performed various attention control, working memory, and reaction time (RT) tasks to assess lapses of attention. Task-unrelated thoughts, task-specific motivation, alertness, and trait factors were also assessed. Behavioral indicators of lapses of attention correlated and loaded on the same general lapse of attention factor. The lapse of attention factor correlated with, but was distinct from, attention control and task-unrelated thoughts factors. The lapses of attention factor further related to working memory capacity, speed of processing, motivation, alertness, boredom proneness, and self-reports of everyday cognitive failures. Structural equation modeling suggested that attention control, task-unrelated thoughts, variance shared across task unrelated thoughts, motivation, and alertness, and boredom proneness all accounted for unique variance in lapses of attention. These results provide important evidence for the general tendency to experience lapses of attention in a variety of tasks and situations and further suggest that multiple factors contribute to variation in lapses of attention.

A recent surge of interest in the empirical measurement of mind-wandering has led to an increase in the use of thought-probing to measure attentional states, which has led to large variation in methodologies across studies (Weinstein in Behavior Research Methods, 50, 642-661, 2018). Three sources of variation in methodology include the frequency of thought probes during a task, the number of response options provided for each probe, and the way in which various attentional states are framed during the task instructions. Method variation can potentially affect behavioral performance on the tasks in which thought probes are embedded, the experience of various attentional states within those tasks, and/or response biases to the thought probes. Therefore, such variation can be problematic, both pragmatically and theoretically. Across three experiments, we examined how manipulating probe frequency, response options, and framing affected behavioral performance and responses to thought probes. Probe frequency and framing did not affect behavioral performance or probe responses. But, in light of the present results, we argue that thought probes need at least three responses, corresponding to on-task, off-task, and task-related interference. When researchers are specifically investigating mind-wandering, the probe responses should also distinguish between mind-wandering, external distraction, and mind-blanking.

Two experiments examined individual differences in lapses of sustained attention. Participants performed variants of the psychomotor vigilance task while pupillary responses and fixations were recorded. Examining pupillary responses during the interstimulus interval in both experiments suggested that individuals particularly susceptible to lapses of attention (indexed by the slowest response times) demonstrated a decreased pupillary response during the interstimulus interval, whereas individuals less susceptible to lapses of attention demonstrated an increased pupillary response during the interstimulus interval. These results suggest that variation in lapses of attention are partially attributable to individual differences in the ability to voluntarily control the intensity of attention (intrinsic alertness) and fully engage preparatory processes on a moment-by-moment basis. Furthermore, across both experiments additional individual differences factors covaried with lapses of attention, including attention control, working memory capacity, susceptibility to off-task thinking, task-specific motivation, and fixation stability. These results provide evidence for the notion that individual differences in lapses of attention are multifaceted and that variation in intrinsic alertness and other factors are important contributors to this variation.

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.