Quantifying streams of thought during cognitive task performance using sequence analysis

Insights into the time course of mind wandering during task execution

Our minds tend to wander, sometimes with little control. Despite this phenomenon, that can affect our ability to perform everyday tasks gaining much interest, relatively little is understood about the actual time course of MW across an experimental task. With this in mind, we collated data from two previously reported studies investigating the effect of auditory beat stimulation on MW. Taking experience sampling probes intermittently dispersed throughout a sustained-attention-to-response task (SART), we re-evaluated responses to theta monaural beat stimulation, as well as to two control conditions (silence (headphones only) and a sine wave control tone). The experience sampling probes were binned into shorter intervals of approximately five minutes duration, chronologically as they appeared within the paradigm. Experience sampling probes assayed whether MW had occurred, with or without meta-awareness, and lastly in which temporal orientation (past/present/future). By applying this somewhat temporally better resolved approach, we were able to examine the time course of attentional fluctuations related to MW during the execution of the SART, as well as interactions arising from the auditory beat stimulation. As anticipated, MW increased during task execution, most prominently at the beginning of the experiment. We also observed that levels of meta-awareness declined over time. Moreover, the temporal evolution of meta-awareness and past-orientation appeared to depend on the stimulation condition. These data demonstrate that time-on-task is a crucial factor in measuring MW, during the performance of an attentional task.

What's behind deliberation? The effect of task-related mind-wandering on post-incubation creativity

Previous studies have already suggested that the deliberate nature of Mind-Wandering (MW) is critical for promoting creative performance. However, the deliberate nature of MW may be mixed up with task-relatedness. Whether the deliberate nature or task-relatedness of MW is responsible for such positive influence remains unclear. The present study tried to address this issue by investigating the influence of deliberate MW (MW-d) and task-related MW (MW-r) on post-incubation creative performance. Our result showed that MW-d is positively correlated with MW-r and spontaneous MW (MW-s) is highly positively correlated with task-unrelated MW (MW-u). Meanwhile, after controlling the possible confounding variables (i.e., the pre-incubation creative performance, the performance during distraction task, and motivation on creative ideation), both MW-d and MW-r predicted participants' AUT performance after incubation. However, the prediction model based on MW-r was stable while the MW-d-based prediction model was not. These findings indicate that the task-relatedness of MW, instead of its deliberate nature, might have a positive influence on subsequent creative performance.

Coexistence of thought types as an attentional state during a sustained attention task

Some studies have asked participants about attentional state on a scale from on-task to off-task, which set the middle option as attention focused on both, including the possibility of the coexistence of thoughts. In addition, studies using multidimensional probes explicitly assumed coexistence within spontaneous thoughts and task-focus dimensions. Although several studies have assumed the coexistence of some thought dimensions, none has explored whether these are different types of thoughts (task-focus, mind-wandering, task-related, external stimuli-related). To examine whether this coexistence of thought types occurred, we used thought probes to determine the degree of immersion in each. The participants responded to probes presented at random during a sustained attention task. The results revealed a mixture of thought types in many self-reports. In addition, the state of attentional allocation behind self-reports was estimated using the hidden Markov model. We observed the following attentional states: task-focused, task-unrelated, task-related, external stimuli-focused, and task-focused-but also focused on other thoughts. These results suggest that individuals can simultaneously allocate attention to thought types and discriminate between reporting. In some cases, probe options should also be considered for this coexistence. We also examined the relationship between self-reports and behavioral indexes, and discussed the necessity of separately measuring the degree of immersion for each thought type.

The steady state visual evoked potential (SSVEP) tracks "sticky" thinking, but not more general mind-wandering

For a large proportion of our daily lives, spontaneously occurring thoughts tend to disengage our minds from goal-directed thinking. Previous studies showed that EEG features such as the P3 and alpha oscillations can predict mind-wandering to some extent, but only with accuracies of around 60%. A potential candidate for improving prediction accuracy is the Steady-State Visual Evoked Potential (SSVEP), which is used frequently in single-trial contexts such as brain-computer interfaces as a marker of the direction of attention. In this study, we modified the sustained attention to response task (SART) that is usually employed to measure spontaneous thought to incorporate the SSVEP elicited by a 12.5-Hz flicker. We then examined whether the SSVEP could track and allow for the prediction of the stickiness and task-relatedness dimensions of spontaneous thought. Our results show that the SSVEP evoked by flickering words was able to distinguish between more and less sticky thinking but not between whether a participant was on- or off-task. This suggests that the SSVEP is able to track spontaneous thinking when it is strongly disengaged from the task (as in the sticky form of off-task thinking) but not off-task thought in general. Future research should determine the exact dimensions of spontaneous thought to which the SSVEP is most sensitive.

Self-reported mind wandering reflects executive control and selective attention

Mind wandering is ubiquitous in everyday life and has a pervasive and profound impact on task-related performance. A range of psychological processes have been proposed to underlie these performance-related decrements, including failures of executive control, volatile information processing, and shortcomings in selective attention to critical task-relevant stimuli. Despite progress in the development of such theories, existing descriptive analyses have limited capacity to discriminate between the theories. We propose a cognitive-model based analysis that simultaneously explains self-reported mind wandering and task performance. We quantitatively compare six explanations of poor performance in the presence of mind wandering. The competing theories are distinguished by whether there is an impact on executive control and, if so, how executive control acts on information processing, and whether there is an impact on volatility of information processing. Across two experiments using the sustained attention to response task, we find quantitative evidence that mind wandering is associated with two latent factors. Our strongest conclusion is that executive control is impaired: increased mind wandering is associated with reduced ability to inhibit habitual response tendencies. Our nuanced conclusion is that executive control deficits manifest in reduced ability to selectively attend to the information value of rare but task-critical events.

Impact of active and latent concerns about COVID-19 on attention

The interactions between emotion and attention are complex due to the multifaceted nature of attention. Adding to this complexity, the COVID-19 pandemic has altered the emotional landscape, broadly heightening health and financial concerns. Can the heightened concerns about COVID-19 impair one or more of the components of attention? To explore the connection between heightened concerns about COVID-19 and attention, in a preregistered study, we collected survey responses from 234 participants assessing levels of concerns surrounding COVID-19, followed by four psychophysics tasks hypothesized to tap into different aspects of attention: visual search, working memory, sustained attention, and cognitive control. We also measured task-unrelated thoughts. Results showed that task-unrelated thoughts, but not survey reports of concern levels, negatively correlated with sustained attention and cognitive control, while visual search and working memory remained robust to task-unrelated thoughts and survey-indicated concern levels. As a whole, these findings suggest that being concerned about COVID-19 does not interfere with cognitive function unless the concerns are active in the form of task-unrelated thoughts.

Testing the construct validity of competing measurement approaches to probed mind-wandering reports

Psychology faces a measurement crisis, and mind-wandering research is not immune. The present study explored the construct validity of probed mind-wandering reports (i.e., reports of task-unrelated thought [TUT]) with a combined experimental and individual-differences approach. We examined laboratory data from over 1000 undergraduates at two U.S. institutions, who responded to one of four different thought-probe types across two cognitive tasks. We asked a fundamental measurement question: Do different probe types yield different results, either in terms of average reports (average TUT rates, TUT-report confidence ratings), or in terms of TUT-report associations, such as TUT rate or confidence stability across tasks, or between TUT reports and other consciousness-related constructs (retrospective mind-wandering ratings, executive-control performance, and broad questionnaire trait assessments of distractibility–restlessness and positive-constructive daydreaming)? Our primary analyses compared probes that asked subjects to report on different dimensions of experience: TUT-content probes asked about what they’d been mind-wandering about, TUT-intentionality probes asked about why they were mind-wandering, and TUT-depth probes asked about the extent (on a rating scale) of their mind-wandering. Our secondary analyses compared thought-content probes that did versus didn’t offer an option to report performance-evaluative thoughts. Our findings provide some “good news”—that some mind-wandering findings are robust across probing methods—and some “bad news”—that some findings are not robust across methods and that some commonly used probing methods may not tell us what we think they do. Our results lead us to provisionally recommend content-report probes rather than intentionality- or depth-report probes for most mind-wandering research.

The neural correlates of ongoing conscious thought

A core goal in cognitive neuroscience is identifying the physical substrates of the patterns of thought that occupy our daily lives. Contemporary views suggest that the landscape of ongoing experience is heterogeneous and can be influenced by features of both the person and the context. This perspective piece considers recent work that explicitly accounts for both the heterogeneity of the experience and context dependence of patterns of ongoing thought. These studies reveal that systems linked to attention and control are important for organizing experience in response to changing environmental demands. These studies also establish a role of the default mode network beyond task-negative or purely episodic content, for example, implicating it in the level of vivid detail in experience in both task contexts and in spontaneous self-generated experiential states. Together, this work demonstrates that the landscape of ongoing thought is reflected in the activity of multiple neural systems, and it is important to distinguish between processes contributing to how the experience unfolds from those linked to how these experiences are regulated.

Associations between self-reported spontaneous thought and temporal sequences of EEG microstates

Thought dynamically evolves from one moment to the next even in the absence of external stimulation. The extent to which patterns of spontaneous thought covary with time-varying fluctuations in intrinsic brain activity is of great interest but remains unknown. We conducted novel analyses of data originally reported by Portnova et al. (2019) to examine associations between the intrinsic dynamics of EEG microstates and self-reported thought measured using the Amsterdam Resting-State Questionnaire (ARSQ). Accordingly, the millisecond fluctuations of microstates were associated with specific dimensions of thought. We evaluated the reliability of these findings by combining our results with those of another study using meta-analysis. Importantly, we extended this investigation using multivariate methods to evaluate multidimensional thought profiles of individuals and their links to sequences of successive microstates. Thought profiles were identified based on hierarchical clustering of ARSQ ratings and were distinguished in terms of the temporal ordering of successive microstates based on sequence analytic methods. These findings demonstrate the relevance of assessing spontaneous thought for understanding intrinsic brain activity and the novel use of sequence analysis for characterizing microstate dynamics. Integrating the phenomenological view from within remains crucial for understanding the functional significance of intrinsic large-scale neurodynamics.

How to Interpret Resting-State fMRI: Ask Your Participants

Resting-state fMRI (rsfMRI) reveals brain dynamics in a task-unconstrained environment as subjects let their minds wander freely. Consequently, resting subjects navigate a rich space of cognitive and perceptual states (i.e., ongoing experience). How this ongoing experience shapes rsfMRI summary metrics (e.g., functional connectivity) is unknown, yet likely to contribute uniquely to within- and between-subject differences. Here we argue that understanding the role of ongoing experience in rsfMRI requires access to standardized, temporally resolved, scientifically validated first-person descriptions of those experiences. We suggest best practices for obtaining those descriptions via introspective methods appropriately adapted for use in fMRI research. We conclude with a set of guidelines for fusing these two data types to answer pressing questions about the etiology of rsfMRI.

The psychological correlates of distinct neural states occurring during wakeful rest

When unoccupied by an explicit external task, humans engage in a wide range of different types of self-generated thinking. These are often unrelated to the immediate environment and have unique psychological features. Although contemporary perspectives on ongoing thought recognise the heterogeneity of these self-generated states, we lack both a clear understanding of how to classify the specific states, and how they can be mapped empirically. In the current study, we capitalise on advances in machine learning that allow continuous neural data to be divided into a set of distinct temporally re-occurring patterns, or states. We applied this technique to a large set of resting state data in which we also acquired retrospective descriptions of the participants' experiences during the scan. We found that two of the identified states were predictive of patterns of thinking at rest. One state highlighted a pattern of neural activity commonly seen during demanding tasks, and the time individuals spent in this state was associated with descriptions of experience focused on problem solving in the future. A second state was associated with patterns of activity that are commonly seen under less demanding conditions, and the time spent in it was linked to reports of intrusive thoughts about the past. Finally, we found that these two neural states tended to fall at either end of a neural hierarchy that is thought to reflect the brain's response to cognitive demands. Together, these results demonstrate that approaches which take advantage of time-varying changes in neural function can play an important role in understanding the repertoire of self-generated states. Moreover, they establish that important features of self-generated ongoing experience are related to variation along a similar vein to those seen when the brain responds to cognitive task demands.