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Tests of working memory capacity (WMC) and fluid intelligence (gF) are thought to capture variability in a crucial cognitive capacity that is broadly predictive of success, yet pinpointing the exact nature of this capacity is an area of ongoing controversy. We propose that mind-wandering is associated with performance on tests of WMC and gF, thereby partially explaining both the reliable correlations between these tests and their broad predictive utility. Existing evidence indicates that both WMC and gF are correlated with performance on tasks of attention, yet more decisive evidence requires an assessment of the role of attention and, in particular, mind-wandering during performance of these tests. Four studies employing complementary methodological designs embedded thought sampling into tests of general aptitude and determined that mind-wandering was consistently associated with worse performance on these measures. Collectively, these studies implicate the capacity to avoid mind-wandering during demanding tasks as a potentially important source of success on measures of general aptitude, while also raising important questions about whether the previously documented relationship between WMC and mind-wandering can be exclusively attributed to executive failures preceding mind-wandering (McVay & Kane, 2010b). (PsycINFO Database Record (c) 2012 APA, all rights reserved).
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... Consistent with the idea that suppressing mind wandering may require cognitive resources (Mcvay & Kane, 2010), individuals with low working memory capacity (WMC) compared to high WMC are more likely to experience mind wandering during high-load tasks (Mcvay & Kane, 2009, 2012aMrazek et al., 2012). Researchers have reported negative correlations between WMC and mind wandering during high-load tasks (Mcvay & Kane, 2012b;Mrazek et al., 2012;, while positive and null-significant associations have been observed between WMC and mind wandering when the latter is measured in low-load tasks (Levinson et al., 2012;Mcvay & Kane, 2012a;Unsworth, McMillan, Brewer, & Spillers, 2012). ...
... Consistent with the idea that suppressing mind wandering may require cognitive resources (Mcvay & Kane, 2010), individuals with low working memory capacity (WMC) compared to high WMC are more likely to experience mind wandering during high-load tasks (Mcvay & Kane, 2009, 2012aMrazek et al., 2012). Researchers have reported negative correlations between WMC and mind wandering during high-load tasks (Mcvay & Kane, 2012b;Mrazek et al., 2012;, while positive and null-significant associations have been observed between WMC and mind wandering when the latter is measured in low-load tasks (Levinson et al., 2012;Mcvay & Kane, 2012a;Unsworth, McMillan, Brewer, & Spillers, 2012). Building on these results, Ju et al. (2018) found an interaction between WMC and task load on mind wandering (Ju & Lien, 2018). ...
... However, despite individuals with lower WMC investing more executive control and allocating a higher proportion of executive resources to the task during high-load tasks, their total amount of executive resources remains lower compared to individuals with higher WMC. Consequently, they end up allocating fewer resources to the task compared to those with higher WMC, leading to the phenomenon observed in previous literature where individuals with higher WMC exhibit less mind wandering during high-load tasks compared to those with lower WMC (Ju & Lien, 2018;Mcvay & Kane, 2009, 2012aMrazek et al., 2012;Rummel & Boywitt, 2014). ...
Article
According to the cognitive flexibility view, individuals with higher cognitive control ability are more flexible in experiencing on task or mind wandering during tasks with different loads. On the other hand, the resource-control theory posits that executive control is essential for allocating attentional resources between mind wandering and tasks. Focus back effort may reflect the adjustment of executive control in the resource-control theory. Here, 121 participants completed two span tasks, as well as high-and low-load tasks, while mind wandering and focus back effort were measured. Our findings indicated that mind wandering was influenced by working memory capacity (WMC) and focus back effort. Additionally, participants demonstrated a higher focus back effort during the higher load task. This effect was particularly pronounced in individuals with lower WMC, which was treated as a continuous variable. These findings integrate the cognitive flexibility view and resource-control theory to describe how individuals modulate mind wandering.
... stimulus-independent) distraction would be you sitting in your office intending to write a paper but wallowing in memories of your last holidays instead. The frequency with which instances of internal distraction are experienced while performing a cognitively taxing task has been shown to be negatively associated with task performance (McVay & Kane, 2009;Mrazek et al., 2012;Robison & Unsworth, 2018;Rummel & Boywitt, 2014;Soemer & Schiefele, 2020;Stawarczyk & D'Argembeau, 2016;Unsworth & McMillan, 2013). Just as often, however, when we experience distractions, they are triggered by the occurrence of some task-irrelevant stimulus in the environment, such as a heated discussion by some colleagues in the hallway that distracts us from writing the paper. ...
... Moreover, attention and working memory are closely intertwined [4,5], and individual differences in these abilities are dependent on their interrelated variations [6]. Lapses in working memory performance have been associated with differences in individuals' attention [7], wherein low-ability individuals exhibit more frequent mind-wandering, particularly during cognitively demanding tasks, and this phenomenon demonstrates synchronized behavior [4]. ...
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This study was designed to examine how mind-wandering and its neural correlates vary across tasks with different attentional demands, motivated by the context regulation hypothesis of mind-wandering. Participants ( n = 59 undergraduates) completed the sustained attention to response task (SART) and the Stroop selective attention task in counterbalanced order while EEG was recorded. The tasks included experience-sampling probes to identify self-reported episodes of mind-wandering, along with retrospective reports. Participants reported more mind-wandering during the SART than the Stroop and during whichever task was presented second during the session, compared with first. Replicating previous findings, EEG data ( n = 37 usable participants) indicated increased alpha oscillations during episodes of mind-wandering, compared with on-task episodes, for both the SART and Stroop tasks. ERP data, focused on the P2 component reflecting perceptual processing, found that mind-wandering was associated with increased P2 amplitudes during the Stroop task, counter to predictions from the perceptual decoupling theory. Overall, the study found that self-report and neural correlates of mind-wandering are sensitive to task context. This line of research can further the understanding of how mechanisms of mind-wandering are adapted to varied tasks and situations.
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I present an outline of the abilities and dispositions relevant for innovation in the twenty-first century. Explaining this outline, I discuss how intelligence and creativity relate to two attentional dispositions: mindfulness and mind wandering. I argue that understanding creative problem solving and innovation requires studying the interaction between intelligence, creativity, and these attentional dispositions. To do so, I summarize the twentieth-century maps of human intelligence and their limitations. Second, I use a computational metaphor to discuss the role of intelligence, creativity, and attentional dispositions in creative problem solving. Third, I review some evidence about the relationship between human abilities and attentional dispositions. Finally, to provide an illustration, I discuss the process of innovation in poetry.KeywordsIntelligenceCreativityMind wanderingMindfulnessPoetry
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This chapter shows how immediate memory represents a distinct system or set of processes from long memory. Working memory (WM) was proposed as a dynamic system that enabled active maintenance of task-relevant information in support of the simultaneous execution of complex cognitive tasks. Working memory span tasks measure executive attention processes that are believed to be domain general and contribute to WM span performance irrespective of the skills or the stimuli involved. WM span tasks reflect primarily general executive processes and domain-specific rehearsal and storage processes. Thus, executive processes help maintain or recover access to the target items in the absence of focal attention and effective rehearsal procedures. WM capacity variation, which is driven largely by individual differences in executive attention processes, represents a web of inference across correlational and experimental studies.
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The Raven Progressive Matrices (RPM) tests measure “general cognitive ability” or, better, eductive, or “meaning making,” ability (Raven, Raven, & Court, 1998a,2000). The term “eductive” comes from the Latin root educere, which means, “to draw out.” The basic version of the test, known as the Standard Progressive Matrices (or SPM), consists of five sets of items of the kind shown in Figures 11.1 and 11.2. Within each set, the items become progressively more difficult. At the beginning of each set, the items, although easy again, follow a different logic. The sets in turn become progressively more difficult. The five sets offer those taking the test five opportunities to become familiar with the method of thought required to solve the problems. In addition to the Standard series, there is the Coloured Progressive Matrices (CPM), which is designed to spread the scores of children and less able adults and the Advanced Progressive Matrices (APM), developed to spread the scores of the top 20% of the population.
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Working memory - the ability to keep important information in mind while comprehending, thinking, and acting - varies considerably from person to person and changes dramatically during each person's life. Understanding such individual and developmental differences is crucial because working memory is a major contributor to general intellectual functioning. This volume offers an understanding variation in working memory by presenting comparisons of the leading theories. It incorporates views from the different research groups that operate on each side of the Atlantic, and covers working-memory research on a wide variety of populations, including healthy adults, children with and without learning difficulties, older adults, and adults and children with neurological disorders. Each research group explicitly addresses the same set of theoretical questions, from the perspective of both their own theoretical and experimental work, and from the perspective of relevant alternative approaches. Through these questions, each research group considers their overarching theory of working memory, specifies the critical sources of working memory variation according to their theory, reflects on the compatibility of their approach with other approaches, and assesses their contribution to general working-memory theory. This shared focus across chapters unifies the volume and highlights the similarities and differences among the various theories. Each chapter includes both a summary of research positions and a detailed discussion of each position.
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This chapter describes the nature of working memory capacity (WMC), and addresses the nature of WMC limitations, their effects on higher order cognitive tasks, their relationship to attention control and general fluid intelligence, and their neurological substrates. Much of work explores these issues in the context of individual differences in WMC and the cause of those individual differences. Measures of WMC are highly reliable and highly valid indicators of some construct of clear relevance to feral cognition. Macroanalytic studies have demonstrated that the construct reflected by WMC tasks has a strong relationship with gF above and beyond what these tasks share with simple span tasks. The conflict might also arise from stimulus representations of competing strength. This two-factor model fits with current thinking about the role of two brain structures: the prefrontal cortex as important to the maintenance of information in an active and easily accessible state and the anterior cingulate as important to the detection and resolution of conflict.