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Randall W Engle - One of the best experts on this subject based on the ideXlab platform.
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working Memory Capacity and fluid intelligence maintenance and disengagement
Perspectives on Psychological Science, 2016Co-Authors: Zach Shipstead, Tyler L. Harrison, Randall W EngleAbstract:Working Memory Capacity and fluid intelligence have been demonstrated to be strongly correlated traits. Typically, high working Memory Capacity is believed to facilitate reasoning through accurate ...
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working Memory Capacity and fluid intelligence maintenance and disengagement
Perspectives on Psychological Science, 2016Co-Authors: Zach Shipstead, Tyler L. Harrison, Randall W EngleAbstract:Working Memory Capacity and fluid intelligence have been demonstrated to be strongly correlated traits. Typically, high working Memory Capacity is believed to facilitate reasoning through accurate maintenance of relevant information. In this article, we present a proposal reframing this issue, such that tests of working Memory Capacity and fluid intelligence are seen as measuring complementary processes that facilitate complex cognition. Respectively, these are the ability to maintain access to critical information and the ability to disengage from or block outdated information. In the realm of problem solving, high working Memory Capacity allows a person to represent and maintain a problem accurately and stably, so that hypothesis testing can be conducted. However, as hypotheses are disproven or become untenable, disengaging from outdated problem solving attempts becomes important so that new hypotheses can be generated and tested. From this perspective, the strong correlation between working Memory Capacity and fluid intelligence is due not to one ability having a causal influence on the other but to separate attention-demanding mental functions that can be contrary to one another but are organized around top-down processing goals.
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Working Memory Capacity and the scope and control of attention
Attention Perception & Psychophysics, 2015Co-Authors: Zach Shipstead, Tyler L. Harrison, Randall W EngleAbstract:Complex span and visual arrays are two common measures of working Memory Capacity that are respectively treated as measures of attention control and storage Capacity. A recent analysis of these tasks concluded that (1) complex span performance has a relatively stronger relationship to fluid intelligence and (2) this is due to the requirement that people engage control processes while performing this task. The present study examines the validity of these conclusions by examining two large data sets that include a more diverse set of visual arrays tasks and several measures of attention control. We conclude that complex span and visual arrays account for similar amounts of variance in fluid intelligence. The disparity relative to the earlier analysis is attributed to the present study involving a more complete measure of the latent ability underlying the performance of visual arrays. Moreover, we find that both types of working Memory task have strong relationships to attention control. This indicates that the ability to engage attention in a controlled manner is a critical aspect of working Memory Capacity, regardless of the type of task that is used to measure this construct.
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wonderlic working Memory Capacity and fluid intelligence
Intelligence, 2015Co-Authors: Kenny L Hicks, Tyle L Harriso, Randall W EngleAbstract:Abstract Despite the widespread popularity of the Wonderlic Personnel Test, evidence of its validity as a measure of intelligence and personnel selection is limited. The present study sought to better understand the Wonderlic by investigating its relationship to multiple measures of working Memory Capacity and fluid intelligence. Our results show that Wonderlic has no direct relationship to fluid intelligence once its commonality to working Memory Capacity is accounted for. Further, we found that the Wonderlic was a significant predictor of working Memory Capacity for subjects with low fluid intelligence, but failed to discriminate as well among subjects with high fluid intelligence. These results suggest that the predictive power of the Wonderlic could depend on the characteristics of the sample it is administered to, whereas the relationship between fluid intelligence and working Memory Capacity is robust and invariant to the cognitive capabilities of the sample.
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the mechanisms of working Memory Capacity primary Memory secondary Memory and attention control
Journal of Memory and Language, 2014Co-Authors: Zach Shipstead, Dakota R B Lindsey, Robyn L Marshall, Randall W EngleAbstract:Working Memory Capacity is traditionally treated as a unitary construct that can be explained using one cognitive mechanism (e.g., storage, attention control). Several recent studies have, however, demonstrated that multiple mechanisms are needed to explain individual differences in working Memory Capacity. The present study focuses on three such mechanisms: Maintenance/disengagement in primary Memory, retrieval from sec- ondary Memory, and attention control. Structural equation modeling reveals that each of these mechanisms is important to explaining individual differences in working Memory Capacity. Further analyses reveal that the degree to which these mechanisms are apparent may be driven by the type of task used to operationalize working Memory Capacity. Spe- cifically, complex span (processing and storage) and visual arrays (change detection) per- formance is strongly related to a person's attention control, while running Memory span (Memory for last n items on a list) performance has a relationship to primary Memory that is apparent above-and-beyond other working Memory tasks. Finally, regardless of the working Memory task that is used, it is found that primary and secondary Memory fully explain the relationship of working Memory Capacity to general fluid intelligence.
Nash Unsworth - One of the best experts on this subject based on the ideXlab platform.
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mind wandering and reading comprehension examining the roles of working Memory Capacity interest motivation and topic experience
Journal of Experimental Psychology: Learning Memory and Cognition, 2013Co-Authors: Nash Unsworth, Brittany D McmillanAbstract:Individual differences in mind wandering and reading comprehension were examined in the current study. In particular, individual differences in mind wandering, working Memory Capacity, interest in the current topic, motivation to do well on the task, and topic experience and their relations with reading comprehension were examined in the current study. Using confirmatory factor analysis and structural equation modeling it was found that variation in mind wandering while reading was influenced by working Memory Capacity, topic interest, and motivation. Furthermore, these same factors, along with topic experience, influenced individual differences in reading comprehension. Importantly, several factors had direct effects on reading comprehension (and mind wandering), while the relation between reading comprehension (and mind wandering) and other factors occurred via indirect effects. These results suggest that both domain-general and domain-specific factors contribute to mind wandering while reading and to reading comprehension.
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faster smarter working Memory Capacity and perceptual speed in relation to fluid intelligence
Journal of cognitive psychology, 2012Co-Authors: Thomas S Redick, Nash Unsworth, Andrew J Kelly, Randall W EngleAbstract:Numerous studies have found that working Memory Capacity and perceptual speed predict variation in fluid intelligence. Within the cognitive ageing literature, perceptual speed accounts for substantial ageing variance in working Memory Capacity and fluid intelligence. However, within young adults, the interrelationships among these three abilities are less clear. The current work investigated these relationships via confirmatory factor analyses and structural equation modelling using tasks with verbal, spatial, and numerical content. The results indicate that working Memory Capacity and perceptual speed were not related in a large, cognitively diverse sample of young adults. However, both working Memory Capacity and perceptual speed accounted for unique variance in fluid intelligence. The results are discussed in relation to previous research with young and older adults.
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measuring working Memory Capacity with automated complex span tasks
European Journal of Psychological Assessment, 2012Co-Authors: Thomas S Redick, Nash Unsworth, James M Broadway, Matt E Meier, Princy S Kuriakose, Michael J Kane, Randall W EngleAbstract:Individual differences in working Memory Capacity are related to a variety of behaviors both within and outside of the lab. Recently developed automated complex span tasks have contributed to increasing our knowledge concerning working Memory Capacity by making valid and reliable assessments freely available for use by researchers. Combining the samples from three testing locations yielded data from over 6,000 young adult participants who performed at least one of three such tasks (Operation, Symmetry, and Reading Span). Normative data are presented here for researchers interested in applying cutoffs for their own applications, and information on the validity and reliability of the tasks is also reported. In addition, the data were analyzed as a function of sex and college status. While automated complex span tasks are just one way to measure working Memory Capacity, the use of a standardized procedure for adminis- tration and scoring greatly facilitates comparison across studies.
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working Memory Capacity attention control secondary Memory or both a direct test of the dual component model
Journal of Memory and Language, 2010Co-Authors: Nash Unsworth, Gregory J. SpillersAbstract:The current study examined the extent to which attention control abilities, secondary Memory abilities, or both accounted for variation in working Memory Capacity (WMC) and its relation to fluid intelligence. Participants performed various attention control, secondary Memory, WMC, and fluid intelligence measures. Confirmatory factor analyses suggested that attention control, secondary Memory, and WMC were best represented as three separate, yet correlated factors, each of which was correlated with fluid intelligence. Structural equation modeling suggested that both attention control and secondary Memory accounted for unique variance in WMC. Furthermore, structural equation modeling and variance partitioning analyses suggested that a substantial part of the shared variance between WMC and fluid intelligence was due to both attention control and secondary Memory abilities. Working Memory Capacity also accounted for variance in fluid intelligence independently of what was accounted for by the other two factors. The results are interpreted within a dual-component model of WMC which suggests that both attention control and secondary Memory abilities (as well as other abilities) are important components of WMC.
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there s more to the working Memory Capacity fluid intelligence relationship than just secondary Memory
Psychonomic Bulletin & Review, 2009Co-Authors: Nash Unsworth, Gene A Ewe, Gregory J. SpillersAbstract:The present study examined the claim that secondary Memory processes account for the correlation between working Memory Capacity and fluid intelligence via a latent variable analysis. In the present study, participants performed multiple measures of secondary Memory, working Memory Capacity, and fluid intelligence. Structural equation modeling suggested that both secondary Memory and working Memory Capacity account for unique variance in fluid intelligence. These results are inconsistent with recent claims that working Memory Capacity does not account for variance in fluid intelligence over and above what is accounted for by secondary Memory. Rather, the results are consistent with models of working Memory Capacity that suggest that both maintenance and retrieval processes are needed to account for the substantial relation between working Memory Capacity and fluid intelligence.
Zach Shipstead - One of the best experts on this subject based on the ideXlab platform.
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working Memory Capacity and fluid intelligence maintenance and disengagement
Perspectives on Psychological Science, 2016Co-Authors: Zach Shipstead, Tyler L. Harrison, Randall W EngleAbstract:Working Memory Capacity and fluid intelligence have been demonstrated to be strongly correlated traits. Typically, high working Memory Capacity is believed to facilitate reasoning through accurate ...
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working Memory Capacity and fluid intelligence maintenance and disengagement
Perspectives on Psychological Science, 2016Co-Authors: Zach Shipstead, Tyler L. Harrison, Randall W EngleAbstract:Working Memory Capacity and fluid intelligence have been demonstrated to be strongly correlated traits. Typically, high working Memory Capacity is believed to facilitate reasoning through accurate maintenance of relevant information. In this article, we present a proposal reframing this issue, such that tests of working Memory Capacity and fluid intelligence are seen as measuring complementary processes that facilitate complex cognition. Respectively, these are the ability to maintain access to critical information and the ability to disengage from or block outdated information. In the realm of problem solving, high working Memory Capacity allows a person to represent and maintain a problem accurately and stably, so that hypothesis testing can be conducted. However, as hypotheses are disproven or become untenable, disengaging from outdated problem solving attempts becomes important so that new hypotheses can be generated and tested. From this perspective, the strong correlation between working Memory Capacity and fluid intelligence is due not to one ability having a causal influence on the other but to separate attention-demanding mental functions that can be contrary to one another but are organized around top-down processing goals.
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Working Memory Capacity and the scope and control of attention
Attention Perception & Psychophysics, 2015Co-Authors: Zach Shipstead, Tyler L. Harrison, Randall W EngleAbstract:Complex span and visual arrays are two common measures of working Memory Capacity that are respectively treated as measures of attention control and storage Capacity. A recent analysis of these tasks concluded that (1) complex span performance has a relatively stronger relationship to fluid intelligence and (2) this is due to the requirement that people engage control processes while performing this task. The present study examines the validity of these conclusions by examining two large data sets that include a more diverse set of visual arrays tasks and several measures of attention control. We conclude that complex span and visual arrays account for similar amounts of variance in fluid intelligence. The disparity relative to the earlier analysis is attributed to the present study involving a more complete measure of the latent ability underlying the performance of visual arrays. Moreover, we find that both types of working Memory task have strong relationships to attention control. This indicates that the ability to engage attention in a controlled manner is a critical aspect of working Memory Capacity, regardless of the type of task that is used to measure this construct.
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the mechanisms of working Memory Capacity primary Memory secondary Memory and attention control
Journal of Memory and Language, 2014Co-Authors: Zach Shipstead, Dakota R B Lindsey, Robyn L Marshall, Randall W EngleAbstract:Working Memory Capacity is traditionally treated as a unitary construct that can be explained using one cognitive mechanism (e.g., storage, attention control). Several recent studies have, however, demonstrated that multiple mechanisms are needed to explain individual differences in working Memory Capacity. The present study focuses on three such mechanisms: Maintenance/disengagement in primary Memory, retrieval from sec- ondary Memory, and attention control. Structural equation modeling reveals that each of these mechanisms is important to explaining individual differences in working Memory Capacity. Further analyses reveal that the degree to which these mechanisms are apparent may be driven by the type of task used to operationalize working Memory Capacity. Spe- cifically, complex span (processing and storage) and visual arrays (change detection) per- formance is strongly related to a person's attention control, while running Memory span (Memory for last n items on a list) performance has a relationship to primary Memory that is apparent above-and-beyond other working Memory tasks. Finally, regardless of the working Memory task that is used, it is found that primary and secondary Memory fully explain the relationship of working Memory Capacity to general fluid intelligence.
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working Memory training may increase working Memory Capacity but not fluid intelligence
Psychological Science, 2013Co-Authors: Tyle L Harriso, Kenny L Hicks, Zach Shipstead, Thomas S Redick, David Z Hambrick, Randall W EngleAbstract:Working Memory is a critical element of complex cognition, particularly under conditions of distraction and interference. Measures of working Memory Capacity correlate positively with many measures of real-world cognition, including fluid intelligence. There have been numerous attempts to use training procedures to increase working Memory Capacity and thereby performance on the real-world tasks that rely on working Memory Capacity. In the study reported here, we demonstrated that training on complex working Memory span tasks leads to improvement on similar tasks with different materials but that such training does not generalize to measures of fluid intelligence.
Edward K. Vogel - One of the best experts on this subject based on the ideXlab platform.
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the contribution of attentional lapses to individual differences in visual working Memory Capacity
Journal of Cognitive Neuroscience, 2015Co-Authors: Kirsten Adam, Keisuke Fukuda, Irida Mance, Edward K. VogelAbstract:Attentional control and working Memory Capacity are important cognitive abilities that substantially vary between individuals. Although much is known about how attentional control and working Memory Capacity relate to each other and to constructs like fluid intelligence, little is known about how trial-by-trial fluctuations in attentional engagement impact trial-by-trial working Memory performance. Here, we employ a novel whole-report Memory task that allowed us to distinguish between varying levels of attentional engagement in humans performing a working Memory task. By characterizing low-performance trials, we can distinguish between models in which working Memory performance failures are caused by either 1 complete lapses of attention or 2 variations in attentional control. We found that performance failures increase with set-size and strongly predict working Memory Capacity. Performance variability was best modeled by an attentional control model of attention, not a lapse model. We examined neural signatures of performance failures by measuring EEG activity while participants performed the whole-report task. The number of items correctly recalled in the Memory task was predicted by frontal theta power, with decreased frontal theta power associated with poor performance on the task. In addition, we found that poor performance was not explained by failures of sensory encoding; the P1/N1 response and ocular artifact rates were equivalent for high-and low-performance trials. In all, we propose that attentional lapses alone cannot explain individual differences in working Memory performance. Instead, we find that graded fluctuations in attentional control better explain the trial-by-trial differences in working Memory that we observe.
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visual working Memory Capacity from psychophysics and neurobiology to individual differences
Trends in Cognitive Sciences, 2013Co-Authors: Steven J Luck, Edward K. VogelAbstract:Visual working Memory Capacity is of great interest because it is strongly correlated with overall cognitive ability, can be understood at the level of neural circuits, and is easily measured. Recent studies have shown that Capacity influences tasks ranging from saccade targeting to analogical reasoning. A debate has arisen over whether Capacity is constrained by a limited number of discrete representations or by an infinitely divisible resource, but the empirical evidence and neural network models currently favor a discrete item limit. Capacity differs markedly across individuals and groups, and recent research indicates that some of these differences reflect true differences in storage Capacity whereas others reflect variations in the ability to use Memory Capacity efficiently.
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impaired contingent attentional capture predicts reduced working Memory Capacity in schizophrenia
PLOS ONE, 2012Co-Authors: Jutta S Mayer, Edward K. Vogel, Keisuke Fukuda, Sohee ParkAbstract:Although impairments in working Memory (WM) are well documented in schizophrenia, the specific factors that cause these deficits are poorly understood. In this study, we hypothesized that a heightened susceptibility to attentional capture at an early stage of visual processing would result in working Memory encoding problems. 30 patients with schizophrenia and 28 demographically matched healthy participants were presented with a search array and asked to report the orientation of the target stimulus. In some of the trials, a flanker stimulus preceded the search array that either matched the color of the target (relevant-flanker capture) or appeared in a different color (irrelevant-flanker capture). Working Memory Capacity was determined in each individual using the visual change detection paradigm. Patients needed considerably more time to find the target in the no-flanker condition. After adjusting the individual exposure time, both groups showed equivalent capture costs in the irrelevant-flanker condition. However, in the relevant-flanker condition, capture costs were increased in patients compared to controls when the stimulus onset asynchrony between the flanker and the search array was high. Moreover, the increase in relevant capture costs correlated negatively with working Memory Capacity. This study demonstrates preserved stimulus-driven attentional capture but impaired contingent attentional capture associated with low working Memory Capacity in schizophrenia. These findings suggest a selective impairment of top-down attentional control in schizophrenia, which may impair working Memory encoding.
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the effects of two types of sleep deprivation on visual working Memory Capacity and filtering efficiency
PLOS ONE, 2012Co-Authors: Sean P A Drummond, Edward K. Vogel, Dane E Anderson, Laura D Straus, Veronica B PerezAbstract:Sleep deprivation has adverse consequences for a variety of cognitive functions. The exact effects of sleep deprivation, though, are dependent upon the cognitive process examined. Within working Memory, for example, some component processes are more vulnerable to sleep deprivation than others. Additionally, the differential impacts on cognition of different types of sleep deprivation have not been well studied. The aim of this study was to examine the effects of one night of total sleep deprivation and 4 nights of partial sleep deprivation (4 hours in bed/night) on two components of visual working Memory: Capacity and filtering efficiency. Forty-four healthy young adults were randomly assigned to one of the two sleep deprivation conditions. All participants were studied: 1) in a well-rested condition (following 6 nights of 9 hours in bed/night); and 2) following sleep deprivation, in a counter-balanced order. Visual working Memory testing consisted of two related tasks. The first measured visual working Memory Capacity and the second measured the ability to ignore distractor stimuli in a visual scene (filtering efficiency). Results showed neither type of sleep deprivation reduced visual working Memory Capacity. Partial sleep deprivation also generally did not change filtering efficiency. Total sleep deprivation, on the other hand, did impair performance in the filtering task. These results suggest components of visual working Memory are differentially vulnerable to the effects of sleep deprivation, and different types of sleep deprivation impact visual working Memory to different degrees. Such findings have implications for operational settings where individuals may need to perform with inadequate sleep and whose jobs involve receiving an array of visual information and discriminating the relevant from the irrelevant prior to making decisions or taking actions (e.g., baggage screeners, air traffic controllers, military personnel, health care providers).
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neural activity predicts individual differences in visual working Memory Capacity
Nature, 2004Co-Authors: Edward K. Vogel, Maro G MachizawaAbstract:Contrary to our rich phenomenological visual experience, our visual short-term Memory system can maintain representations of only three to four objects at any given moment1,2. For over a century, the Capacity of visual Memory has been shown to vary substantially across individuals, ranging from 1.5 to about 5 objects3,4,5,6,7. Although numerous studies have recently begun to characterize the neural substrates of visual Memory processes8,9,10,11,12, a neurophysiological index of storage Capacity limitations has not yet been established. Here, we provide electrophysiological evidence for lateralized activity in humans that reflects the encoding and maintenance of items in visual Memory. The amplitude of this activity is strongly modulated by the number of objects being held in the Memory at the time, but approaches a limit asymptotically for arrays that meet or exceed storage Capacity. Indeed, the precise limit is determined by each individual's Memory Capacity, such that the activity from low-Capacity individuals reaches this plateau much sooner than that from high-Capacity individuals. Consequently, this measure provides a strong neurophysiological predictor of an individual's Capacity, allowing the demonstration of a direct relationship between neural activity and Memory Capacity.
Gregory J. Spillers - One of the best experts on this subject based on the ideXlab platform.
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working Memory Capacity attention control secondary Memory or both a direct test of the dual component model
Journal of Memory and Language, 2010Co-Authors: Nash Unsworth, Gregory J. SpillersAbstract:The current study examined the extent to which attention control abilities, secondary Memory abilities, or both accounted for variation in working Memory Capacity (WMC) and its relation to fluid intelligence. Participants performed various attention control, secondary Memory, WMC, and fluid intelligence measures. Confirmatory factor analyses suggested that attention control, secondary Memory, and WMC were best represented as three separate, yet correlated factors, each of which was correlated with fluid intelligence. Structural equation modeling suggested that both attention control and secondary Memory accounted for unique variance in WMC. Furthermore, structural equation modeling and variance partitioning analyses suggested that a substantial part of the shared variance between WMC and fluid intelligence was due to both attention control and secondary Memory abilities. Working Memory Capacity also accounted for variance in fluid intelligence independently of what was accounted for by the other two factors. The results are interpreted within a dual-component model of WMC which suggests that both attention control and secondary Memory abilities (as well as other abilities) are important components of WMC.
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there s more to the working Memory Capacity fluid intelligence relationship than just secondary Memory
Psychonomic Bulletin & Review, 2009Co-Authors: Nash Unsworth, Gene A Ewe, Gregory J. SpillersAbstract:The present study examined the claim that secondary Memory processes account for the correlation between working Memory Capacity and fluid intelligence via a latent variable analysis. In the present study, participants performed multiple measures of secondary Memory, working Memory Capacity, and fluid intelligence. Structural equation modeling suggested that both secondary Memory and working Memory Capacity account for unique variance in fluid intelligence. These results are inconsistent with recent claims that working Memory Capacity does not account for variance in fluid intelligence over and above what is accounted for by secondary Memory. Rather, the results are consistent with models of working Memory Capacity that suggest that both maintenance and retrieval processes are needed to account for the substantial relation between working Memory Capacity and fluid intelligence.
