Training Improves Multitasking Performance by Increasing the Speed of Information Processing in Human Prefrontal Cortex

Dux, Paul E.; Tombu, Michael; Harrison, Stephenie; Rogers, Baxter P.; Tong, Frank; Marois, René

doi:10.1016/j.neuron.2009.06.005

Cited by 257 publications

(281 citation statements)

References 68 publications

(121 reference statements)

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“…Interestingly, the IFJ has also been referred to as a neural basis of a central, amodal bottleneck in information processing by Dux and colleagues (Dux et al, 2006(Dux et al, , 2009; see also Tombu et al, 2011). We suggest that this description is compatible with the more functional description provided by Derrfuss et al (2004) in terms of task set configuration if one assumes that the central bottleneck arises from the inability of the IFJ to update two task set configurations at once.…”

Section: The Nature Of Wm Resources: Domain-general Time-based Resourmentioning

confidence: 53%

Domain-general involvement of the posterior frontolateral cortex in time-based resource-sharing in working memory: An fMRI study

et al. 2015

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Working memory is often defined in cognitive psychology as a system devoted to the simultaneous processing and maintenance of information. In line with the time-based resource-sharing model of working memory (TBRS; Barrouillet and Camos, 2015;Barrouillet et al., 2004), there is accumulating evidence that, when memory items have to be maintained while performing a concurrent activity, memory performance depends on the cognitive load of this activity, independently of the domain involved. The present study used fMRI to identify regions in the brain that are sensitive to variations in cognitive load in a domain-general way. More precisely, we aimed at identifying brain areas that activate during maintenance of memory items as a direct function of the cognitive load induced by both verbal and spatial concurrent tasks. Results show that the right IFJ and bilateral SPL/IPS are the only areas showing an increased involvement as cognitive load increases and do so in a domain general manner. When correlating the fMRI signal with the approximated cognitive load as defined by the TBRS model, it was shown that the main focus of the cognitive load-related activation is located in the right IFJ. The present findings indicate that the IFJ makes domain-general contributions to time-based resource-sharing in working memory and allowed us to generate the novel hypothesis by which the IFJ might be the neural basis for the process of rapid switching. We argue that the IFJ might be a crucial part of a central attentional bottleneck in the brain because of its inability to upload more than one task rule at once. © 2015 Elsevier Inc. All rights reserved. IntroductionThe ability of storing information, while doing something else, is one of the core abilities of the human mind making it possible for humans to flexibly adapt to an ever-changing environment. In cognitive psychology, the limited-capacity system underpinning human's ability to mentally maintain information in an active and accessible state, while concurrently and selectively processing some additional information, is referred to as working memory (WM; Baddeley and Hitch, 1974). A model of WM that has focused explicitly on the dual functioning of WM, i.e., the combination of processing and storage, is the time-based resource-sharing model (TBRS; Barrouillet et al., 2004Barrouillet et al., , 2007Barrouillet et al., , 2011. According to this model, the dual functioning of WM is achieved through a mechanism of time-based sharing of domain-general resources between processing and storage. The model assumes that processing and storage both require attention which constitutes a pool of limited domain-general resources that needs to be shared (see also Egner, 2014a, 2014b, for a similar assumption). When attention is focused on the memory traces of to-be-recalled information, they receive activation, but this activation decays over time as soon as the focus of attention is switched away (Cowan, 1995(Cowan, , 1999Towse and Hitch, 1995). Their complete loss would be avoided by a rap...

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Section: The Nature Of Wm Resources: Domain-general Time-based Resourmentioning

confidence: 53%

Domain-general involvement of the posterior frontolateral cortex in time-based resource-sharing in working memory: An fMRI study

et al. 2015

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“…There were only two regions showing a moderate overlap for feature and dimension costs (left SPL and right IPL), indicating that the associated processes are largely driven by different underlying neural substrates. Specifically, target dimension changes led to higher activation in pre-motor and other frontal areas, regions that have previously associated with response-selection processes (Dux et al, 2006(Dux et al, , 2009Marois, Chun & Shima, 2005), and feature changes led to higher activation in occipital areas, previously implicated in featural attention processing (e.g., Serences et al, 2005).…”

Section: Discussionmentioning

confidence: 91%

“…In line with this interpretation, Wager and colleagues (2005) showed that a go/no-go task, which required withholding of incorrect responses, led to significant increases in the brain areas that closely matched those activated by target dimension changes; viz. the DLPFC, right anterior PFC, premotor cortex, SMA (as well as posterior and inferior parietal regions; compare Pollmann and colleagues, 2000; see also Dux et al, 2006Dux et al, , 2009Filmer et al, 2013a,b;Tombu et al, 2011).…”

Section: Theoretical Implicationsmentioning

confidence: 95%

Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI

2014

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Publisher's copyright statement: NOTICE: this is the author's version of a work that was accepted for publication in NeuroImage. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be re ected in this document. Changes may have been made to this work since it was submitted for publication. A de nitive version was subsequently published in NeuroImage, 102, Part 2, 15 November 2014, 10.1016/j.neuroimage.2014.08.058. Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractIn visual search, responses are slowed, from one trial to the next, both when the target dimension changes (e.g., from a color target to a size target) and when the target feature changes (e.g., from a red target to a green target) relative to being repeated across trials. The present study examined whether such feature and dimension switch costs can be attributed to the same underlying mechanism(s). Contrary to this contention, an EEG study showed that feature changes influenced visual selection of the target (i.e., delayed N2pc onset), whereas dimension changes influenced the later process of response selection (i.e., delayed s-LRP onset). An fMRI study provided convergent evidence for the two-system view: Compared with repetitions, feature changes led to increased activation in the occipital cortex, and superior and inferior parietal lobules, which have been implicated in spatial attention. By contrast, dimension changes led to activation of a frontoposterior network that is primarily linked with response selection (i.e., pre-motor cortex, supplementary motor area and frontal areas). Taken together, the results suggest that feature and dimension switch costs are based on different processes. Specifically, whereas target feature changes delay attention shifts to the target, target dimension changes interfere with later response selection operations.

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“…In this section we address these issues based on recent brain imaging studies and the application of videogame playing training regimens. Dux et al (2009) showed that training in a dual task reduced the activation in an area of the prefrontal cortex, namely the inferior frontal junction. The observation is consistent with the hypothesis that efficient multitasking results from a decreased reliance on brain regions involved in executive control.…”

mentioning

confidence: 99%

“…Bherer et al (2005) showed that training improved dual-task performance in both older and younger adults. The improvement also generalized to novel task combinations.Thus, what brain imaging has revealed so far is that the emergence of efficient multitasking does not necessitate the recruitment of new brain regions (Dux et al, 2009); rather, it may be associated with better synchronization or coordination between task-related areas and more efficient use of neural resources. …”

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confidence: 99%

What Brain Imaging Reveals About the Nature of Multitasking

Just¹,

Buchweitz²

2014

Oxford Handbooks Online

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The goal of this chapter is to provide an account of multitasking from the perspective of brain function and cognition, using the new information gleaned from brain imaging science. By comparing the brain activation patterns observed in multitasking to the activation in the component tasks, it is possible to discover what is neurally distinctive and costly about multitasking.The neurocognitive account relates multitasking to the coordination of two large scale cortical networks underlying each of the two tasks and a network of executive control. This approach provides new answers to several timeless questions about multitasking, such as the nature of the limited brain resources for which two tasks compete, the role of automaticity of one of the tasks being co-performed, and the brain effects of training. Keywords:Multitasking; fMRI, brain imaging, brain networks, neural resources, neural mechanisms, training effects, executive function, automaticity Because work and home environments often demand that several tasks be performed concurrently, the scientific study of multitasking has long been of interest. Multiple events in the natural and social environment often co-occur and need to be dealt with immediately and concurrently. For example, parents often have had to attend to one or more children while simultaneously performing other domestic tasks. Another source of interest in multitasking research is that it explores the limits of human cognitive capacities. It is our good fortune that, to some extent, the human brain has the remarkable capability to follow multiple trains of thought at the same time. But this capability has severe limitations because human thought is not unbounded, and it is difficult enough at times to follow just one train of thought.Multitasking opportunities have increased enormously due to the 21 st century technologies that provide a myriad of information streams on various communication devices, multiplying the already multiple streams of available information that might potentially be attended and processed. The availability of these multiple electronic information streams raises the question of what occurs in the human mind and brain when we try to process more than one stream of information at any given time.In this chapter we will use the term multitasking (or dual-tasking) to refer to the concurrent performance of two or more cognitive tasks, and not just passively experiencing multiple media stream inputs, such as interacting online while a movie is on TV. There must be two ongoing concurrent streams of active thought to qualify as multitasking according to our definition.Although the number of available information streams has increased, the brain capability of concurrently processing multiple streams of information has probably not increased by much, because the biological limits have not expanded. Multitasking usually results in at least one of the concurrent tasks being performed more poorly than when it is performed alone. Effective multitasking requires that two com...

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Training Improves Multitasking Performance by Increasing the Speed of Information Processing in Human Prefrontal Cortex

Cited by 257 publications

References 68 publications

Domain-general involvement of the posterior frontolateral cortex in time-based resource-sharing in working memory: An fMRI study

Domain-general involvement of the posterior frontolateral cortex in time-based resource-sharing in working memory: An fMRI study

Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI

What Brain Imaging Reveals About the Nature of Multitasking

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