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Articles, Behavioral/Cognitive

Prefrontal Cortex Structure Predicts Training-Induced Improvements in Multitasking Performance

Ashika Verghese, K.G. Garner, Jason B. Mattingley and Paul E. Dux
Journal of Neuroscience 2 March 2016, 36 (9) 2638-2645; https://doi.org/10.1523/JNEUROSCI.3410-15.2016
Ashika Verghese
1School of Psychology and
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K.G. Garner
1School of Psychology and
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Jason B. Mattingley
1School of Psychology and
2Queensland Brain Institute, The University of Queensland, St. Lucia, Queensland 4072, Australia
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Paul E. Dux
1School of Psychology and
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    Figure 1.

    Testing protocol and behavioral paradigms. A, Overview of the testing protocol for each participant. Familiarization sessions were run on Friday afternoon in the week before testing. MRI test sessions were conducted on Monday and Friday at the same time for each participant. Three days of training sessions were run in the interim period (Tuesday, Wednesday, Thursday). B, Example display sequence for the multitasking paradigm. The task comprised three conditions: single task visual manual, in which participants made a manual response to one of two shapes (a “spikey” or a “smoothy” shape); single task auditory manual, in which participants responded manually to an auditory tone (two easily discernible, complex tones); and multitask, in which both single tasks were presented concurrently and each required a separate response. C, Visual search paradigm performed by the irrelevant training group. Participants judged the orientation of a letter “T” target (rotated by 90° clockwise or counterclockwise) presented among 7 (small set size), 11 (medium set size), or 15 (large set size) rotated letter “L” distractors. This is a classic inefficient search paradigm.

  • Figure 2.
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    Figure 2.

    Results. A, Behavioral data. Improvements in multitasking performance from pretraining to posttraining sessions were greater for the relevant training group than for the irrelevant training group (p < 0.0001; error bars represent SEM). B, Whole-brain structural analysis. The cortical surface p maps shows the left rostral DLPFC region for the relevant training group, whose volume (determined from pretraining T1 scans) reliably predicted training-induced multitasking improvements (premultitasking cost minus postmultitasking cost). Clusters were thresholded at p < 0.01 (corrected for multiple comparisons) across all participants in the group. C, Region of interest correlation. The pattern of correlation between the volumes of the significant DLPFC cluster in the two groups and multitasking performance benefit is depicted. Unlike the relevant training group (red symbols), the irrelevant training group (blue symbols) did not show a correlation between behavior and left rostral DLPFC volume.

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    Figure 3.

    Correlations between multitasking performance benefit and cortical thickness and area. A, Significant correlation is observed between left rostral DLPFC thickness and multitasking performance improvements in the relevant training group (red symbols) but not in the irrelevant training group (blue symbols). B, Shows a similar pattern of results for the relationship between left rostral DLPFC area and multitasking performance benefit.

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    Figure 4.

    Split-half cross-validation. A, The left panel depicts p maps of the differences in the correlations observed between volume and multitasking performance benefit for the relevant training and the irrelevant training subgroups (Split 1), estimated by a general linear model analysis (corrected for multiple comparisons) using the split-half approach. The correlations in the prefrontal region were significantly stronger for the relevant training subgroup than for the irrelevant training subgroup. The p value maps are thresholded at p < 0.05 (Monte Carlo correction for multiple comparisons). The right panel shows multitasking performance benefit as a function of left rostral DLPFC volume that was originally extracted from the whole-brain analyses (n = 100). As demonstrated, the relevant training group showed an inverse relationship with multitasking performance benefit even with a smaller subset (Split 1, n = 25 per group). B, The left panel shows a similar pattern of clustering using the Split 2 subgroups of the relevant training and the irrelevant training cohorts. The right panel also demonstrates that only the relevant training group shows a relationship between multitasking performance benefit and left rostral DLPFC volume even with reduced sampling (Split 2, n = 25 per group).

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    Figure 5.

    Correlations between structure and behavior for the multitask trials. The figure shows a whole-brain SBM analysis showing the correlation between volume and training-induced performance gains for the multitask trials only (pretraining multitask trial RT minus posttraining multitask trial RT) in the relevant training group. The data depicted have been corrected for multiple comparisons at the p < 0.05 level.

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The Journal of Neuroscience: 36 (9)
Journal of Neuroscience
Vol. 36, Issue 9
2 Mar 2016
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Prefrontal Cortex Structure Predicts Training-Induced Improvements in Multitasking Performance
Ashika Verghese, K.G. Garner, Jason B. Mattingley, Paul E. Dux
Journal of Neuroscience 2 March 2016, 36 (9) 2638-2645; DOI: 10.1523/JNEUROSCI.3410-15.2016

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Prefrontal Cortex Structure Predicts Training-Induced Improvements in Multitasking Performance
Ashika Verghese, K.G. Garner, Jason B. Mattingley, Paul E. Dux
Journal of Neuroscience 2 March 2016, 36 (9) 2638-2645; DOI: 10.1523/JNEUROSCI.3410-15.2016
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Keywords

  • attention
  • individual differences
  • MRI
  • multitasking
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