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Scale-invariance in brain activity predicts practice effects in cognitive performance

View ORCID ProfileOmid Kardan, View ORCID ProfileElliot Layden, View ORCID ProfileKyoung Whan Choe, View ORCID ProfileMuxuan Lyu, Xihan Zhang, Sian L. Beilock, View ORCID ProfileMonica D. Rosenberg, View ORCID ProfileMarc G. Berman
doi: https://doi.org/10.1101/2020.05.25.114959
Omid Kardan
1University of Chicago, Chicago, IL, USA
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  • For correspondence: okardan@uchicago.edu bermanm@uchicago.edu
Elliot Layden
1University of Chicago, Chicago, IL, USA
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Kyoung Whan Choe
1University of Chicago, Chicago, IL, USA
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Muxuan Lyu
2The Hong Kong Polytechnic University, Hong Kong
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Xihan Zhang
1University of Chicago, Chicago, IL, USA
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Sian L. Beilock
3Barnard College, Columbia University, NY, USA
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Monica D. Rosenberg
1University of Chicago, Chicago, IL, USA
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Marc G. Berman
1University of Chicago, Chicago, IL, USA
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  • For correspondence: okardan@uchicago.edu bermanm@uchicago.edu
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Abstract

Although practicing a task generally benefits later performance on that same task (‘practice effect’), there are large—and mostly unexplained—individual differences in reaping the benefits from practice. One promising avenue to model and predict such differences comes from recent research showing that brain networks can extract functional advantages from operating in the vicinity of criticality, a state in which brain network activity is more scale-free. As such, we hypothesized that individuals with more scale-free fMRI activity, indicated by BOLD time series with a higher Hurst exponent (H), gain more benefits from practice. In this study, participants practiced a test of working memory and attention, the dual n-back task (DNB), watched a video clip as a break, and then performed the DNB again, during MRI. To isolate the practice effect, we divided the participants into two groups based on improvement in performance from the first to second DNB task run. We identified regions and connections in which H and functional connectivity related to practice effects in the last run. More scale-free brain activity in these regions during the preceding runs (either first DNB or video) distinguished individuals who showed greater DNB performance improvements over time. In comparison, functional connectivity (r2) in the identified connections did not reliably classify the two groups in the preceding runs. Finally, we replicated both H and r2 results from study 1 in an independent fMRI dataset of participants performing multiple runs of another working memory and attention task (word completion). We conclude that the brain networks can accommodate further practice effects in individuals with higher scale-free BOLD activity.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 26, 2020.
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Scale-invariance in brain activity predicts practice effects in cognitive performance
Omid Kardan, Elliot Layden, Kyoung Whan Choe, Muxuan Lyu, Xihan Zhang, Sian L. Beilock, Monica D. Rosenberg, Marc G. Berman
bioRxiv 2020.05.25.114959; doi: https://doi.org/10.1101/2020.05.25.114959
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Scale-invariance in brain activity predicts practice effects in cognitive performance
Omid Kardan, Elliot Layden, Kyoung Whan Choe, Muxuan Lyu, Xihan Zhang, Sian L. Beilock, Monica D. Rosenberg, Marc G. Berman
bioRxiv 2020.05.25.114959; doi: https://doi.org/10.1101/2020.05.25.114959

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