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Network NeuroscienceNeurosciencePeer-reviewed journal article

Improvements in task performance after practice are associated with scale-free dynamics of brain activity

Omid KardaniD, Andrew J. StieriD, Elliot A. LaydeniD, Kyoung Whan ChoeiD, Muxuan LyuiD, Xi-Han ZhangiD, Sian Leah BeilockiD, Monica D. RosenbergiD, Marc G. BermaniD

PDFDOIPreprint

Abstract

Although practicing a task generally benefits later performance on that same task, there are individual differences in practice effects. One avenue to model such differences comes from research showing that brain networks extract functional advantages from operating in the vicinity of criticality, a state in which brain network activity is more scale-free. We hypothesized that higher scale-free signal from fMRI data, measured with the Hurst exponent (H), indicates closer proximity to critical states. We tested whether individuals with higher H during repeated task performance would show greater practice effects. In Study 1, participants performed a dual-n-back task (DNB) twice during MRI (n = 56). In Study 2, we used two runs of n-back task (NBK) data from the Human Connectome Project sample (n = 599). In Study 3, participants performed a word completion task (CAST) across 6 runs (n = 44). In all three studies, multivariate analysis was used to test whether higher H was related to greater practice-related performance improvement. Supporting our hypothesis, we found patterns of higher H that reliably correlated with greater performance improvement across participants in all three studies. However, the predictive brain regions were distinct, suggesting that the specific spatial H{uparrow} patterns are not task-general.

Citations
27
FWCI
2.70
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top 10%

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