Barely Significant
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Structural Brain Imaging Predicts Individual-Level Task Activation Maps Using Deep Learning.

Front Neuroimaging · 2022 · PMC10406267 · PMID 37555134

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closest p · 0.0× alpha
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highly significantp < 0.001actually significant
A Kolmogorov-Smirnov test between the distribution of the diagonal elements of the correlation matrix and the extra-diagonal elements ( Figure 4C ) resulted in a highly significant difference ( p < 0.001), indicating that the predicted task maps are significantly more correlated to their actual maps than to the maps of other subjects.

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