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Chunk #44 — 4. Discussion — 4.5. Correlations among the Significant Features

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Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features.
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also significantly correlated with each other, regardless of their frequency band. It is possible that the common node forms a subnetwork that can facilitate information flow across the regions of the subnetwork as well as other connected regions in the brain [162]. Further, correlational results also showed that the beta band connections had highly significant correlations with other connections within the same frequency as well as among low-frequency connections (p < 0.001), especially with the theta band connections (p < 0.001 and survived Bonferroni correction). This could be because low frequencies (delta/theta) synchronously work together with high frequencies (beta/gamma) during cognitive processing, including working memory processes [163,164,165]. However, alpha and gamma band connections showed only within-frequency correlations but no cross-frequency correlations, partly because the magnitude of correlations is smaller and requires more statistical power to identify meaningful alpha–gamma associations.