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Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks

CVPR 2016 · Graph learning › Graph algorithms and clustering · approach: Graph distance and retrieval · 7 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add both longitudinal and cross-sectional coupling instead of no coupling (ablation)Coupled harmonic bases · RAVLT and MMSE quantile classification, j=1accuracy (%): RAVLT: 33.33 -> 71.43; 38.10 -> 57.14; 28.57 -> 47.62. MMSE: 42.86 -> 76.19; 42.86 -> 47.62; 34.92 -> 47.62Mixed
Add both longitudinal and cross-sectional coupling instead of no coupling (ablation)Coupled harmonic bases · RAVLT and MMSE quantile classification, j={1,2,3}accuracy (%): RAVLT: 34.92 -> 71.43; 33.33 -> 55.56; 28.57 -> 34.92. MMSE: 41.27 -> 71.43; 38.10 -> 50.79; 28.57 -> 28.57Mixed
Add cross-sectional coupling only instead of no coupling (ablation)Coupled harmonic bases · RAVLT and MMSE quantile classificationaccuracy (%): RAVLT j=1: 33.33 -> 66.67; 38.10 -> 57.14; 28.57 -> 30.16; MMSE j=1: 42.86 -> 57.14; 42.86 -> 47.62; 34.92 -> 19.05Mixed
Add longitudinal coupling only instead of no coupling (ablation)Coupled harmonic bases · RAVLT and MMSE quantile classificationaccuracy (%): RAVLT j=1: 33.33 -> 42.86; 38.10 -> 52.38; 28.57 -> 23.81; MMSE j=1: 42.86 -> 28.57; 42.86 -> 47.62; 34.92 -> 23.81Mixed
Add both forms of coupling rather than longitudinal coupling only (ablation)Coupled harmonic bases · RAVLT and MMSE quantile classificationaccuracy (%): RAVLT j=1: 42.86 -> 71.43; 52.38 -> 57.14; 23.81 -> 47.62; MMSE j=1: 28.57 -> 76.19; 47.62 -> 47.62; 23.81 -> 47.62Mixed
Add both forms of coupling rather than cross-sectional coupling only (ablation)Coupled harmonic bases · RAVLT and MMSE quantile classificationaccuracy (%): RAVLT j={1,2,3}: 60.32 -> 71.43; 44.44 -> 55.56; 23.81 -> 34.92; MMSE j={1,2,3}: 39.68 -> 71.43; 46.03 -> 50.79; 12.70 -Mixed

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