Node proximity attenuates the CCEP–DTI degree association, while the patient-level residual is not Holm-significant
We re-evaluated the reported association between effective connectivity degree (ECD) from single-pulse CCEPs and structural connectivity degree (SCD) from DTI in ds005448, using the authors’ derived input table for 857 electrode areas from 13 patients (5 ECoG, 8 SEEG). Within each patient, we calculated Spearman correlations and partial correlations controlling for node proximity (NP), then used exact sign-flip tests across patients and Holm correction across seven tests within each cohort. The unadjusted SCD–ECD association was positive in 12 of 13 patients (mean rho 0.32; authors’ 11-patient cohort p = 0.005, Holm p = 0.029). ECD and NP were strongly correlated (mean rho -0.62). After control for NP, mean partial rho fell to 0.12; it was not significant after Holm correction in the authors’ cohort (7/11 positive, p = 0.061, Holm p = 0.18), all 13 patients (9/13 positive, p = 0.029, Holm p = 0.087), or SEEG-only cohort (6/8 positive, p = 0.047, Holm p = 0.125). Fixed-effects OLS recovered the authors’ raw-unit ECD coefficient (0.125 versus 0.126), but its patient-cluster bootstrap 95% CI included zero (-0.047 to 0.295); a within-patient z-score model had a CI excluding zero (0.013 to 0.303), so significance depended on method. The reported direction was reproduced, while much of the association was consistent with shared dependence on proximity. We did not recompute tractography, CCEP N1 detection, or NP. Rank residualization assumes linear control, non-linear effects may remain, and 13 patients provide low power; a small partial association (rho about 0.1) cannot be excluded.
focal epilepsy · effective connectivity · structural connectivity · CCEP · DTI · node proximity · partial correlation · patient-level inference · sign-flip test
References
3- usesIn six SEEG patients, SOZ contacts did not receive significantly more CCEP N1 responses after distance control sci:sha256:50d7449a6feefc0875ffd1fb06586e32df6d2856efee1a3b0302b99bd622f9bf
This package uses the ds005448 v1.0.0 derivative tables (input_LMM_model.csv, output_LMM_model.csv) and participant metadata that are archived in that publication.
- usesdoi:10.18112/openneuro.ds005448.v1.0.0
The analyzed input table is identified in the archived report as a derivative from OpenNeuro ds005448 v1.0.0; the cached version-pinned dataset record provides this DOI and identifies the release as CC0.
- doi:10.1016/j.ynirp.2025.100274
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