Fig. 4: Epicenter connectivity-based prediction of cross-sectional synaptic loss.

a A data-driven approach to identify the SV2A w score epicenter, adapted from the method proposed by Shafiei et al.⁴⁰. Epicenter likelihood was calculated as the mean rank of the regional SV2A-PET w score and connectivity-weighted neighbor w score. ROIs with significantly higher mean ranks compared to the distribution of null ranks from 1000 surrogate maps were identified as epicenters (one-sided p_spin < 0.05, without multiple comparison correction). b Surface renderings show the group-average SV2A-PET w scores and epicenters functional connectivity (outlined in white) in Aβ+ group (n = 91). The association between SV2A-PET w score with epicenter connectivity was estimated by linear regression (p = 4.02×10⁻¹⁶, two-sided). To validate this association against the network topology, one-sided p_rewired value was identified by comparing exact β value with the null distributions from the 1000 rewired connectivity matrices. c Subject-level epicenter connectivity-based prediction of SV2A-PET w score in Aβ+ subjects. Surface rendering illustrates the overlap frequencies of subject-specific epicenter locations. Based on functional connectivity quantities to the subject-specific epicenter, the ROIs were divided into quartiles for each subject. Line charts show a gradual greater of synaptic loss across the ROIs weakly connected to the epicenters (i.e., Q1) to those strongly connected (i.e., Q4). β values and two-sided p values were estimated from linear mixed-effect regression models. d Subject-level epicenter connectivity-based prediction of SV2A-PET w score in CU Aβ- subjects (n = 54). e The epicenter probabilities were stratified according to the canonical functional networks in CU Aβ- (green line) and Aβ + (red line) groups. f A linear regression was applied for each subject to assess the association between subject-specific epicenter connectivity and SV2A-PET w-score. The subject-level regression-derived β values were compared between CU Aβ- and Aβ+ subjects using linear regression. Linear model fits are indicated with 95% confidence intervals. Boxplots are displayed as median (center line) ± interquartile range (bounds) with whiskers including observations within the 1.5 interquartile range. DMN default mode network, FPCN fronto-parietal control network, VAN ventral attention network, DAN dorsal attention network. Source data are provided in a Source data file.