Fig. 5: Opposing effects on gradient dynamics between structural connectivity and ascending neuromodulatory system.
From: Multimodal analysis demonstrating the shaping of functional gradients in the marmoset brain
a Pipeline for the dynamic function gradients prediction. Briefly, we fitted the empirical dynamic function connectivity (dFC) frame-by-frame utilizing the same GLM strategy as Fig. 4a. After binned by the arousal index, the predicted dFC matrices were averaged and projected into dynamic function gradients, respectively. b Predicted dynamic function gradients and corresponding explained variances (Full model). Details were shown in Supplementary Fig. 23. c Arousal relevant flow of each network in gradient space (Full model). Arrow reflected the direction of the shift along with arousal dynamics. d, e As in (b) but for the unique distribution of structure connectivity (d) and neuromodulatory similarity (e), respectively. f, g As in (c) but for the unique distribution of each predictor. Notably, the flow of arrows was in an opposite way between structure connectivity f and neuromodulatory similarity g. h Conceptual summary of the underlying basis of complex global functional processing in large scale cortical organization. Source data are provided as a Source Data file.
