traced-activation-cascade-analysis

To identify minimal edge weight changes for brain activation cascade differences, you can use TRACED root-cause analysis. It finds the smallest set of connectome graph edge weight changes explaining activation cascade differences between two groups, outputting a validated minimal explanatory edge set.

A linear-threshold model in connectome activation cascade analysis simulates how activation spreads through brain networks. TRACED requires activation cascade data generated with this model, alongside group-specific connectome graphs, to perform root-cause analysis on network perturbations.

Yes, you can use connectome perturbation analysis for clinical group comparisons like MDD versus healthy controls. TRACED maps minimal explanatory edge changes to brain regions and functional implications, making it suitable for clinical studies and pre/post treatment analyses.

To run root-cause analysis on brain network activation cascades, you need activation cascade data generated with a linear-threshold model and group-specific connectome graphs. TRACED processes these inputs to output a minimal explanatory edge set with validation.

Yes, TRACED outputs validation for the minimal explanatory edge set in connectome graphs. It identifies the smallest edge weight changes explaining cascade differences between groups and provides validation to ensure the reliability of the root-cause analysis results.