Lei Wu

SILICA-SNC: FROM STREAMLINES TO NETWORKS

SILICA-SNC transforms whole brain tractography into a network representation, revealing organized white matter architecture and coupling patterns.

Dynamic fusion of structural and functional connectivity via joint connectivity matrix ICA

This paper introduces a dynamic fusion framework to integrate structural and functional connectivity data, revealing differences between schizophrenia patients and controls.

SILICA: Streamline Independent Component Analysis for Trajectory-Resolved White Matter Decomposition

SILICA decomposes white matter tractograms into population-level statistical components while preserving individual streamline geometry, revealing recognizable brain systems and enabling trajectory-resolved visualization.

Structural connectivity-informed dynamic estimation (STRiDE): Multimodal connectivity constrained ICA

STRiDE improves dynamic brain state estimation by integrating structural and functional connectivity, revealing disruptions in schizophrenia.

Evidence for white matter intrinsic connectivity networks at rest and during a task: a large-scale study and templates

The paper presents a WM intrinsic connectivity network template derived from 100,000 fMRI scans, showing distinct WM and GM networks with task-related activity and differences in schizophrenia.

Joint cmICA: auto-linking of structural and functional connectivity

This paper introduces joint cmICA, a method that integrates structural and functional brain connectivity data to simultaneously parcellate and link cortical regions using MRI data.