BCCT: A GUI Toolkit for Brain Structural Covariance Connectivity Analysis on MATLAB

Area of Science:

• Neuroscience
• Computational Neuroscience
• Brain Imaging Analysis

Background:

• Brain structural covariance networks (SCN) reveal synchronized, long-range alterations in brain structure.
• SCN applications are crucial for understanding cognition and neuropsychiatric disorders.
• Advanced SCN techniques include causal analysis (CaSCN), winner-take-all cortex-subcortex analysis (WTA-CSSCN), and modulation analysis (MOD-SCN).

Purpose of the Study:

• To address the limited application of SCN due to a lack of user-friendly software.
• To develop a graphical user interface (GUI) toolkit for comprehensive brain structural covariance connectivity analysis.
• To facilitate easier application of SCN, CaSCN, MOD-SCN, and WTA-CSSCN, particularly for clinical researchers.

Main Methods:

• Development of a MATLAB-based graphical user interface (GUI) toolkit.
• Integration of analysis modules for SCN, CaSCN, MOD-SCN, and WTA-CSSCN.
• Inclusion of group comparison and results visualization modules, with a demo dataset provided.

Main Results:

• A novel GUI toolkit for brain structural covariance connectivity analysis has been successfully developed.
• The toolkit integrates multiple advanced SCN analysis methods (SCN, CaSCN, MOD-SCN, WTA-CSSCN).
• The software includes essential modules for group comparisons and result presentation.

Conclusions:

• The developed MATLAB toolkit significantly enhances the accessibility and application of brain structural covariance network analysis.
• This tool is expected to empower researchers, especially in clinical settings, to conduct sophisticated brain connectivity studies more efficiently.
• The toolkit promotes wider adoption of advanced SCN methodologies in neuroscience research.