Cormotif

Cormotif identifies statistically overabundant motifs in multi-layer brain networks by integrating structural connectivity from diffusion imaging and functional connectivity from functional magnetic resonance imaging (fMRI) to analyze relationships between anatomical connections and correlated neural activity.

Key Features:

• Multi-Layer Network Analysis: Extends motif analysis to multiplex networks by modeling and jointly considering structural (anatomical) and functional (activity correlation) layers.
• Motif Classification: Classifies subgraphs within multiplex networks and detects statistically overabundant motifs that represent significant connectivity patterns.
• Integration of Imaging Data: Integrates diffusion imaging (anatomical) and functional magnetic resonance imaging (fMRI) data to construct the structural and functional layers of brain networks.
• Reinforcement Mechanism Investigation: Analyzes reinforcement between structural and functional layers by quantifying how the presence of links in one layer influences connections in the other, revealing anatomical constraints on functional connectivity.

Scientific Applications:

• Neuroscience Research: Supports investigation of relationships between brain structure and function to aid identification of central areas and organizational principles of neural systems.
• Brain Network Analysis: Enables detection of fundamental building blocks of neural systems by revealing overabundant multi-layer motifs and their role in network dynamics.

Methodology:

Employs a mathematical framework for multi-layer (multiplex) networks to classify subgraphs and extend motif analysis across layers, integrating diffusion imaging and fMRI to identify motifs where anatomical connections co-occur with correlated activity and assessing motif overabundance for statistical significance.