netjack

netjack implements the network statistic (NS) jackknife framework to evaluate how simulated lesioning of nodes or edges affects local and global whole-brain network topology for neuroimaging studies.

Key Features:

• NS jackknife framework: Implements the network statistic (NS) jackknife framework to quantify the contribution of local elements to overall network statistics.
• Simulated lesioning: Systematically removes nodes or edges to evaluate impacts on local and global network properties.
• Integration of global and local analysis: Combines global network metrics such as global efficiency with detection of local structural differences to capture both overall and focal topological changes.
• Empirical validation: Validation has been reported using simulation studies and empirical comparisons, including analyses of global efficiency differences between children with attention-deficit/hyperactivity disorder (ADHD) and typically developing (TD) children.

Scientific Applications:

• Whole-brain network characterization: Analysis of global and local topology in structural or functional brain networks.
• Brain–behavior and cognition studies: Investigation of relationships between brain network organization and cognitive or behavioral domains.
• Clinical and developmental comparisons: Examination of disrupted network structures associated with neurological or developmental conditions, exemplified by ADHD versus TD comparisons.

Methodology:

Applies the NS jackknife framework with simulated lesioning by removing nodes or edges to assess changes in local and global network properties; validation via simulation studies and empirical comparisons is reported.