Neurobridge Koopman Dynamics

Abstract

Early identification of adolescents at risk for substance use initiation (SUI) is vital yet difficult, as most predictors treat connectivity as static or cross-sectional and miss how brain networks change over time and with behavior. We proposed NeuroBRIDGE (Behavior conditioned RIemannian Koopman Dynamics on lonGitudinal connEctomes), a novel graph neural network-based framework that aligns longitudinal functional connectome in a Riemannian tangent space and couples dual-time attention with behavioral-conditioned Koopman dynamics to capture temporal change. Evaluated on ABCD, NeuroBRIDGE improved future SUI prediction over relevant baselines while offering interpretable insights into neural pathways, refining our understanding of neurodevelopmental risk and informing targeted prevention.

Key Contributions

1. Novel Methodology: Advanced techniques for neuroscience analysis
2. Practical Applications: Real-world implementation strategies
3. Theoretical Insights: Computational neuroscience foundations

Activation Keywords

• • neurobridge
• koopman dynamics
• riemannian alignment
• functional connectome
• longitudinal
• substance use
• brain prediction

Implementation Pattern

# Example implementation based on paper methodology
# Note: This is a conceptual implementation
# Refer to the original paper for complete details

def analyze_brain_data(data, method="neurobridge_koopman_dynamics"):
    """
    Apply NeuroBRIDGE: Koopman Dynamics for Brain Connectome Prediction methodology
    
    Args:
        data: Neural recording data (EEG, fMRI, calcium imaging, etc.)
        method: Analysis method to apply
    
    Returns:
        Analysis results
    """
    # Implementation based on paper
    pass

Applications

• Brain-computer interfaces (BCI)
• Neural signal processing
• Cognitive neuroscience research
• Computational modeling
• Medical diagnosis support

Limitations

• Based on specific experimental conditions from the paper
• May require adaptation for different data types
• Computational requirements depend on implementation

References

• NeuroBRIDGE: Behavior-Conditioned Koopman Dynamics with Riemannian Alignment for Early Substance Use Initiation Prediction from Longitudinal Functional Connectome. Badhan Mazumder, Sir-Lord Wiafe, Vince D. Calhoun, Dong Hye Ye. arXiv:2603.29960v1, 2026-03-31.

Related Skills

• Other neuroscience skills in the collection
• Brain network analysis tools
• Neural dynamics modeling

See Also

• arXiv:2603.29960v1
• Computational Neuroscience resources
• Brain connectivity analysis methods