Dynamic Network Disruption under Cognitive Strain: Coupling of Local Node Failure and Global Edge Integrity Reveals Differential Systemic Resilience
Keywords:
Neuro Feedback, Eeg Neuro Analytics, Network Analysis, Machine Learning, Cognitive Resilience, Arousal Index.Abstract
Objective: To investigate how systemic resilience to cognitive stress differs between Normal and Abnormal individuals by analyzing the dynamic coupling between local Resource Management (Node Status) and global Information Flow (Edge Function) in the brain's functional network. Methods: We analyzed 19-channel EEG data during a 12-question arithmetic task 30 epochs). CAR pre-processing was used. Node Status (resource depletion) was traced via Frontal Alpha Power (µV2) at Fz. Edge Function (systemic integrity) was quantified by the Arousal Index and Alpha/Theta Ratio (ATR).
Results: The Normal network exhibited acute vulnerability: Edge Integrity (Arousal) dropped 28.85% Q1 - Q11, coupled to an acute 76.47% deactivation of the Fz Node. The Abnormal network maintained a relatively stable Fz node despite a larger overall reduction in vigilance ATR - 44.00%. This reveals two distinct systemic failure modes.
Conclusion: Differences in systemic resilience are determined by resource management architecture. The Normal network's high-risk strategy leads to rapid, acute systemic failure—a phenomenon analogous to non-compensated circulatory collapse.
