Early Preconfiguration Failure: A Novel Predictor of the Repetitive Subconcussion
Jiajia Li, Zhenzhen Yu, Zhenghao Fu, Guozheng Xu, Jian Song

TL;DR
This study presents a novel EEG-based method to early diagnose repetitive subconcussive brain injuries by analyzing millisecond-level cortical dynamics, outperforming traditional imaging techniques.
Contribution
It introduces a new approach combining dynamic hierarchical spatial features and cortical time-domain sensitivity for early detection of rSC injuries.
Findings
Distinct temporal patterns differentiate HC and rSC in early cortical responses.
Reduced integration levels indicate impaired pre-configuration dynamics in rSC patients.
Machine learning effectively classifies HC, rSC, and cTBI based on early cortical features.
Abstract
Early diagnosis and assessment of repetitive subconcussive (rSC) brain injuries are crucial for early clinical intervention. Conventional methods, largely relying on slow fMRI, fail to capture millisecond-level early cortical dynamics, particularly spatiotemporal features associated with pre-configuration dynamics. This study introduces a novel approach integrating dynamic hierarchical spatial features and cortical early behavioral time-domain sensitivity, utilizing EEG and visual attention tasks. We analyzed cortical early behaviors in 24 healthy controls (HC), 21 rSC patients,and a validation cohort of 25 cTBI patients from public datasets. Results reveal distinct temporal patterns in HC: elevated integration at 0-100 ms, rebound dynamics at 100-200ms, and visual perception integration peaks at 200-600 ms. In contrast, rSC patients exhibited significantly impaired dynamic features,…
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