International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2026
Task-evoked brain network dynamics underlying executive function in preadolescent children.
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Parvez Alfia, Verma Shreya, Liu Ruyu, Reeser Ginger, Mullen Sean P, Raine Lauren B, Renzi-Hammond Lisa, Hillman Charles H, Khan Naiman A
Аннотация
OBJECTIVE: Executive function (EF) has been studied using functional magnetic resonance imaging (fMRI) based functional connectivity (FC); however, electroencephalography (EEG) based dynamic FC interactions supporting EF in children and explaining behavioral performance remain underexplored. We used EEG to examine FC within and between seven core brain networks: Default Mode (DMN), Dorsal Attention (DAN), Ventral Attention (VAN), Somatomotor (SMN), Frontoparietal (FPN), Visual (VIN), and Limbic (LIN), during a modified Eriksen flanker task. We aimed to identify dynamic network configurations linked to EF, specifically selective attention and inhibitory control in preadolescent children (8-10 years).
METHODS: Secondary analyses of source-localized EEG data from 84 children (mean age 8.89 ± 0.82 years; 51.2% female) were conducted. A Hidden Markov model extracted spatiotemporal dynamics, quantifying within- and between-network FC correlations. Support vector regression (SVR) with an interpretable kernel identified connectivity patterns predicting behavioral outcomes, including accuracy and reaction time (RT) interference.
RESULTS: SVR moderately predicted Accuracy Interference (RMSE = 6.51, R2 = 0.48) and RT Interference (RMSE = 31.42, R2 = 0.26). Behavioral performance indices were most strongly associated with interference within VAN, DMN, SMN, and VIN. Notably, within-VAN FC explained between-subject variability in both Accuracy Interference (ρ = -0.28, p = 0.012) and RT Interference (r = 0.26, p = 0.017).
CONCLUSIONS: Dynamic, task-based FC, particularly within-VAN, underpins individual differences in EF among preadolescent children. Stronger within-VAN reconfiguration during high cognitive demand trials supported accuracy but at the cost of slower responses, highlighting a trade-off between stability and efficiency in developing EF.
METHODS: Secondary analyses of source-localized EEG data from 84 children (mean age 8.89 ± 0.82 years; 51.2% female) were conducted. A Hidden Markov model extracted spatiotemporal dynamics, quantifying within- and between-network FC correlations. Support vector regression (SVR) with an interpretable kernel identified connectivity patterns predicting behavioral outcomes, including accuracy and reaction time (RT) interference.
RESULTS: SVR moderately predicted Accuracy Interference (RMSE = 6.51, R2 = 0.48) and RT Interference (RMSE = 31.42, R2 = 0.26). Behavioral performance indices were most strongly associated with interference within VAN, DMN, SMN, and VIN. Notably, within-VAN FC explained between-subject variability in both Accuracy Interference (ρ = -0.28, p = 0.012) and RT Interference (r = 0.26, p = 0.017).
CONCLUSIONS: Dynamic, task-based FC, particularly within-VAN, underpins individual differences in EF among preadolescent children. Stronger within-VAN reconfiguration during high cognitive demand trials supported accuracy but at the cost of slower responses, highlighting a trade-off between stability and efficiency in developing EF.