Age-Related Differences in Neural Networks for Error Detection and Inhibitory Control: A LORETA-Based Comparative Study

BACKGROUND/OBJECTIVES: Assessing inhibitory function and error detection is crucial for the early detection of age-related cognitive decline. This study aimed to investigate the neural network dynamics underlying these functions in younger and older adults to better understand age-related changes in cognitive control. METHODS: We recorded electroencephalograms (EEGs) during an inhibitory control task in 17 older and 15 younger healthy adults. Behavioral performance was assessed, and directional functional connectivity was analyzed using Low-Resolution Electromagnetic Tomography (LORETA), isolated effective coherence (iCoh), and Full Vector Field analysis across the theta, alpha, and beta frequency bands. RESULTS: Older adults showed significantly fewer correct responses than younger adults. During incorrect responses, older adults exhibited strong beta-band directionality from the ventral anterior cingulate cortex (ACC) to the left frontal polar cortex (FPC), alongside strong intra-ACC connectivity. During correct responses, they demonstrated alpha- and beta-band directionality from the left dorsolateral prefrontal cortex (DLPFC) to the right FPC. Conversely, compared with older adults, younger adults demonstrated significantly stronger mutual directionality within the ACC and widespread robust connectivity among the ACC, bilateral DLPFC, and FPC during correct responses. CONCLUSIONS: Efficient inhibitory control in older adults appears to rely on higher-order error-monitoring and error detection networks. The altered network dynamics in older adults suggest an age-related decline in immediate cognitive control. Evaluating these neural networks via EEGs provides a potential non-invasive biomarker for early cognitive decline and highlights higher-order executive control as a promising target for preventive interventions.