摘要
How does task complexity influence cognitive performance and neural dynamics, and how do individual differences shape these effects? We employed a two-stage arithmetic load verification task to investigate the impacts of increasing cognitive load on accuracy, reaction time (RT), inverse efficiency scores (IES), and neural activity indexed by P300 and frequency-band dynamics. Participants completed tasks of varying complexity (low, intermediate, and high) and were categorized as high-performing (HG) or low-performing (LG) based on task outcomes of the pilot study. Behavioral results showed that increasing task complexity reduced accuracy, slowed RT, and elevated IES. Electrophysiological analyses revealed phase-specific patterns: during the problem presentation stage, P300 amplitudes showed anterior-central dominance without cognitive load effects; HG exhibited smaller amplitudes than LG, while LG displayed decreasing frontal theta and alpha power with increasing load—indicating attentional limitations. During the response evaluation stage, P300 amplitudes exhibited a robust cognitive load effect (low > intermediate > high) and posterior dominance, but no group differences. Theta and alpha power at Cz predicted accuracy under intermediate load. Together, these findings demonstrate complementary contributions of ERP and oscillatory measures in tracking neural resource allocation and adaptability, thereby extending cognitive load theory.
•P300 shifted from anterior-central to posterior sites between problem presentation and response evaluation.•High performers showed smaller P300, while low performers had reduced frontal theta–alpha with increasing load.•Theta–alpha at Cz predicted accuracy, highlighting complementary roles of ERP and spectral measures.