Distance-based integration of ERP correlation analysis

Abstract

Interpretation of cognitive performance is a paramount pursuit in learning achievements. Cognitive abilities, encompassing attention, memory, decision-making, and language comprehension, are recognized on individual's capacity to navigate in diverse cognitive tasks. In the academic domain, optimal cognitive functioning is essential for effective learning, information retention, and problem-solving. Proficiency in cognitive skills is directly linked to academic success and intellectual development, providing the necessary cognitive tools for processing, and synthesizing complex information. Therefore, this study explores the correlation between event-related potential (ERP) sub-components (P300, N170, N400) to assess the intricacies of cognitive performance. A regularized approach utilizing Spearman's Rank Correlation Coefficient and Euclidean Distance is employed. Positive correlations reveal consistent relationships among P300, N170, and N400 ranks across EEG channels, indicating similar response patterns. Negative correla-tions denote inverse relationships. Moreover, the theoretical framework focuses on the digital filtering, ensemble averaging, and baseline correction from data con-trast discrimination tasks. Findings indicate positive correlations, suggesting higher ERP amplitudes correspond to superior cognitive performance. This tailored and integrated methodology, indicating the correlation between ERP sub-components, contributes to the broader field of neuroscience and informatics, potentially informing cognitive enhancement strategies in education and biomedical analysis.