神经科学中受试者内相关性的偏最小二乘法

Partial least squares correlation (PLSC) is a multivariate technique used in neuroscience to capture patterns of relationships between neural data and covariates of interest. Conventionally, PLSC captures between-subjects correlations (e.g., between average neural activation and average task performance). However, within-subject correlations (e.g., trial-by-trial relationships between neural activation and subjective ratings or stimulus attributes) are often of interest as well. Thus, we introduce an extension of PLSC to capture within-subject correlations. We validate this approach against re