Machine Learning in the Assessment of the Nomological Organization of Traits

This paper discusses the applicability of trait theory within the field of neuroscience. Trait theory holds a strong tradition in contemporary psychology, bridging with clinical psychology, neuroscience, and most psychotherapeutic modalities. Unsupervised machine learning techniques applied to the evaluation of hybrid data (psychometric, neuroimaging, and others) demonstrate greater sensitivity and precision in capturing personality structure in the context of brain connectivity research. From a translational standpoint, we interpret trait constructs as components of a broader nomological network, reflecting stable patterns of association.