Using machine learning and Hidden Markov Models, this research analyzes the authorship of disputed New Testament letters. The results show that stylistic differences reflect the Apostle Paul’s versatile writing styles rather than forgery, demonstrating how modern computational tools can help recover long-standing historical truths.

This research proposes that psychotherapy works by reshaping cognitive maps in the brain, much like navigation. In depression, these maps become narrow and repetitive. By analyzing therapy language and concept networks, this work aims to make therapy more precise—helping clinicians visualize mental “stuck points” and guide patients toward healthier paths.