If you find this work interesting, and would like to know more about how we use modeling and NLP to uncover semantic processes and mentalization in interacting individuals, please get in touch or see our lab website sites.google.com/view/thought...

I want to thank my amazing collaborators, Ray Dolan, Rani Moran, @drrickadams.bsky.social, and Noam Siegelman, Max Planck Centre for Computational Psychiatry, Editor and reviewers at Nature Mental Health, as well as the EU Horizon 2020 MSCA-IF program for supporting this work.

Our findings also extend previous work using NLP to characterize language incoherence in psychosis in a large, general population sample, thereby allowing for rigorous testing of the psychometric properties of different NLP measures.

Our finding that alterations in speech and thought are relatively specific is striking given the ubiquity of transdiagnostic findings in psychopathology. Notably, the relevant dimensions were distinctly interpersonal, reflecting the inherently social nature of language.

Whereas Formal Thought Disorder, prevalent in psychosis, is usually diagnosed based on speech incoherence, computational modeling of associative output allowed us to uncover disorganized semantic retrieval as a core mechanism, evident even when language output is intact.

Our findings suggest a core mechanism underlying language incoherence in psychosis is more widespread than commonly assumed, while also showing notable specificity to particular dimensions of psychopathology.

We aimed to map alterations in thought and discourse across dimensions of psychopathology and detail their underlying mechanisms. We combine a transdiagnostic approach, inspired by @clairegillan.bsky.social, @tobywise.bsky.social, and others, with NLP and comp. modeling of associative thinking.