Ethological computational psychiatry: Challenges and opportunities

• Published in: Current opinion in neurobiology Vol. 86; p. 102881
• Main Authors: Monosov, Ilya E., Zimmermann, Jan, Frank, Michael J., Mathis, Mackenzie W., Baker, Justin T.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.06.2024
• Subjects: Animals; Artificial Intelligence; Ethology - methods; Humans; Mental Disorders - therapy; Psychiatry - methods; Psychiatry - trends
• ISSN: 0959-4388; 1873-6882; 1873-6882
• DOI: 10.1016/j.conb.2024.102881

Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions and well-constrained behaviors over short timescales (e.g., trials, hours), many mental health conditions involve complex interactions of mood and cognition that are non-stationary across behavioral contexts and evolve over extended timescales. Here, we discuss opportunities, challenges, and possible future directions in computational psychiatry to quantify non-stationary continuously monitored behaviors. We suggest that this exploratory effort may contribute to a more precision-based approach to treating mental disorders and facilitate a more robust reverse translation across animal species. We conclude with ethical considerations for any field that aims to bridge artificial intelligence and patient monitoring. •Psychiatric disorders are non stationary, and evolve over long time scales.•They are associated with aberrant behavioral hierarchies.•New neurotechnology and analytic methods to study behavior continuously could facilitate precision neuropsychiatry.•Reverse translation across species and models is necessary to discover the disease related breakpoints in neural circuits.