Ethological computational psychiatry: Challenges and opportunities

Ilya E. Monosov, Jan Zimmermann, Michael J. Frank, Mackenzie W. Mathis, Justin T. Baker

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

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.

Original languageEnglish
Article number102881
JournalCurrent Opinion in Neurobiology
Volume86
DOIs
StatePublished - Jun 2024

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