TY - JOUR
T1 - Ethological computational psychiatry
T2 - Challenges and opportunities
AU - Monosov, Ilya E.
AU - Zimmermann, Jan
AU - Frank, Michael J.
AU - Mathis, Mackenzie W.
AU - Baker, Justin T.
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/6
Y1 - 2024/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85191780650&partnerID=8YFLogxK
U2 - 10.1016/j.conb.2024.102881
DO - 10.1016/j.conb.2024.102881
M3 - Review article
C2 - 38696972
AN - SCOPUS:85191780650
SN - 0959-4388
VL - 86
JO - Current Opinion in Neurobiology
JF - Current Opinion in Neurobiology
M1 - 102881
ER -