Clinical Promise of Brain-Phenotype Modeling

神经科学 表型 神经影像学 心理学 计算模型 计算机科学 生物 人工智能 生物化学 基因
作者
Abigail S. Greene,R. Todd Constable
出处
期刊:JAMA Psychiatry [American Medical Association]
卷期号:80 (8): 848-848 被引量:17
标识
DOI:10.1001/jamapsychiatry.2023.1419
摘要

Importance: Assessing the link between whole-brain activity and individual differences in cognition and behavior has the potential to offer insights into psychiatric disorder etiology and change the practice of psychiatry, from diagnostic clarification to intervention. To this end, recent application of predictive modeling to link brain activity to phenotype has generated significant excitement, but clinical applications have largely not been realized. This Review explores explanations for the as yet limited practical utility of brain-phenotype modeling and proposes a path forward to fulfill this clinical potential. Observations: Clinical applications of brain-phenotype models are proposed and will require coordinated collaboration across the relatively siloed fields of psychometrics and computational neuroscience. Such interdisciplinary work will maximize the reliability and validity of modeled phenotypic measures, ensuring that resulting brain-based models are interpretable and useful. The models, in turn, may shed additional light on the neurobiological systems into which each phenotypic measure taps, permitting further phenotype refinement. Conclusions and Relevance: Together, these observations reflect an opportunity: bridging the divide between phenotypic measure development and validation and measure end use for brain-phenotype modeling holds the promise that each may inform the other, yielding more precise and useful brain-phenotype models. Such models can in turn be used to reveal the macroscale neural bases of a given phenotype, advancing basic neuroscientific understanding and identifying circuits that can be targeted (eg, via closed-loop neurofeedback or brain stimulation) to slow, reverse, or even prevent functional impairment.
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