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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
眯眯眼的霸完成签到 ,获得积分10
刚刚
Orange的应助被欢呼摇伽采纳,获得20
1秒前
zhangyanci发布了新的文献求助10
2秒前
Lila完成签到 ,获得积分10
3秒前
脑洞疼的应助被阳光的山雁采纳,获得10
3秒前
4秒前
小王完成签到 ,获得积分10
5秒前
852的应助被暖暖采纳,获得10
7秒前
未来完成签到,获得积分10
7秒前
科研通AI6.2的应助被Amber采纳,获得10
8秒前
9秒前
烧饼拌糖完成签到,获得积分10
9秒前
今后的应助被赞赞采纳,获得10
9秒前
沉静亦寒完成签到,获得积分10
11秒前
12秒前
现代的迎海完成签到,获得积分10
13秒前
13秒前
开心绿草完成签到 ,获得积分10
13秒前
14秒前
jiangsu发布了新的文献求助10
14秒前
高兴书兰完成签到,获得积分20
14秒前
Nole的应助被zhangyanci采纳,获得10
15秒前
15秒前
15秒前
怀民已就寝完成签到,获得积分10
18秒前
18秒前
19秒前
19秒前
小马甲的应助被109upup采纳,获得10
19秒前
20秒前
20秒前
NGU发布了新的文献求助10
21秒前
刘恩瑜发布了新的文献求助10
21秒前
21秒前
21秒前
沙漠完成签到,获得积分10
22秒前
Zhu完成签到,获得积分10
23秒前
24秒前
科研通AI6.2的应助被astroecho采纳,获得10
25秒前
思源的应助被109upup采纳,获得10
25秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 1000
Questions on Teacher Wellbeing 600
Guidelines for fracture-safe and fatigue-reliable design of steel structures 600
The Basics of Practical Optimization, Second Edition 600
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization 600
Organizational Behavior 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 7987880
求助须知:如何正确求助?哪些是违规求助? 9445884
关于积分的说明 21101458
捐赠科研通 7562031
什么是DOI,文献DOI怎么找? 3377779
关于科研通互助平台的介绍 2511644
邀请新用户注册赠送积分活动 2411070