Data-driven approaches to neuroimaging biomarkers for neurological and psychiatric disorders: emerging approaches and examples

doi:10.1097/WCO.0000000000000967

	Data-driven approaches to neuroimaging biomarkers for neurological and psychiatric disorders: emerging approaches and examples
	Calhoun, Vince D.1; Pearlson, Godfrey D.2; Sui, Jing1,3,4
发表期刊	CURRENT OPINION IN NEUROLOGY
ISSN	1350-7540
	2021-08-01
卷号	34 期号:4 页码:469-479
通讯作者	Calhoun, Vince D.(vcalhoun@gsu.edu)
摘要	Purpose of review The 'holy grail' of clinical applications of neuroimaging to neurological and psychiatric disorders via personalized biomarkers has remained mostly elusive, despite considerable effort. However, there are many reasons to continue to be hopeful, as the field has made remarkable advances over the past few years, fueled by a variety of converging technical and data developments. Recent findings We discuss a number of advances that are accelerating the push for neuroimaging biomarkers including the advent of the 'neuroscience big data' era, biomarker data competitions, the development of more sophisticated algorithms including 'guided' data-driven approaches that facilitate automation of network-based analyses, dynamic connectivity, and deep learning. Another key advance includes multimodal data fusion approaches which can provide convergent and complementary evidence pointing to possible mechanisms as well as increase predictive accuracy. The search for clinically relevant neuroimaging biomarkers for neurological and psychiatric disorders is rapidly accelerating. Here, we highlight some of these aspects, provide recent examples from studies in our group, and link to other ongoing work in the field. It is critical that access and use of these advanced approaches becomes mainstream, this will help propel the community forward and facilitate the production of robust and replicable neuroimaging biomarkers.
关键词	data driven data fusion dynamics multimodal neuroimaging biomarkers
DOI	10.1097/WCO.0000000000000967
关键词[WOS]	DYNAMIC FUNCTIONAL CONNECTIVITY ; HUMAN CONNECTOME PROJECT ; MULTIMODAL FUSION ; PATTERNS ; ICA ; CLASSIFICATION ; PREDICTION ; COGNITION ; SUBJECT
收录类别	SCI
语种	英语
资助项目	National Institutes of Health[R01EB006841] ; National Institutes of Health[R01MH118695] ; National Institutes of Health[R01MH117107] ; National Institutes of Health[RF1AG063153]
项目资助者	National Institutes of Health
WOS研究方向	Neurosciences & Neurology
WOS类目	Clinical Neurology ; Neurosciences
WOS记录号	WOS:000670005200001
出版者	LIPPINCOTT WILLIAMS & WILKINS
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/45262
专题	脑图谱与类脑智能实验室_脑网络组研究
通讯作者	Calhoun, Vince D.
作者单位	1.Emory Univ, Triinst Ctr Translat Res Neuroimaging & Data Sci, Georgia State Univ, Georgia Inst Technol, Atlanta, GA 30322 USA 2.Yale Sch Med, Dept Psychiat & Neurosci, New Haven, CT USA 3.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Calhoun, Vince D.,Pearlson, Godfrey D.,Sui, Jing. Data-driven approaches to neuroimaging biomarkers for neurological and psychiatric disorders: emerging approaches and examples[J]. CURRENT OPINION IN NEUROLOGY,2021,34(4):469-479.
APA	Calhoun, Vince D.,Pearlson, Godfrey D.,&Sui, Jing.(2021).Data-driven approaches to neuroimaging biomarkers for neurological and psychiatric disorders: emerging approaches and examples.CURRENT OPINION IN NEUROLOGY,34(4),469-479.
MLA	Calhoun, Vince D.,et al."Data-driven approaches to neuroimaging biomarkers for neurological and psychiatric disorders: emerging approaches and examples".CURRENT OPINION IN NEUROLOGY 34.4(2021):469-479.