利用转化神经科学方法了解焦虑的异质性。

IF 2.5 3区 医学 Q2 BEHAVIORAL SCIENCES
Carly M Drzewiecki, Andrew S Fox
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引用次数: 0

摘要

焦虑症影响着全球数百万人,由于其临床表现具有很大的异质性,因此给神经科学研究带来了挑战。虽然人们在理解恐惧和焦虑的神经生物学方面取得了很大进展,但这些见解并没有带来有效的治疗方法。了解表型异质性与潜在生物学之间的关系是解决这一问题的关键第一步。我们展示了翻译、反向翻译和计算建模可以促进对恐惧和焦虑以及焦虑症的精细化、跨物种理解。更具体地说,我们概述了如何利用动物模型,通过有针对性的跨物种方法和符合伦理学的行为范式,在人类中提出可检验的假设。我们讨论了反向转化方法,这些方法可以指导非传统研究物种的动物研究并确定其优先次序。最后,我们提倡使用计算模型来协调对焦虑的跨物种和跨方法研究。总之,这种转化神经科学方法将有助于弥合我们目前在焦虑症的概念和诊断方法上不断扩大的差距,并有助于发现更好的焦虑症治疗方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Understanding the heterogeneity of anxiety using a translational neuroscience approach.

Understanding the heterogeneity of anxiety using a translational neuroscience approach.

Anxiety disorders affect millions of people worldwide and present a challenge in neuroscience research because of their substantial heterogeneity in clinical presentation. While a great deal of progress has been made in understanding the neurobiology of fear and anxiety, these insights have not led to effective treatments. Understanding the relationship between phenotypic heterogeneity and the underlying biology is a critical first step in solving this problem. We show translation, reverse translation, and computational modeling can contribute to a refined, cross-species understanding of fear and anxiety as well as anxiety disorders. More specifically, we outline how animal models can be leveraged to develop testable hypotheses in humans by using targeted, cross-species approaches and ethologically informed behavioral paradigms. We discuss reverse translational approaches that can guide and prioritize animal research in nontraditional research species. Finally, we advocate for the use of computational models to harmonize cross-species and cross-methodology research into anxiety. Together, this translational neuroscience approach will help to bridge the widening gap between how we currently conceptualize and diagnose anxiety disorders, as well as aid in the discovery of better treatments for these conditions.

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来源期刊
CiteScore
5.00
自引率
3.40%
发文量
64
审稿时长
6-12 weeks
期刊介绍: Cognitive, Affective, & Behavioral Neuroscience (CABN) offers theoretical, review, and primary research articles on behavior and brain processes in humans. Coverage includes normal function as well as patients with injuries or processes that influence brain function: neurological disorders, including both healthy and disordered aging; and psychiatric disorders such as schizophrenia and depression. CABN is the leading vehicle for strongly psychologically motivated studies of brain–behavior relationships, through the presentation of papers that integrate psychological theory and the conduct and interpretation of the neuroscientific data. The range of topics includes perception, attention, memory, language, problem solving, reasoning, and decision-making; emotional processes, motivation, reward prediction, and affective states; and individual differences in relevant domains, including personality. Cognitive, Affective, & Behavioral Neuroscience is a publication of the Psychonomic Society.
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