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网络神经科学:精神医学中生物标志物开发的框架。

Network Neuroscience: A Framework for Developing Biomarkers in Psychiatry.

作者信息

Lydon-Staley David M, Bassett Danielle S

机构信息

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.

Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

Curr Top Behav Neurosci. 2018;40:79-109. doi: 10.1007/7854_2018_41.

Abstract

Psychiatric disorders are disturbances of cognitive and behavioral processes mediated by the brain. Emerging evidence suggests that accurate biomarkers for psychiatric disorders might benefit from incorporating information regarding multiple brain regions and their interactions with one another, rather than considering local perturbations in brain structure and function alone. Recent advances in the field of applied mathematics generally - and network science specifically - provide a language to capture the complexity of interacting brain regions, and the application of this language to fundamental questions in neuroscience forms the emerging field of network neuroscience. This chapter provides an overview of the use and utility of network neuroscience for building biomarkers in psychiatry. The chapter begins with an overview of the theoretical frameworks and tools that encompass network neuroscience before describing applications of network neuroscience to the study of schizophrenia and major depressive disorder. With reference to work on genetic, molecular, and environmental correlates of network neuroscience features, the promises and challenges of network neuroscience for providing tools that aid in the diagnosis and the evaluation of treatment response in psychiatric disorders are discussed.

摘要

精神障碍是由大脑介导的认知和行为过程的紊乱。新出现的证据表明,精神障碍的准确生物标志物可能受益于纳入有关多个脑区及其相互作用的信息,而不是仅考虑脑结构和功能的局部扰动。一般应用数学领域,特别是网络科学领域的最新进展提供了一种语言来捕捉相互作用的脑区的复杂性,并且将这种语言应用于神经科学的基本问题形成了新兴的网络神经科学领域。本章概述了网络神经科学在精神病学中构建生物标志物的用途和效用。本章首先概述了涵盖网络神经科学的理论框架和工具,然后描述了网络神经科学在精神分裂症和重度抑郁症研究中的应用。参考关于网络神经科学特征的遗传、分子和环境相关性的研究,讨论了网络神经科学在提供有助于精神障碍诊断和治疗反应评估工具方面的前景和挑战。

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