Singh Manpreet K, Gotlib Ian H
Stanford University School of Medicine, United States.
Department of Psychology, Stanford University, United States.
Behav Res Ther. 2014 Nov;62:60-73. doi: 10.1016/j.brat.2014.08.008. Epub 2014 Sep 4.
Major Depressive Disorder (MDD) is among the most prevalent of all psychiatric disorders and is the single most burdensome disease worldwide. In attempting to understand the profound deficits that characterize MDD across multiple domains of functioning, researchers have identified aberrations in brain structure and function in individuals diagnosed with this disorder. In this review we synthesize recent data from human neuroimaging studies in presenting an integrated neural network framework for understanding the impairments experienced by individuals with MDD. We discuss the implications of these findings for assessment of and intervention for MDD. We conclude by offering directions for future research that we believe will advance our understanding of neural factors that contribute to the etiology and course of depression, and to recovery from this debilitating disorder.
重度抑郁症（MDD）是所有精神疾病中最常见的疾病之一，也是全球负担最重的单一疾病。为了试图理解在多个功能领域中表征MDD的严重缺陷，研究人员已经确定了被诊断患有这种疾病的个体大脑结构和功能的异常。在本综述中，我们综合了来自人类神经影像学研究的最新数据，提出了一个综合神经网络框架，以理解MDD患者所经历的损伤。我们讨论了这些发现对MDD评估和干预的意义。我们通过为未来研究提供方向来结束本文，我们相信这些研究将推进我们对导致抑郁症病因和病程以及从这种使人衰弱的疾病中康复的神经因素的理解。
