重度抑郁症患者治疗前后脑功能及结构的MRI研究进展

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李海东王峻牛金亮

Cite this article as: Li HD, Wang J, Niu JL. MRI research progress of brain function and structure in patients with major depressive disorder before and after treatment[J]. Chin J Magn Reson Imaging, 2022, 13(3): 143-146.本文引用格式：李海东, 王峻, 牛金亮. 重度抑郁症患者治疗前后脑功能及结构的MRI研究进展[J]. 磁共振成像, 2022, 13(3): 143-146. DOI:10.12015/issn.1674-8034.2022.03.035.

摘要

[摘要] 重度抑郁症(major depressive disorder，MDD)是由多种因素导致的精神疾病，可引起情绪低落及认知功能受损等症状，抗抑郁治疗前后存在大脑功能和结构的不同改变。MRI有助于进一步确定MDD相关症状的神经病理生理机制。研究发现未治疗MDD患者前额叶、扣带回、楔前叶及海马等脑区的神经活动减低，默认模式网络(default mode network，DMN)、中央执行网络(central executive network，CEN)及显著性网络(salience network，SN)功能连接增强，灰质体积减小、白质结构损伤，抗抑郁药物治疗后部分脑区神经活动增加，脑网络功能连接及灰、白质结构正常化。本文综述MDD治疗前后的MRI脑功能及结构改变，为早期诊断及抗抑郁药物疗效评估提供客观影像学依据。

[Abstract] Major depressive disorder (MDD) is a psychiatric disorder that is caused by varieties of factors, which can result in symptoms such as upset and cognitive impairment. Different changes in brain function and structure exist before and after antidepressant treatment. MRI can further identify the neuropathophysiological mechanisms associated with the symptoms of MDD. Recent drug-naive MDD studies have shown decreased regional brain activity in prefrontal cortex, cingulate, precuneus, hippocampus and increased functional connectivity in default mode network (DMN), central executive network (CEN), salience network (SN). These studies also exhibite the reduction of gray matter volume and disruption of white matter simultaneously. Post-treatment studies display increased brain activity in partial brain regions, which also indicate the normalization in DMN, CEN, SN, gray matter volume and white matter structure. This paper reviews the effects of major depressive disorder before and after antidepressant treatment from the perspective of functional and structural MRI to provide objective reference information for early diagnosis and curative effect evaluation.

[关键词] 重度抑郁症；磁共振成像；脑结构；脑功能；机制；抗抑郁药物治疗；影像标志物

[Keywords] major depressive disorder；magnetic resonance imaging；brain structure；brain function；mechanism；antidepressant therapy；imaging marker

作者信息

李海东 ¹ 王峻 ² 牛金亮 ^2*

¹ 山西医科大学医学影像学院，太原　030001

² 山西医科大学第二医院磁共振室，太原　030001

牛金亮，E-mail：sxlscjy@163.com

作者利益冲突声明：全部作者均声明无利益冲突。

出版信息

基金项目： 国家自然科学基金 82071898 山西省卫生健康委员会专项科技项目 2020-1

收稿日期：2021-11-25

接受日期：2022-03-14

中图分类号：R445.2 R749.4

文献标识码：A

DOI: 10.12015/issn.1674-8034.2022.03.035

本文引用格式：李海东, 王峻, 牛金亮. 重度抑郁症患者治疗前后脑功能及结构的MRI研究进展[J]. 磁共振成像, 2022, 13(3): 143-146. DOI:10.12015/issn.1674-8034.2022.03.035.

正文

重度抑郁症(major depressive disorder，MDD)是以认知、情绪障碍及心情低落为特征的常见精神疾病^[¹^]，目前诊断和预后评估主要依据患者症状和行为的现象学评估、他评及自评量表等。MRI能定量分析MDD功能及结构异常，抗抑郁药物治疗MDD会引起相关脑组织功能及结构的变化。本文综述MDD治疗前后磁共振功能及结构的改变，以进一步提高对该疾病的认识。

1 MDD的发病机制及治疗方法

MDD的发病与生物化学、遗传、社会及环境等因素有关，涉及多种神经递质、脑区及环路的异常。发病机制主要有：(1)单胺类神经递质缺乏及受体敏感性异常^[²^]。5-羟色胺(5-hydroxytryptamine，5-HT)、去甲肾上腺素(noradrenalin，NE)、多巴胺(dopamine，DA)等神经递质缺乏及脑中5-HT、NE受体敏感性增高是MDD重要的发病机制，上述三种单胺的主要来源分别是中缝核、蓝斑、黑质和腹侧被盖区^[³^]。中缝核血清素能神经元投射到尾状核、壳核、苍白球、杏仁核、边缘前脑和新皮质，5-HT负责积极性、情绪压力处理及其他边缘功能的调节。蓝斑分泌的NE是参与学习、记忆、情绪、睡眠、食欲和神经内分泌功能神经回路的关键递质^[³^]。黑质和腹侧被盖区主要投射到伏隔核和腹侧纹状体，是大脑奖励系统的枢纽，参与调节负面情绪的刺激^[²^]。DA的缺乏与MDD的快感缺失、积极性减低及相关的认知症状有关^[³^]，是MDD产生情绪障碍的机制；(2)下丘脑-垂体-肾上腺(hypothalamic-pituitary-adrenal，HPA)轴功能亢进。体内激素如糖皮质激素水平升高损伤海马的神经发生，引起海马和前额叶皮层萎缩，导致HPA轴负反馈减弱^[⁴^]，糖皮质激素水平进一步升高，加剧HPA轴的功能障碍，导致MDD发生；(3)神经营养因子表达降低。脑源性神经营养因子(brain-derived neurotrophic factor，BDNF)由大脑广泛区域的神经细胞、小胶质细胞和星形胶质细胞分泌，在神经细胞的存活、维持、分化和突触可塑性中发挥重要作用。BDNF等神经营养因子水平减低会导致神经发生受损，边缘系统功能减退及体积萎缩，从而引起MDD^[⁵^]；(4)炎症反应。MDD患者体内炎症因子水平明显升高，炎症因子可以明显增强5-HT和DA神经元的活性，使单胺类神经递质的再摄取作用增强，神经递质浓度减低，并可能导致神经退行性变、海马体积减小和BDNF减少，引起情绪低落、快感缺失、认知功能障碍、神经可塑性异常及神经发生受损^[⁶^]。目前抗抑郁药物是治疗MDD的主要方法，三环和四环类抗抑郁药、单胺氧化酶抑制剂、选择性5-HT再摄取抑制剂、5-HT与NE再摄取抑制剂等药物可通过提高神经递质及神经营养因子含量，达到缓解症状的效用。

MDD的发病机制涉及化学神经递质、神经激素失调、神经可塑性、免疫炎症反应及心理社会因素等多种因素，其机制的复杂性导致MDD的异质性，通过MRI对其机制的探索，为进一步解释脑功能及结构的改变提供了帮助。

2 MDD患者脑功能及结构的MRI研究方法

MDD的脑功能MRI (functional MRI，fMRI)研究方法包括静息态功能磁共振成像(resting-state functional MRI，rs-fMRI)、任务态功能磁共振成像(task functional MRI，task-fMRI)。rs-fMRI采用非任务设计驱动的数据处理方法获得多种参数图像，研究静息状态下脑活动机制。其分析方法主要包括两种：(1)局部脑活动分析，包括局部一致性(regional homogeneity，ReHo)、低频振幅(amplitude of low frequency fluctuations，ALFF)和低频振幅分数(fractional amplitude of low frequency fluctuations，fALFF)等；(2)脑功能整合，包括脑功能连接(functional connectivity，FC)、独立成分分析(independent component analysis，ICA)等。task-fMRI研究采用任务实验设计，分析受试者不同任务之间或不同受试者相同任务之间的血氧水平依赖(blood oxygen level dependent，BOLD)信号差异。

脑结构MRI研究方法包括基于体素的形态学测量方法(voxel-based morphometry，VBM)、基于表面的形态学测量方法(surface-based morphometry，SBM)、用于评估区域灰质体积的常规结构MRI以及反映白质微结构变化的弥散张量成像(diffusion tensor imaging，DTI)等，上述方法可直观反映大脑结构变化及脑组织成分差异。

3 fMRI在MDD治疗前后的研究进展

3.1 MDD的fMRI表现

rs-fMRI研究显示MDD患者治疗前右侧额上回、右侧楔前叶、双侧扣带回的ReHo值降低^[⁷^,⁸^]，左侧背内侧前额叶ReHo值增高(P＜0.05)^[⁷^]。近期研究发现青年MDD患者右侧额下回三角部及左侧中央后回的ReHo值较老年患者显著增加(P＜0.05)^[⁹^]。MDD患者背外侧前额叶、背内侧前额叶及楔前叶的fALFF值减小，楔前叶、扣带回ALFF值减小(P＜0.05)^[¹⁰^,¹¹^]。Lan等^[¹²^]的研究显示伴有自杀意念的MDD患者较无自杀意念患者右侧海马、双侧丘脑及尾状核ALFF值升高(P＜0.05)。相关研究还发现有躯体化症状的MDD患者双侧中央前回、双侧中央后回和左侧中央旁回的ReHo、ALFF值显著降低(P＜0.01)^[¹³^]。MDD患者治疗前默认模式网络(default mode network，DMN)、中央执行网络(central executive network，CEN)及显著性网络(salience network，SN)内FC增加(P＜0.05)^[¹⁴^,¹⁵^]。基于情绪冲突任务的task-fMRI显示MDD患者右侧颞下回、外侧枕叶激活减低(P＜0.05)^[¹⁶^]，负面情绪词汇任务中患者中脑、背外侧前额叶、扣带回、丘脑和尾状核激活减低(P＜0.05)^[¹⁷^]。

因此，fMRI的多种分析方法可以发现MDD多个脑区及脑网络异常，还可以对MDD的多种亚型进行有效评估，有利于进一步实现个体化的精准治疗。

3.2 MDD治疗后的fMRI改变

抗抑郁治疗后rs-fMRI研究显示，MDD患者右侧额上回及扣带回ReHo值升高，左侧背内侧前额叶ReHo值降低(P＜0.05)^[⁷^,¹⁸^]，右侧楔前叶ReHo值仍低于正常对照组(P＜0.01)^[¹⁹^]。背外侧前额叶、背内侧前额叶及扣带回fALFF值增加(P＜0.05)^[¹⁰^,²⁰^]，楔前叶ALFF值低于正常对照组^[¹¹^]。基于ICA的rs-fMRI研究显示治疗后MDD患者DMN网络内FC减低^[²¹^]，小脑和SN之间的FC减低(P＜0.05)^[²²^]。大尺度脑网络rs-fMRI研究显示DMN网络内FC减低，DMN与视交叉上核(suprachiasmatic nucleus，SCN)网络间FC减低(P＜0.05)^[²³^]。但Chin Fatt等^[²⁴^]的研究发现了不一致的结果，治疗后患者DMN、CEN及SN网络内FC增加，且DMN网络内FC、DMN与CEN网络间FC越高治疗效果越好(P＜0.05)。一项关于难治性MDD的研究表明，患者治疗后参与DMN认知过程的左背外侧前额叶和右腹外侧前额叶以及与CEN情感过程相关的周围前扣带回皮层和眶额皮层之间的FC增加(P＜0.05)^[²⁵^]。另一项老年MDD研究发现治疗后患者CEN内右侧中央前回的连接增加，DMN内右侧额下回和缘上回的连接减少(P＜0.05)^[²⁶^]。相关研究结果不一致的原因除MDD的异质性外，还有可能是各功能网络之间相互作用及不同的抗抑郁药物诱导的不同神经活动所导致。

一项关于面部表情识别任务的task-fMRI研究显示治疗1周后MDD患者在左顶叶、中央前回和双侧岛叶的激活增加^[²⁷^]。治疗4周后患者在面部表情识别任务中前扣带回、背内侧前额叶、背外侧前额叶和基底神经节的激活增加(P＜0.05)^[²⁸^]。但Reed等^[²⁹^]的研究则显示，治疗后MDD患者双侧额叶、颞叶、楔前叶和后扣带回激活降低(P＜0.001)。不同研究间存在差异的原因可能是刺激任务不同、患者异质性及患者对刺激的敏感性存在差异。

以上相关研究结果表明，fMRI作为非侵入性检查方法对于患者的治疗反应的评估有重要价值，但不同研究间仍存在差异，日后需在扩大样本量的基础上加强研究，为患者的诊疗提供更多的有价值的信息。

3.3 治疗后fMRI改变可能的机制

右侧额上回和执行功能有关，负责控制内在矛盾的冲动反应^[³⁰^]，背外侧前额叶是调节注意力、认知控制、动机和情绪的关键区域^[³¹^]，右额下回三角部是背外侧前额叶的重要组成部分。背内侧前额叶与情绪和认知调节有关，其功能异常会引起负面情绪并降低认知能力^[³²^]。扣带回与情绪、自我控制有关^[³³^]，楔前叶参与自我意识及记忆的调节，与患者的自尊过低及记忆力减退有关^[³⁴^]，海马与记忆功能、调节情绪反应、执行功能、感觉运动整合和目标导向活动有关，丘脑参与情绪痛苦的处理，其功能改变可能导致患者产生自杀意念^[¹²^,³⁵^]。中央后回是大脑接收和整合外界刺激的躯体感觉信息中枢，中央前回和中央旁回与躯体运动功能有关^[⁹^,¹³^]，其功能异常是导致MDD躯体化症状的病理机制。上述脑区ReHo、ALFF值及DMN、CEN、SN功能的改变可能导致认知、情绪处理脑区自发活动及连接功能的异常，这与MDD患者认知障碍、情绪低落等临床症状相吻合。抗抑郁药通过改变相关兴奋性突触功能或增加突触间隙中如5-HT、NE等神经递质的浓度^[³^]，抑制多巴胺神经元的兴奋^[³⁶^]，调节神经元连接功能，并促进神经可塑性和抗炎作用^[⁶^,³⁷^]，改善相关脑区功能活动，恢复情绪处理的调控作用，使DMN、CEN及SN的静息态脑功能连接恢复正常，改善相关功能连接异常导致的负性自我关注增强、自我反刍、认知、情绪控制异常等症状。但抗抑郁治疗后仍存在楔前叶的ReHo值及ALFF值减低，其原因可能是抗抑郁药的疗效需要8～12周才能出现，需要后续长期治疗以进一步研究楔前叶异常活动的改变。值得注意的是，如顶叶及岛叶等脑区的激活在治疗早期发生了与任务相关的变化，表明药物治疗后改变了相关脑网络及脑区激活状态，通过任务态fMRI可以了解药物治疗早期的神经变化。

这些结果表明，MDD涉及多个与情绪、认知密切相关的脑区及脑网络的异常，但部分研究仍局限于数据分析方法单一，需进一步利用多模态fMRI进行纵向研究明确其发病及治疗机制。此外，研究不同症状的MDD差异脑区有利于深入了解MDD不同病程及亚型潜在的神经病理机制，并为疾病早期诊断、分型提供影像学依据。

4 脑结构MRI在MDD治疗前后的研究进展

4.1 MDD的脑结构MRI表现

VBM及SBM研究发现，MDD患者腹内侧前额叶、扣带回、岛叶、眶额叶、颞叶、顶叶及海马灰质体积减小^[³⁸^,³⁹^]。一项与MDD临床表型相关的结构MRI研究显示，MDD患者的焦虑痛苦症状与边缘系统和额叶的灰质厚度及灰质下体积呈负相关，身体、情感创伤史及性虐待史与内嗅灰质厚度及海马体积呈负相关(P＜0.05)^[⁴⁰^]。DTI研究显示MDD患者放射冠、胼胝体、上纵束、钩状束、内囊、扣带回、杏仁核和眶额叶的FA值减低^[⁴¹^,⁴²^]，进一步研究显示左侧内囊FA值越低，抑郁严重程度越高(P＜0.05)^[⁴³^]。一项7.0 T MRI的脑白质结构网络研究显示MDD患者海马的连通性较正常对照组降低(P＜0.01)^[⁴⁴^]。

结构MRI能够识别MDD患者大脑灰、白质的异常，可作为对fMRI的补充，未来可通过与其他分析方法联合使用，从宏观和微观的角度对MDD的结构改变进行全面的评估。

4.2 MDD治疗后的脑结构MRI改变

抗抑郁治疗后，MDD患者的左侧额叶、楔前叶、缘上回灰质及海马体积增大^[⁴⁵^,⁴⁶^]，一项7.0 T的结构MRI研究也有相似的发现(P＜0.05)^[⁴⁷^]。然而，Voineskos等^[⁴⁸^]的研究显示治疗后患者左侧大脑半球灰质厚度显著减少，以额叶和颞叶为著。不同研究的差异可能与样本量过小、抗抑郁治疗药物差异及疾病的异质性有关。DTI研究显示治疗后MDD患者的左侧上纵束、下纵束、扣带回、双侧钩状束的FA值显著增加(P＜0.05)^[⁴⁹^,⁵⁰^]，且治疗前FA值与抗抑郁药的疗效呈正相关^[⁴⁸^]。

治疗后患者的认知和情感症状改善表明相应脑区灰、白质的结构改变可能是MDD的神经病理机制，未来采用高场MRI并结合如扩散峰度成像、扩散频谱成像等成像方式在MDD诊断及疗效评估方面具有广阔的研究前景。

4.3 治疗后脑结构改变可能的机制

灰质厚度及体积反映了神经元的密度、大小和排列^[⁵¹^]，MDD患者灰质变薄可能是由神经胶质细胞密度和神经元体积减小所致。脑白质的FA值与轴突密度和髓鞘形成有关，FA值减小则表明轴突损伤及白质微结构的破坏^[⁵²^]。研究中发生异常改变的区域为调节情感和认知的关键脑区及神经回路。抗抑郁药物通过调节神经递质含量及相关受体的表达，增强局部突触的连通性^[³⁷^]，发挥抗炎作用逆转炎症变化，并增加如BDNF等神经营养因子，促进神经可塑性的激活^[⁵^]，改变大脑的微观结构，使灰质体积及白质微结构正常化，从而减轻情绪障碍。

因此上述研究表明药物治疗后MDD患者脑灰、白质的病理改变是可逆的，通过脑结构MRI可增加对抗抑郁药改善情绪神经机制的理解。未来的研究需要将功能及结构相结合深入探究两者之间的关系，为诊断与个体评估疗效提供新思路。

5 小结

MDD患者治疗前后脑功能及结构的MRI具有多种改变，这些改变可作为诊断及评估疗效的影像学标志物。然而，在目前的研究中，多数研究观察了抗抑郁治疗前及急性期治疗后的静息态脑功能变化，对抗抑郁药物长期治疗的影响尚不明确；MDD患者的疾病异质性、抗抑郁药物的种类、剂量的不同可能会影响研究的准确度及可重复性。后续研究中建议利用纵向研究完善有关缓解阶段和复发状态的详细信息，探索功能及结构的关系，综合运用多模态成像研究方法，为研究抗抑郁药物治疗的作用机制和疗效评价提供一种新的研究视角。

参考文献

[1]

Lim SS, Vos T, Flaxman AD, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010[J]. Lancet, 2012, 380(9859): 2224-2260. DOI: 10.1016/S0140-6736(12)61766-8.

[2]

Spellman T, Liston C. Toward circuit mechanisms of pathophysiology in depression[J]. Am J Psychiatry, 2020, 177(5): 381-390. DOI: 10.1176/appi.ajp.2020.20030280.

[3]

Shao XJ, Zhu G. Associations among monoamine neurotransmitter pathways, personality traits, and major depressive disorder[J]. Front Psychiatry, 2020, 11: 381. DOI: 10.3389/fpsyt.2020.00381.

[4]

Dwyer JB, Aftab A, Radhakrishnan R, et al. Hormonal treatments for major depressive disorder: state of the art[J]. Am J Psychiatry, 2020, 177(8): 686-705. DOI: 10.1176/appi.ajp.2020.19080848.

[5]

Suda K, Matsuda K. How microbes affect depression: underlying mechanisms via the gut-brain axis and the modulating role of probiotics[J]. Int J Mol Sci, 2022, 23(3): 1172. DOI: 10.3390/ijms23031172.

[6]

Wiebenga JXM, Heering HD, Eikelenboom M, et al. Associations of three major physiological stress systems with suicidal ideation and suicide attempts in patients with a depressive and/or anxiety disorder[J]. Brain Behav Immun, 2022, 102: 195-205. DOI: 10.1016/j.bbi.2022.02.021.

[7]

Wang L, Li K, Zhang Q, et al. Short-term effects of escitalopram on regional brain function in first-episode drug-naive patients with major depressive disorder assessed by resting-state functional magnetic resonance imaging[J]. Psychol Med, 2014, 44(7): 1417-1426. DOI: 10.1017/S0033291713002031.

[8]

Jiang XW, Fu SN, Yin ZY, et al. Common and distinct neural activities in frontoparietal network in first-episode bipolar disorder and major depressive disorder: preliminary findings from a follow-up resting state fMRI study[J]. J Affect Disord, 2020, 260: 653-659. DOI: 10.1016/j.jad.2019.09.063.

[9]

Zhang ZJ, Chen YY, Wei W, et al. Changes in regional homogeneity of medication-free major depressive disorder patients with different onset ages[J]. Front Psychiatry, 2021, 12: 713614. DOI: 10.3389/fpsyt.2021.713614.

[10]

Cheng Y, Xu J, Arnone D, et al. Resting-state brain alteration after a single dose of SSRI administration predicts 8-week remission of patients with major depressive disorder[J]. Psychol Med, 2017, 47(3): 438-450. DOI: 10.1017/S0033291716002440.

[11]

Wang M, Ju YM, Lu XW, et al. Longitudinal changes of amplitude of low-frequency fluctuations in MDD patients: a 6-month follow-up resting-state functional magnetic resonance imaging study[J]. J Affect Disord, 2020, 276: 411-417. DOI: 10.1016/j.jad.2020.07.067.

[12]

Lan MJ, Rizk MM, Pantazatos SP, et al. Resting-state amplitude of low-frequency fluctuation is associated with suicidal ideation[J]. Depress Anxiety, 2019, 36(5): 433-441. DOI: 10.1002/da.22888.

[13]

Liu PH, Tu HW, Zhang AX, et al. Brain functional alterations in MDD patients with somatic symptoms: a resting-state fMRI study[J]. J Affect Disord, 2021, 295: 788-796. DOI: 10.1016/j.jad.2021.08.143.

[14]

Scalabrini A, Vai B, Poletti S, et al. All roads lead to the default-mode network-global source of DMN abnormalities in major depressive disorder[J]. Neuropsychopharmacology, 2020, 45(12): 2058-2069. DOI: 10.1038/s41386-020-0785-x.

[15]

Li YL, Dai X, Wu HW, et al. Establishment of effective biomarkers for depression diagnosis with fusion of multiple resting-state connectivity measures[J]. Front Neurosci, 2021, 15: 729958. DOI: 10.3389/fnins.2021.729958.

[16]

Alders GL, Davis AD, MacQueen G, et al. Reduced accuracy accompanied by reduced neural activity during the performance of an emotional conflict task by unmedicated patients with major depression: a CAN-BIND fMRI study[J]. J Affect Disord, 2019, 257: 765-773. DOI: 10.1016/j.jad.2019.07.037.

[17]

Miller JM, Schneck N, Siegle GJ, et al. fMRI response to negative words and SSRI treatment outcome in major depressive disorder: a preliminary study[J]. Psychiatry Res Neuroimaging, 2013, 214(3): 296-305. DOI: 10.1016/j.pscychresns.2013.08.001.

[18]

Lai CH, Wu YT. Frontal regional homogeneity increased and temporal regional homogeneity decreased after remission of first-episode drug-naïve major depressive disorder with panic disorder patients under duloxetine therapy for 6 weeks[J]. J Affect Disord, 2012, 136(3): 453-458. DOI: 10.1016/j.jad.2011.11.004.

[19]

Yang CX, Zhang AX, Jia AX, et al. Identify abnormalities in resting-state brain function between first-episode, drug-naive major depressive disorder and remitted individuals: a 3-year retrospective study[J]. Neuroreport, 2018, 29(11): 907-916. DOI: 10.1097/WNR.0000000000001054.

[20]

Zhou M, Hu XY, Lu L, et al. Intrinsic cerebral activity at resting state in adults with major depressive disorder: a meta-analysis[J]. Prog Neuro Psychopharmacol Biol Psychiatry, 2017, 75: 157-164. DOI: 10.1016/j.pnpbp.2017.02.001.

[21]

Li BJ, Liu L, Friston KJ, et al. A treatment-resistant default mode subnetwork in major depression[J]. Biol Psychiatry, 2013, 74(1): 48-54. DOI: 10.1016/j.biopsych.2012.11.007.

[22]

Sahib AK, Loureiro JR, Vasavada M, et al. Modulation of the functional connectome in major depressive disorder by ketamine therapy[J]. Psychol Med, 2020: 1-10. DOI: 10.1017/s0033291720004560.

[23]

Li L, Su YN, Wu YK, et al. Eight-week antidepressant treatment reduces functional connectivity in first-episode drug-naïve patients with major depressive disorder[J]. Hum Brain Mapp, 2021, 42(8): 2593-2605. DOI: 10.1002/hbm.25391.

[24]

Chin Fatt CR, Jha MK, Cooper CM, et al. Effect of intrinsic patterns of functional brain connectivity in moderating antidepressant treatment response in major depression[J]. Am J Psychiatry, 2020, 177(2): 143-154. DOI: 10.1176/appi.ajp.2019.18070870.

[25]

Mkrtchian A, Evans JW, Kraus C, et al. Ketamine modulates fronto-striatal circuitry in depressed and healthy individuals[J]. Mol Psychiatry, 2021, 26(7): 3292-3301. DOI: 10.1038/s41380-020-00878-1.

[26]

Karim HT, Andreescu C, Tudorascu D, et al. Intrinsic functional connectivity in late-life depression: trajectories over the course of pharmacotherapy in remitters and non-remitters[J]. Mol Psychiatry, 2017, 22(3): 450-457. DOI: 10.1038/mp.2016.55.

[27]

Williams RJ, Brown EC, Clark DL, et al. Early post-treatment blood oxygenation level-dependent responses to emotion processing associated with clinical response to pharmacological treatment in major depressive disorder[J]. Brain Behav, 2021, 11(8): e2287. DOI: 10.1002/brb3.2287.

[28]

Frodl T, Scheuerecker J, Schoepf V, et al. Different effects of mirtazapine and venlafaxine on brain activation[J]. J Clin Psychiatry, 2011, 72(4): 448-457. DOI: 10.4088/jcp.09m05393blu.

[29]

Reed JL, Nugent AC, Furey ML, et al. Effects of ketamine on brain activity during emotional processing: differential findings in depressed versus healthy control participants[J]. Biol Psychiatry Cogn Neurosci Neuroimaging, 2019, 4(7): 610-618. DOI: 10.1016/j.bpsc.2019.01.005.

[30]

Seminowicz DA, Mayberg HS, McIntosh AR, et al. Limbic-frontal circuitry in major depression: a path modeling metanalysis[J]. NeuroImage, 2004, 22(1): 409-418. DOI: 10.1016/j.neuroimage.2004.01.015.

[31]

Zhou HX, Chen X, Shen YQ, et al. Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression[J]. NeuroImage, 2020, 206: 116287. DOI: 10.1016/j.neuroimage.2019.116287.

[32]

Yin JB, Liang SH, Li F, et al. dmPFC-vlPAG projection neurons contribute to pain threshold maintenance and antianxiety behaviors[J]. J Clin Invest, 2020, 130(12): 6555-6570. DOI: 10.1172/JCI127607.

[33]

邱晶, 王碧馨, 王蕾, 等. 首发抑郁症患者静息态脑功能局部一致性研究[J]. 磁共振成像, 2020, 11(9): 721-725. DOI: 10.12015/issn.1674-8034.2020.09.001.

Qiu J, Wang BX, Wang L, et al. Research on regional homogeneity of resting state functional magnetic resonance imaging in first-episode depressive disorder patients[J]. Chin J Magn Reson Imaging, 2020, 11(9): 721-725. DOI: 10.12015/issn.1674-8034.2020.09.001.

[34]

Köhler CA, Carvalho AF, Alves GS, et al. Autobiographical memory disturbances in depression: a novel therapeutic target?[J]. Neural Plast, 2015, 2015: 759139. DOI: 10.1155/2015/759139.

[35]

Zhang Q, Hong S, Cao J, et al. Hippocampal subfield volumes in major depressive disorder adolescents with a history of suicide attempt[J]. Biomed Res Int, 2021, 2021: 5524846. DOI: 10.1155/2021/5524846.

[36]

Blier P, Mansari ME. Serotonin and beyond: therapeutics for major depression[J]. Philos Trans R Soc Lond B Biol Sci, 2013, 368(1615): 20120536. DOI: 10.1098/rstb.2012.0536.

[37]

Duman RS, Aghajanian GK, Sanacora G, et al. Synaptic plasticity and depression: new insights from stress and rapid-acting antidepressants[J]. Nat Med, 2016, 22(3): 238-249. DOI: 10.1038/nm.4050.

[38]

Marques Périco C, Dickstein DP, Farrow TFD, et al. Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis. Mol Psychiatry, 2017, 22(10):1455-1463. DOI: 10.1038/mp.2016.72.

[39]

Li Q, Zhao Y, Chen Z, et al. Meta-analysis of cortical thickness abnormalities in medication-free patients with major depressive disorder. Neuropsychopharmacology, 2020, 45(4):703-712. DOI: 10.1038/s41386-019-0563-9.

[40]

Yu MC, Cullen N, Linn KA, et al. Structural brain measures linked to clinical phenotypes in major depression replicate across clinical centres[J]. Mol Psychiatry, 2021, 26(7): 2764-2775. DOI: 10.1038/s41380-021-01039-8.

[41]

van Velzen LS, Kelly S, Isaev D, et al. White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group[J]. Mol Psychiatry, 2020, 25(7): 1511-1525. DOI: 10.1038/s41380-019-0477-2.

[42]

Jiang J, Zhao YJ, Hu XY, et al. Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging[J]. J Psychiatry Neurosci, 2017, 42(3): 150-163. DOI: 10.1503/jpn.150341.

[43]

Wang Y, Zhao T, Xie J, et al. The study of white matter micro-structures mediating onset age and the severity of depressive disorder based on DTI[J]. Chin J Magn Reson Imaging, 2021, 12(6): 1-4, 15. DOI: 10.12015/issn.1674-8034.2021.06.001.

[44]

Rutland JW, Brown S, Verma G, et al. Hippocampal subfield-specific connectivity findings in major depressive disorder: a 7 Tesla diffusion MRI study[J]. J Psychiatr Res, 2019, 111: 186-192. DOI: 10.1016/j.jpsychires.2019.02.008.

[45]

Zarate-Garza PP, Ortega-Balderas JA, Ontiveros-Sanchez de la Barquera JA, et al. Hippocampal volume as treatment predictor in antidepressant naïve patients with major depressive disorder[J]. J Psychiatr Res, 2021, 140: 323-328. DOI: 10.1016/j.jpsychires.2021.06.008.

[46]

Bartlett EA, DeLorenzo C, Sharma P, et al. Pretreatment and early-treatment cortical thickness is associated with SSRI treatment response in major depressive disorder[J]. Neuropsychopharmacology, 2018, 43(11): 2221-2230. DOI: 10.1038/s41386-018-0122-9.

[47]

Kraus C, Seiger R, Pfabigan DM, et al. Hippocampal subfields in acute and remitted depression-an ultra-high field magnetic resonance imaging study[J]. Int J Neuropsychopharmacol, 2019, 22(8): 513-522. DOI: 10.1093/ijnp/pyz030.

[48]

Voineskos AN, Mulsant BH, Dickie EW, et al. Effects of antipsychotic medication on brain structure in patients with major depressive disorder and psychotic features: neuroimaging findings in the context of a randomized placebo-controlled clinical trial[J]. JAMA Psychiatry, 2020, 77(7): 674-683. DOI: 10.1001/jamapsychiatry.2020.0036.

[49]

Sydnor VJ, Lyall AE, Cetin-Karayumak S, et al. Studying pre-treatment and ketamine-induced changes in white matter microstructure in the context of ketamine's antidepressant effects[J]. Transl Psychiatry, 2020, 10(1): 432. DOI: 10.1038/s41398-020-01122-8.

[50]

Melloni EMT, Poletti S, Dallaspezia S, et al. Changes of white matter microstructure after successful treatment of bipolar depression[J]. J Affect Disord, 2020, 274(1): 1049-1056. DOI: 10.1016/j.jad.2020.05.146.

[51]

Narr KL, Bilder RM, Toga AW, et al. Mapping cortical thickness and gray matter concentration in first episode schizophrenia[J]. Cereb Cortex, 2005, 15(6): 708-719. DOI: 10.1093/cercor/bhh172.

[52]

Cotter D, MacKay D, Chana G, et al. Reduced neuronal size and glial cell density in area 9 of the dorsolateral prefrontal cortex in subjects with major depressive disorder[J]. Cereb Cortex, 2002, 12(4): 386-394. DOI: 10.1093/cercor/12.4.386.

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