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题名:
抑郁情绪与学龄儿童脑发育关系研究
作者: 张蕾
学位类别: 博士
答辩日期: 2018-06
授予单位: 中国科学院研究生院
授予地点: 北京
导师: 左西年
关键词: 重性抑郁障碍 ; 抑郁情绪 ; 学龄期儿童 ; 脑发育 ; 潜变量增长模型
其他题名: Studv on the relationship between depression and brain development in school-age children
学位专业: 认知神经科学
中文摘要:

    重性抑郁障碍(Major depression disorder, MDD)发病率高,治疗有效率低,是全球疾病负担的首要原因。调查显示约67%的精神疾病首发年龄在21岁之前,童年期经历抑郁情绪困扰的儿童在未来生活中有更高的功能受损和抑郁发病风险,因此,对相关神经发育特征的表征是至关重要的。描绘抑郁相关脑区在学龄阶段的发育趋势及影响因素,能够帮助我们从发育角度理解抑郁症发病的脑机制,从而及早进行干预。
    本论文包括三个研究:
    研究一为了确定与发育过程相关的青少年抑郁症的脑活动异常模式,对不同年龄群体和不同服药状态的抑郁症静息态功能磁共振研究进行了全面综述,结果发现青少年MDD,成年MDD和老年MDD表现出不同的静息态脑活动异常模式,具体为:青少年MDD主要表现为默认网络的活动异常,很少涉及到控制网络的异常,成年MDD在未服药状态下主要表现为全脑大范围的功能连接下降,经过抗抑郁药物的治疗,控制网络与默认网络的功能连接上升,但感觉网络功能连接下降。基于低频振幅,局部一致性和种子点功能连接三种不同研究方法的结
果基本一致。
    研究二根据研究一的结论,选择默认网络核心区域一后部扣带(posterior cingulate cortex, PCC)和内侧前额叶(medial prefrontal cortex, MPFC)为感兴趣区,采用潜变量增长模型,探讨了学龄儿童PCC和MPFC在五年三次追踪中结构指标(皮层表面积、厚度和体积)的发育趋势及抑郁的预测作用。被试来源于“中国彩巢计划”项目,一共81人,结果发现在表面积指标上,PCC发育呈线性下降趋势,而MPFC没有呈现出线性上升或下降趋势;在皮层厚度指标上,MPFC发育呈线性下降的趋势,而PCC没有表现出这种趋势;在体积指标上,PCC和MPFC发育都呈现线性下降的趋势。本研究还发现PCC区域的一个子区域一右侧PCV在起始体积上存在显著的个体差异,儿童第一次测试时的抑郁分数对该脑区的起始体积有正向预测作用,抑郁情绪得分高的儿童,起始体积更大。
    研究三首先使用ALFF和ReHo指标探讨学龄儿童大脑局部功能的发育趋势及抑郁的预测作用,潜变量增长模型分析表明:PCC和MPFC在不同指标上发育趋势是不同的,在ALFF指标上,MPFC的发育呈线性下降的趋势,而PCC没有表现出这种趋势;在ReHo指标上,PCC的发育呈线性下降趋势,而MPFC没有表现出这种趋势。研究还发现了性别、抑郁分数及其交互作用对局部脑功能指标发育速度的预测作用:在PCC的子区域31pd区上,女生ALFF和ReH。的起始水平都高于男生,抑郁分数高的女生该脑区ALFF增长的快,同时,抑郁分
数高的女生该脑区ReHo值下降的慢。
    研究三接着以局部功能指标中发现的与抑郁关系最密切的31pd区为种子点,计算该区域与全脑的时间序列相关,对三次测量的功能连接进行潜变量增长模型估计,结果发现,31pd区与多个区域功能连接表现出逐年下降趋势,主要包括听觉皮层,视觉皮层,感觉运动皮层,颗顶联合皮层,顶下皮层和外侧颗叶皮层等,而与内侧前额叶皮层,后部扣带皮层和背外侧前额叶皮层没有表现出下降趋
势。进一步分析发现性别与抑郁的交互作用可以预测右侧31pd区与左侧PGi区的功能连接水平,抑郁分数高的女生连接水平高于抑郁分数低的女生,男生没有表现出显著差异。PGi区也属于默认网络的一部分,该结果表明了性别与抑郁分数对默认网络长距离功能连接的预测作用。
    本研究在综述了不同年龄段不同服药情况抑郁症脑活动异常模式的基础上,发现了青少年抑郁症的核心异常区域一一默认网络,以此为感兴趣区,考察了正常学龄儿童默认网络的结构与功能发育趋势及抑郁的影响作用,结果发现PCC和MPFC在结构和功能上都表现出不同的发育趋势,而且儿童的抑郁得分对默认网络结构和功能的起始水平和发育速度都有预测作用,暗示了抑郁症的发病可能是一个持续的由量变到质变的过程,提示对抑郁症早期脑影像指标进行探测的重要性。

英文摘要:

   Major depression disorder (MDD) has a high incidence and low treatment efficiency, which is the leading cause of global disease burden. The survey showed that about 67 percent of mental illness starts before the age of 21,Children experience depression might have a higher risk of impaired function and depression onset in the future life. Therefore, the related characteristics of neural development is crucial. To describe the developmental trend and influencing factors in the school-age stage can help us understand the brain mechanism of depression from the perspective of development and intervene early.
This paper includes three studies:
    Study one reviewed the resting state functional magnetic resonance imaging researches of MDD according to different age groups and different medicine status, in order to determine the abnormal patterns of brain activity associated with adolescent depression. The results found that adolescent, adult and the eldely MDD patients showed different resting state brain activity characteristics: adolescents MDD mainly shows abnormal connectivity in the default network, rarely involves the control network. Adult MDD showed a decease of function connectivity in the whole brain on the condition of unmedicated, after antidepressant treatment, the control network and the emotion network showed a recovery of function connectivity, but the sensorimotor network still decline. Different analysis methods such as seed-bassed function connection analysis (SCA), regional homogeneity (ReHo) and low frequency amplitude (ALFF) showed consistent results.
    According to the results of study one, study two choose the core regions of default network一posterior cingulate cortex(PCC) and medial prefrontal cortex (MPFC) as regions of interest and investigated their structure development among three measurements in five years.We are also interested in the influence of depression on the development of brain structure. Subjects were from "China color nest project (CCNP)", 81 children were included. Latent variable grow curve model (LGCM) were used to model the three times of brain structure index, which include surface area,cortical thickness, and volume. The results found that in the index of surface area,PCC showed a linearly decline trend, while MPFC did not present a linearly increase or decrease trend. In the cortical thickness index, the MPFC regions showed a trend of linear decline, while the PCC did not show any trend. In the cortical volume index, both PCC and MPFC regions showed a trend of linear decline. This study also found the subregion of PCC一right PCV had significant individual differences at the initial level. Latent variable growth model analysis shows that children's first depression scores has positive prediction effect on the initial volume of PCV, children with high depression scores has larger initial volume.
    Study three firstly used ALFF and ReHo to explore the developmental tendency and predictive effects of local function of brain in school-age children. The results showed that the development trend of PCC and MPFC on different indexes is different. In ALFF index, the development of MPFC is linearly decline, while PCC does not show this trend. On the ReHo index, the PCC showed a linearly decline trend, and the MPFC did not show this trend. The study also found a prediction of gender,depression scores and their interactions on the initial level and development speed. In the subregion of PCC一31 pd, the initial values of ALFF and ReHo are higher in girls than in boys, girls with high depression scores growing fast on ALFF value, at the same time, girls with high depression scores decrease slowly on ReHo value.
    Study three then take the PCC_ 31pd as the seed region to calculate the correlation of the region with the other region of the whole brain. Each individual has three times correlation values. LGCV analysis showed that the PCC showed a downward connectivity trend with multiple regions, including auditory cortex, the visual cortex, sensorimotor cortex, temporal association cortices. While the connectivity between 31pd and other regions did not show significant decline,including lateral temporal lobe cortex, the medial prefrontal cortex, posterior cingulate cortex and dorsolateral prefrontal cortex. Further, we found the interaction of gender and depression could predict the connectivity between right 31pd and left PGi area. Girls with high depression scores had higher connectivity between the right side of 31pd and the left PGi, while boys did not show significant differnece. PGi also belongs to the default network, which showed that gender and depression scores can prediction the default network long-distance connection.
    Based on the review of abnormal patterns of depression brain activity according to different age and medication status, we choose the core regions of default mode network一PCC and MPFC as regions of interest to investigate the development of brain structure and function in school一age children and the effect of depression on brain development. The results showed that depression had a prediction on both the initial level and rate of development, which suggest that the onset of depression may be a continuous process from quantitative change to qualitative change and it is important to detect early brain imaging indicators of depression.

语种: 中文
内容类型: 学位论文
URI标识: http://ir.psych.ac.cn/handle/311026/26139
Appears in Collections:健康与遗传心理学研究室_学位论文

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作者单位: 中国科学院心理研究所

Recommended Citation:
张蕾. 抑郁情绪与学龄儿童脑发育关系研究[D]. 北京. 中国科学院研究生院. 2018.
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