摘要
目的：
伤害避免(harm avoidance, HA)人格主要是指对有害刺激强烈反应的天生倾向。其神经机制仍不清楚。本研究采用多模态磁共振成像(magnetic resonance imaging, MRI)技术,联合运用基于体素的形态学(voxel-based morphometry analysis, VBM)、独立成分分析(independent component analysis, ICA)和感兴趣区静息态功能连接(resting-state functional connectivity, rsFC)方法,研究健康青年脑灰质体积(gray matter volume, GMV)、静息态功能网络(resting-state network, RSN)及rsFC与HA评分的关系。
材料与方法：
选择符合入组标准的健康青年志愿者291例,年龄：18～29岁；男性138例,平均年龄：22.1±2.5岁；女性153例,平均年龄：23.2±2.2岁。每名受试者完成三维人格问卷及Beck抑郁问卷。利用GE3.0T Signa HDX磁共振扫描仪对所有受试者进行静息态及结构像数据的采集。静息态扫描时嘱受试者闭眼、保持身体静止不动,均匀呼吸,精神放松,尽量不思考任何事情。
1.采用基于Matlab平台的SPM8软件及其插件包VBM8对高分辨率结构像进行预处理,预处理过程包括：灰、白质分割、空间标准化及空间平滑。采用基于Matlab平台的REST软件对静息态功能数据进行预处理,预处理过程包括：时间校正、头动校正、空间标准化、重采样到2mm×2mm×2mm的立方体素、带通滤波(带宽：0.01-0.08Hz,以去掉高频噪声和低频漂移)及空间平滑。
2.采用预处理后的结构像数据,利用多重回归的方法,在控制年龄、BDI评分、性别影响后,研究GMV与HA评分的相互关系。
3.采用预处理后的静息态功能数据,利用基于Matlab平台的GIFT软件进行组ICA分析,得到20个独立成分,选择与文献报道相一致的11个独立成分作为感兴趣RSNs,获得11个RSNs群组水平模板。运用多重回归分析,以感兴趣RSNs作为掩模(mask),在控制年龄、BDI评分、性别影响后,探讨网络内功能连接与HA评分的相关性。
4.用最大概率模板提取双侧杏仁核亚区,将其作为感兴趣区并运用REST软件与全脑进行功能连接分析,得到功能连接模式图。运用多重回归分析,以各杏仁核亚区功能连接模式图作为mask,在控制年龄、BDI评分影响后,研究杏仁核亚区功能连接与HA评分的相关性并分析性别差异。
5.统计分析采用AlphaS im多重比较校正方法对结果进行校正,最后将校正后的统计参数映射到MNI标准空间进行显示、观察。描述并记录有统计学意义脑区的团块大小、Brodmann分区、MNI坐标及相关强度。
结果：
1.GMV与HA评分负相关的脑区包括：右侧颞下回、右侧岛叶、双侧楔前叶及右侧顶上小叶。没有正相关的脑区。
2.发现四个RSNs与HA评分存在相关性。背侧注意网络内呈负相关脑区包括右侧缘上回、左侧顶下小叶；没有正相关脑区。腹侧注意网络内呈正相关的脑区是右腹侧额叶皮层；而呈负相关的脑区包括右侧颞上回、双侧缘上回。右侧额顶网络内呈负相关的脑区包括双侧角回、右侧顶下小叶；而呈正相关的脑区是右内侧前额叶。感觉运动网络内呈负的相脑区包括双侧中扣带皮层、右侧辅助运动区、双侧中央后回、左侧中央前回,没有呈正相关的脑区。
3.杏仁核三个亚区为：基底外侧核(laterobasal, LB)、中央内侧核(centromedial, CM)和浅表核(superficial, SF)。每个亚区具有不同的rsFC模式。没有发现LB正rsFC与HA评分相关的脑区。LB负rsFC与HA评分的相关的脑区如下：左侧颞顶交界区(temporoparietal junction, TPJ)和双侧LB间负rsFCs与HA评分呈正相关的脑区；左枕叶和左侧LB间的负rsFC与HA评分呈正相关；双侧颞下回和右侧LB间的负rsFCs与HA评分呈负相关。与CM呈正rsFC的脑区如下：右侧CM和右侧前运动皮层间的正rsFCs与HA评分呈正相关。在与CM呈负rsFC的脑区如下：双侧腹内侧前额叶皮层(ventromedial prefrontal cortex, vmPFC)和左侧CM间的负rsFCs与HA评分呈负相关；右侧额极和右侧CM间的负rsFCs与HA评分呈负相关。在与CM呈负rsFC的脑区中,我们没有发现与HA评分呈正相关的脑区。与SF呈正rsFC的脑区中,右侧腹侧纹状体和右侧SF间的正rsFCs与HA评分呈负相关。在与SF呈负功能连接的脑区如下：双侧vmPFC和左侧SF间的负rsFCs与HA评分呈负相关；左侧颞下回、左侧vmPFC和右侧SF间的负rsFCs与HA评分呈负相关；左侧TPJ和右侧SF间的负rsFCs与HA评分呈正相关。LB rsFC和HA评分的相关性女性受试者较男性强。CMrsFC与HA评分的相关性男性受试者较女性强。SF rsFC与HA评分的相关性没有性别差异。
结论：
1.健康青年局部脑区灰质体积与HA评分呈负相关。
2.健康青年的HA评分与背侧注意网络、腹侧注意网络、右侧额顶网络、感觉运动网络存在相关性。
3.杏仁核亚区的rsFC与HA评分存在相关性,而且这种相关存在性别差异。
Objective:
Harm avoidance (HA) is a personality dimension involving the tendency to respond intensely to signals of aversive stimuli. While its neural substrates remain elusive. We combined voxel-based morphometry (VBM) analysis, independent component analysis (ICA) and resting-state functional connectivity (rsFC) based on ROI analysis of fMRI data to investigate neural correlates of HA scores in a large sample of healthy young adults.
Subjects and Methods:
A total of291right-handed healthy young adults were recruited in this study. After completing the tests of the temperament of the Tridimensional Personality Questionnaire (TPQ) and the Beck Depression Inventory (BDI), the subjects' resting-state fMRI and sagittal structural images were collected using a GE3.0T Signa HDX scanner. During the resting-state scanning, all subjects were explicitly instructed to keep their eyes closed, relax, as motionless as possible and think of nothing.
1. All preprocessing steps were carried out using the statistical parametric mapping (SPM8) based on Matlab.
2. Voxel-based partial correlation analyses were carried out to test correlations between the HA scores and the GMV while controlling age, gender and BDI scores.
3. After ICA by the GIFT software based on Matlab, we chooseed eleven RSNs from the results of ICA. The partial correlation analyses were carried out to test correlations between the HA scores and rsFCs within the eleven RSNs while age, gender and BDI scores were entered as covariates.
4. The amygdala subregions were extracted using the maximum probabilistic map (MPM). The relationships between HA scores and amygdala subregion rsFCs were analyzed using a multiple regression model within the significant mask of each amygdala subregion while controlling for age and BDI scores.
5. The multiple comparisons were statistically corrected by Monte Carlo simulation. Finally the corrected statistical parameter mapping was overlapped onto MNI standard template and the coordinate, size and peak t values of each significant cluster were recorded.
Results:
1. The HA scores were negatively correlated with the GMVs in the right inferior temporal gyrus, right insular cortex, the bilateral precuneus and right superior parietal lobule.
2. The relationships between HA scores and RSNs were found in dorsal attention network, the ventral attention network, the right frontoparietal network, the sensorimotor network.
3. The rsFC patterns of the amygdalar subregions showed different. HA scores were correlated with rsFCs between the LB and temporal and occipital cortices related to emotional information input, between the CM and the frontal cortices associated with emotional output control, and between the SF and the frontal and temporal areas involved in both functions.
Conclusion:
1. HA scores were related to gray matter volumes of several brain areas.
2. HA scores were also related to resting-state functional networks.
3. These findings not only confirmed associations between HA score and the rsFCs of amygdalar subregions, but also found sex differences in these correlations.
引文
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