Social, Cognitive and Affective Neuroscience Laboratory (SCAN Lab), Department of Psychiatry, College of Medicine, University of Arizona, Tucson, AZ, USA; Multimodal Clinical Neuroimaging Laboratory (MCNL), Center for Neurobehavioral Research, Boys Town National Research Hospital, 14015 Flanagan Blvd. Suite #102, Boys Town, NE 68010, USA.
Social, Cognitive and Affective Neuroscience Laboratory (SCAN Lab), Department of Psychiatry, College of Medicine, University of Arizona, Tucson, AZ, USA.
Neuroimage. 2021 Apr 1;229:117750. doi: 10.1016/j.neuroimage.2021.117750. Epub 2021 Jan 14.
Emotional Intelligence (EI) is a well-documented aspect of social and interpersonal functioning, but the underlying neural mechanisms for this capacity remain poorly understood. Here we used advanced brain connectivity techniques to explore the associations between EI and effective connectivity (EC) within four functional brain networks.
The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) was used to collect EI data from 55 healthy individuals (mean age = 30.56±8.3 years, 26 males). The MSCEIT comprises two area cores - experiential EI (T1) and strategic EI (T2). The T1 core included two sub-scales - perception of emotions (S1) and using emotions to facilitate thinking (S2), and the T2 core included two sub-scales - understanding of emotions (S3) and management of emotions (S4). All participants underwent structural and resting-state functional magnetic resonance imaging (rsfMRI) scans. The spectral dynamic causal modeling approach was implemented to estimate EC within four networks of interest - the default-mode network (DMN), dorsal attention network (DAN), control-execution network (CEN) and salience network (SN). The strength of EC within each network was correlated with the measures of EI, with correlations at p < 0.05 considered as significant.
There was no significant association between any of the measures of EI and EC strength within the DMN and DAN. For CEN, however, we found that there were significant negative associations between EC strength from the right anterior prefrontal cortex (RAPFC) to the left anterior prefrontal cortex (LAPFC) and both S2 and T1, and significant positive associations between EC strength from LAPFC to RAPFC and S2. EC strength from the right superior parietal cortex (SPC) to RAPFC also showed significant negative association with S4 and T2. For the SN, S3 showed significant negative association with EC strength from the right insula to RAPFC and significant positive association with EC strength from the left insula to dorsal anterior cingulate cortex (DACC).
We provide evidence that the negative ECs within the right hemisphere, and from the right to left hemisphere, and positive ECs within the left hemisphere and from the left to right hemisphere of CEN (involving bilateral frontal and right parietal region) and SN (involving right frontal, anterior cingulate and bilateral insula) play a significant role in regulating and processing emotions. These findings also suggest that measures of EC can be utilized as important biomarkers to better understand the underlying neural mechanisms of EI.
情商（EI）是社交和人际功能的一个有据可查的方面，但这种能力的潜在神经机制仍知之甚少。在这里，我们使用先进的大脑连接技术来探索 EI 与四个功能大脑网络内的有效连接（EC）之间的关联。
采用迈耶-萨洛维-卡鲁索情绪智力测验（MSCEIT）从 55 名健康个体（平均年龄 30.56±8.3 岁，26 名男性）中收集 EI 数据。MSCEIT 包括两个区域核心 - 体验式 EI（T1）和策略式 EI（T2）。T1 核心包括两个子量表 - 情绪感知（S1）和利用情绪促进思维（S2），T2 核心包括两个子量表 - 理解情绪（S3）和管理情绪（S4）。所有参与者均接受结构和静息态功能磁共振成像（rsfMRI）扫描。实施频谱动态因果建模方法来估计四个感兴趣网络内的 EC - 默认模式网络（DMN）、背侧注意网络（DAN）、控制执行网络（CEN）和突显网络（SN）。每个网络内 EC 的强度与 EI 测量值相关，p<0.05 的相关性被认为具有统计学意义。
在 DMN 和 DAN 内，没有任何 EI 测量值与 EC 强度之间存在显著关联。然而，对于 CEN，我们发现右额前皮质（RAPFC）到左额前皮质（LAPFC）的 EC 强度与 S2 和 T1 之间存在显著负相关，LAPFC 到 RAPFC 的 EC 强度与 S2 之间存在显著正相关。右侧顶叶皮层（SPC）到 RAPFC 的 EC 强度也与 S4 和 T2 呈显著负相关。对于 SN，S3 与右侧岛叶到 RAPFC 的 EC 强度呈显著负相关，与左侧岛叶到背侧前扣带皮层（DACC）的 EC 强度呈显著正相关。
我们提供的证据表明，CEN（涉及双侧额叶和右顶叶）和 SN（涉及右额、前扣带和双侧岛叶）右侧半球内以及从右侧到左侧半球的负 EC，以及左侧半球内以及从左侧到右侧半球的正 EC，在调节和处理情绪方面发挥着重要作用。这些发现还表明，EC 的测量值可用作重要的生物标志物，以更好地理解 EI 的潜在神经机制。
