Barbey Aron K, Colom Roberto, Paul Erick J, Chau Aileen, Solomon Jeffrey, Grafman Jordan H
1 Decision Neuroscience Laboratory, University of Illinois, Urbana, IL, USA 2 Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana, IL, USA 3 Department of Internal Medicine, University of Illinois, Champaign, IL, USA 4 Department of Psychology, University of Illinois, Champaign, IL, USA 5 Department of Speech and Hearing Science, University of Illinois, Champaign, IL, USA 6 Neuroscience Program, University of Illinois, Champaign, IL, USA 7 Institute for Genomic Biology, University of Illinois, Champaign, IL, USA
8 Universidad Autónoma de Madrid, Fundación CIEN/Fundación Reina Sofía, Madrid, Spain.
Brain. 2014 Oct;137(Pt 10):2823-33. doi: 10.1093/brain/awu207. Epub 2014 Jul 28.
Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion-symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease.
越来越多的神经科学证据表明,人类智力由额叶和顶叶区域的分布式网络支持,该网络能够实现复杂的、目标导向行为。然而,这个网络对智力功能社会方面的贡献仍有待充分描述。在这里,我们报告一项人类损伤研究(n = 144),该研究调查了社会问题解决的神经基础(通过日常问题解决量表测量),并检验了广泛的心理变量对表现个体差异的预测程度,这些心理变量包括心理测量智力(通过韦氏成人智力量表测量)、情商(通过梅耶、萨洛维、卡鲁索情商测试测量)和人格特质(通过神经质-外向性-开放性人格量表测量)。获取每个变量的分数,随后进行基于体素的损伤-症状映射。逐步回归分析表明,工作记忆、处理速度和情商可预测日常问题解决中的个体差异。对特定日常问题解决领域(涉及朋友、家庭管理、消费主义、工作、信息管理和家庭)的针对性分析揭示了对每个领域有选择性贡献的心理变量。损伤映射结果表明,社会问题解决、心理测量智力和情商由额叶、颞叶和顶叶区域的共享网络支持,包括将这些区域绑定成一个协调系统的白质联合束。这些结果支持了一个理解社会智力的综合框架,并为将日常问题解决量表应用于健康和疾病中的社会问题解决研究提出了具体建议。