Jornkokgoud Khanitin, Bakiaj Richard, Wongupparaj Peera, Job Remo, Grecucci Alessandro
Department of Research and Applied Psychology, Faculty of Education, Burapha University, Chon Buri, Thailand.
Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, Rovereto, Italy.
Psychophysiology. 2025 Aug;62(8):e70130. doi: 10.1111/psyp.70130.
The neural bases of narcissistic and antisocial traits remain under debate. A key question is whether these traits are encoded within the triple network-comprising the default mode (DMN), salience (SN), and fronto-parietal (FPN) networks-and whether they impact these networks similarly. We conducted connectome-based analyses on resting-state fMRI data from 183 participants, examining graph-theoretical metrics in the DMN, SN, and FPN, using the visual and sensorimotor networks as controls. Predictive models of narcissistic and antisocial traits were developed using stepwise multiple regression and Random Forest regression to ensure generalizability. Seed-based analyses were conducted using regions identified by these models. Our findings revealed clear involvement of the triple network in both traits, supporting a shared neural substrate. Both traits were negatively predicted by the anterior cingulate cortex of the SN, reflecting reduced danger awareness and increased risky behaviors. Conversely, both were positively predicted by the lateral prefrontal cortex of the FPN, suggesting augmented strategic thinking to manipulate others and increased planning skills to achieve personal goals. Besides similarities, there were differences. Specific hubs of the DMN were positively associated with narcissism but negatively with antisocial traits, possibly explaining their differences in self-reflection and thinking about the self, largely present in the former, but usually reduced in the latter. These results expand on prior evidence linking the triple network to personality traits and suggest both shared and distinct neural mechanisms for narcissism and antisociality. These findings may help inform the development of biomarkers for personality pathology and guide biologically informed interventions.
自恋和反社会特质的神经基础仍存在争议。一个关键问题是，这些特质是否编码在由默认模式网络（DMN）、突显网络（SN）和额顶叶网络（FPN）组成的三重网络中，以及它们对这些网络的影响是否相似。我们对183名参与者的静息态功能磁共振成像数据进行了基于连接组的分析，以视觉和感觉运动网络作为对照，检查DMN、SN和FPN中的图论指标。使用逐步多元回归和随机森林回归开发自恋和反社会特质的预测模型，以确保模型的通用性。使用这些模型确定的区域进行基于种子点的分析。我们的研究结果表明，三重网络在这两种特质中均有明显参与，支持了共享神经基质的观点。两种特质均被SN的前扣带回皮质负向预测，反映出危险意识降低和危险行为增加。相反，两种特质均被FPN的外侧前额叶皮质正向预测，表明用于操纵他人的战略思维增强以及实现个人目标的计划能力提高。除了相似之处，也存在差异。DMN的特定枢纽与自恋呈正相关，但与反社会特质呈负相关，这可能解释了它们在自我反思和自我认知方面的差异，这种差异在自恋中很明显，但在反社会特质中通常减弱。这些结果扩展了之前将三重网络与人格特质联系起来的证据，并揭示了自恋和反社会行为中共同和独特的神经机制。这些发现可能有助于为个性病理学生物标志物的开发提供信息，并指导基于生物学的干预措施。
