PDF(Pubmed)
Abstract：
Cross-situational inconsistency is common in the expression of honesty traits; yet, there is insufficient emphasis on behavioral dishonesty across multiple contexts. The current study aimed to investigate behavioral dishonesty in various contexts and reveal the associations between trait honesty, behavioral dishonesty, and neural patterns of observing others behave honestly or dishonestly in videos (abbr.: (dis)honesty video-watching). First, the results revealed limitations in using trait honesty to reflect variations in dishonest behaviors and predict behavioral dishonesty. The finding highlights the importance of considering neural patterns in understanding and predicting dishonest behaviors. Second, by comparing the predictive performance of seven types of data across three neural networks, the results showed that functional connectivity in the hypothesis-driven network during (dis)honesty video-watching provided the highest predictive power in predicting multitask behavioral dishonesty. Last, by applying the feature elimination method, the midline self-referential regions (medial prefrontal cortex, posterior cingulate cortex, and anterior cingulate cortex), anterior insula, and striatum were identified as the most informative brain regions in predicting behavioral dishonesty. In summary, the study offered insights into individual differences in deception and the intricate connections among trait honesty, behavioral dishonesty, and neural patterns during (dis)honesty video-watching.
摘要：
跨情境的不一致在诚实特征的表达中很常见；然而，在多个背景下，对行为不诚实的重视不够。当前的研究旨在调查各种情况下的行为不诚实，并揭示特质诚实之间的关联，行为不诚实，和观察他人的神经模式在视频中诚实或不诚实地表现(缩写。：（dis）诚实视频观看）。首先,结果表明，使用特质诚实来反映不诚实行为的变化并预测行为不诚实的局限性。这一发现强调了在理解和预测不诚实行为时考虑神经模式的重要性。第二,通过比较三种神经网络中七种类型数据的预测性能，结果表明，在（dis）诚实视频观看期间，假设驱动的网络中的功能连通性在预测多任务行为不诚实方面提供了最高的预测能力。最后,通过应用特征消除方法，中线自我参照区(内侧前额叶皮层，后扣带皮质，和前扣带皮质)，前岛,纹状体被认为是预测行为不诚实的信息最多的大脑区域。总之,这项研究提供了对欺骗的个体差异和特质诚实之间错综复杂的联系的见解，行为不诚实，和神经模式在（不）诚实的视频观看。
