讲座题目：Causal neural modulation of self–other integration and its individual differences
讲座安排 主讲人：林永玲（英国伦敦大学学院） 时间：2026年8月10日 下午15:00 地点：心理学院大楼201 主讲人简介 林永玲，北京师范大学博士，现为英国伦敦大学学院（University College London, UCL）博士后。她主要从事社会认知神经科学研究，关注个体如何在复杂社会情境中形成自我与群体表征，以及这些社会认知过程在精神健康相关问题中的变化。她综合运用计算建模、脑电/脑磁图（EEG/MEG）、功能磁共振成像（fMRI）以及非侵入性经颅聚焦超声脑刺激（TUS）等技术，探索复杂社会行为背后的计算神经机制及其因果基础。相关研究成果发表于 Nature、Trends in Neurosciences、Computers in Human Behavior、NeuroImage 等国际学术期刊。 讲座内容 Navigating complex social environments requires the brain to integrate information about oneself and others, a process referred to as self–other integration. One well-established component of this is self-bias: the tendency to prioritise self-related information over information about others, reflecting its relevance for one’s own goals and interests. As social environments become increasingly complex, however, self-other integration requires more than simply weighting information about individual agents. People compress social information by representing its underlying relational structure, enabling more efficient decision-making. We recently proposed that these combinatorial representations, termed social basis functions, are encoded in the medial prefrontal cortex (Wittmann, Lin et al., Nature, 2025). In this talk, I will present recent work investigating the neural and computational mechanisms of self–other integration. First, I will show causal evidence that the pregenual anterior cingulate cortex (pgACC) contributes to self-bias and social basis functions using focused ultrasound stimulation (TUS), a non-invasive method for deep brain neuromodulation. Second, I will examine whether these social computations are altered in borderline personality disorder and individuals with elevated autistic traits. Together, these findings provide causal evidence that the pgACC contributes to self-other integration, demonstrate the utility of TUS for investigating human cognitive neuroscience, and extend our understanding of how these social computations operate across diverse populations.