社会注意力的精确调节

Wenhui Gao, Changbo Zhu, Bailu Si, Liqin Zhou, Ke Zhou
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摘要

由凝视方向等线索引导的社交注意力对于有效的社交互动至关重要。然而,动态环境背景如何调节这一过程仍不清楚。本研究将分层贝叶斯模型与 fMRI 相结合,探讨了个体如何根据对线索有效性(CV)的预测来调整注意力。33 名参与者在不同的 CV 条件下完成了经改进的 Posner 位置线索任务。从行为上看,个体的社会注意力分配与 CV 预测的精确度(反方差)密切相关,而预测是由目标位置出现的精确度加权预测误差(PE)更新的。神经影像学结果显示,社交注意力分配与 CV 之间的相互作用影响了空间注意力和/或社交感知相关区域的活动,如颞顶交界处(TPJ)、额叶眼区(FEF)、颞上沟(STS)和顶下沟(IPS)。关于目标位置的精确加权PE特别调节了TPJ、STS和初级视觉皮层(V1)的活动,强调了它们在完善注意预测中的作用。动态因果建模(DCM)进一步证明,增强的目标位置绝对精度加权PE加强了从V1和STS到TPJ的有效连接,强调了它们在将残余错误信号从低级感觉区域传递到高级关键注意区域中的作用。这些发现阐明了情境预测的精确性是如何动态调节社会注意力的,为研究情境依赖型社会注意力的计算和神经认知机制提供了见解。
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Precision-dependent modulation of social attention
Social attention, guided by cues like gaze direction, is crucial for effective social interactions. However, how dynamic environmental context modulates this process remains unclear. Integrating a hierarchical Bayesian model with fMRI, this study investigated how individuals adjusted attention based on the predictions about cue validity (CV). Thirty-three participants performed a modified Posner location-cueing task with varying CV. Behaviorally, individuals' allocation of social attention was finely tuned to the precision (inverse variance) of CV predictions, with the predictions being updated by precision-weighted prediction errors (PEs) about the occurrence of target locations. Neuroimaging results revealed that the interaction between allocation of social attention and CV influenced activity in regions involved in spatial attention and/or social perception, such as the temporoparietal junction (TPJ), frontal eye field (FEF), superior temporal sulcus (STS), and inferior parietal sulcus (IPS). Precision-weighted PEs about target locations specifically modulated activity in the TPJ, STS, and primary visual cortex (V1), underscoring their roles in refining attentional predictions. Dynamic causal modeling (DCM) further demonstrated that enhanced absolute precision-weighted PEs about target locations strengthened the effective connectivity from V1 and STS to TPJ, emphasizing their roles in conveying residual error signals from low-level sensory areas to high-level critical attention areas. These findings elucidated how the precision of contextual predictions dynamically modulated social attention, offering insights into the computational and neurocognitive mechanisms of context-dependent social attention.
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