Centre for Functional MRI of the Brain (FMRIB), John Radcliffe Hospital, Oxford University, Oxford OX3 9DU, United Kingdom.
Proc Natl Acad Sci U S A. 2013 Sep 17;110(38):E3660-9. doi: 10.1073/pnas.1305373110. Epub 2013 Aug 28.
Brains use predictive models to facilitate the processing of expected stimuli or planned actions. Under a predictive model, surprising (low probability) stimuli or actions necessitate the immediate reallocation of processing resources, but they can also signal the need to update the underlying predictive model to reflect changes in the environment. Surprise and updating are often correlated in experimental paradigms but are, in fact, distinct constructs that can be formally defined as the Shannon information (IS) and Kullback-Leibler divergence (DKL) associated with an observation. In a saccadic planning task, we observed that distinct behaviors and brain regions are associated with surprise/IS and updating/DKL. Although surprise/IS was associated with behavioral reprogramming as indexed by slower reaction times, as well as with activity in the posterior parietal cortex [human lateral intraparietal area (LIP)], the anterior cingulate cortex (ACC) was specifically activated during updating of the predictive model (DKL). A second saccade-sensitive region in the inferior posterior parietal cortex (human 7a), which has connections to both LIP and ACC, was activated by surprise and modulated by updating. Pupillometry revealed a further dissociation between surprise and updating with an early positive effect of surprise and late negative effect of updating on pupil area. These results give a computational account of the roles of the ACC and two parietal saccade regions, LIP and 7a, by which their involvement in diverse tasks can be understood mechanistically. The dissociation of functional roles between regions within the reorienting/reprogramming network may also inform models of neurological phenomena, such as extinction and Balint syndrome, and neglect.
大脑利用预测模型来促进对预期刺激或计划动作的处理。在预测模型下，出乎意料的（低概率）刺激或动作需要立即重新分配处理资源，但它们也可以表明需要更新基础预测模型以反映环境变化。在实验范式中，惊讶和更新通常是相关的，但实际上它们是可以正式定义为与观察相关的香农信息（IS）和 Kullback-Leibler 散度（DKL）的不同结构。在眼跳计划任务中，我们观察到不同的行为和大脑区域与惊讶/IS 和更新/DKL 相关。虽然惊讶/IS 与行为重新编程有关，如反应时间变慢，以及与顶后皮质[人类外侧顶内区（LIP）]的活动有关，但在前扣带皮层（ACC）中，特别是在预测模型更新（DKL）期间被激活。第二个在后下顶叶皮质中的眼跳敏感区域（人类 7a），与 LIP 和 ACC 都有连接，它被惊讶激活，并被更新调制。瞳孔测量法揭示了惊讶和更新之间的进一步分离，惊讶有早期的正效应，更新有晚期的负效应。这些结果通过对 ACC 和两个顶叶眼跳区域（LIP 和 7a）的计算解释，说明了它们在不同任务中的参与可以通过机制理解。在重新定向/重新编程网络内的区域之间的功能角色的分离也可能为神经现象的模型提供信息，如消退和 Balint 综合征和忽视。
