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跨全身运动的空间恒定性的因果推断。

Causal inference for spatial constancy across whole body motion.

机构信息

Donders Institute for Brain, Cognition, and Behaviour, Radboud University , Nijmegen , The Netherlands.

出版信息

J Neurophysiol. 2019 Jan 1;121(1):269-284. doi: 10.1152/jn.00473.2018. Epub 2018 Nov 21.

Abstract

The brain uses self-motion information to internally update egocentric representations of locations of remembered world-fixed visual objects. If a discrepancy is observed between this internal update and reafferent visual feedback, this could be either due to an inaccurate update or because the object has moved during the motion. To optimally infer the object's location it is therefore critical for the brain to estimate the probabilities of these two causal structures and accordingly integrate and/or segregate the internal and sensory estimates. To test this hypothesis, we designed a spatial updating task involving passive whole body translation. Participants, seated on a vestibular sled, had to remember the world-fixed position of a visual target. Immediately after the translation, the reafferent visual feedback was provided by flashing a second target around the estimated "updated" target location, and participants had to report the initial target location. We found that the participants' responses were systematically biased toward the position of the second target position for relatively small but not for large differences between the "updated" and the second target location. This pattern was better captured by a Bayesian causal inference model than by alternative models that would always either integrate or segregate the internally updated target location and the visual feedback. Our results suggest that the brain implicitly represents the posterior probability that the internally updated estimate and the visual feedback come from a common cause and uses this probability to weigh the two sources of information in mediating spatial constancy across whole body motion. NEW & NOTEWORTHY When we move, egocentric representations of object locations require internal updating to keep them in register with their true world-fixed locations. How does this mechanism interact with reafferent visual input, given that objects typically do not disappear from view? Here we show that the brain implicitly represents the probability that both types of information derive from the same object and uses this probability to weigh their contribution for achieving spatial constancy across whole body motion.

摘要

大脑利用自身运动信息对内更新对记忆中世界固定视觉物体位置的自我中心表示。如果观察到内部更新和再传入视觉反馈之间存在差异,这可能是由于更新不准确,或者是因为物体在运动过程中移动了。因此,为了最佳地推断物体的位置,大脑必须估计这两种因果结构的概率,并相应地整合和/或分离内部和感官估计。为了检验这一假设,我们设计了一个涉及被动全身平移的空间更新任务。参与者坐在前庭雪橇上,必须记住视觉目标的世界固定位置。在平移后,通过在估计的“更新”目标位置周围闪烁第二个目标,立即提供再传入的视觉反馈,参与者必须报告初始目标位置。我们发现,参与者的反应系统地偏向于第二个目标位置,对于“更新”和第二个目标位置之间的相对较小的差异,但对于较大的差异则不是。与总是整合或分离内部更新的目标位置和视觉反馈的替代模型相比,贝叶斯因果推理模型更好地捕捉了这种模式。我们的结果表明,大脑隐式表示内部更新的估计和视觉反馈来自共同原因的后验概率,并使用该概率来权衡两种信息源在介导整个身体运动中的空间恒定性方面的贡献。新的和值得注意的是:当我们移动时,物体位置的自我中心表示需要内部更新,以使其与真实的世界固定位置保持一致。在物体通常不会从视野中消失的情况下,这种机制如何与再传入的视觉输入相互作用?在这里,我们表明,大脑隐式表示这两种类型的信息都来自同一物体的概率,并使用该概率来权衡它们在整个身体运动中实现空间恒定性的贡献。

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