Department of Anatomy and Neurobiology, Washington University School of Medicine, Saint Louis, Missouri 63110, USA.
J Neurosci. 2009 Dec 9;29(49):15601-12. doi: 10.1523/JNEUROSCI.2574-09.2009.
The perception of self-motion direction, or heading, relies on integration of multiple sensory cues, especially from the visual and vestibular systems. However, the reliability of sensory information can vary rapidly and unpredictably, and it remains unclear how the brain integrates multiple sensory signals given this dynamic uncertainty. Human psychophysical studies have shown that observers combine cues by weighting them in proportion to their reliability, consistent with statistically optimal integration schemes derived from Bayesian probability theory. Remarkably, because cue reliability is varied randomly across trials, the perceptual weight assigned to each cue must change from trial to trial. Dynamic cue reweighting has not been examined for combinations of visual and vestibular cues, nor has the Bayesian cue integration approach been applied to laboratory animals, an important step toward understanding the neural basis of cue integration. To address these issues, we tested human and monkey subjects in a heading discrimination task involving visual (optic flow) and vestibular (translational motion) cues. The cues were placed in conflict on a subset of trials, and their relative reliability was varied to assess the weights that subjects gave to each cue in their heading judgments. We found that monkeys can rapidly reweight visual and vestibular cues according to their reliability, the first such demonstration in a nonhuman species. However, some monkeys and humans tended to over-weight vestibular cues, inconsistent with simple predictions of a Bayesian model. Nonetheless, our findings establish a robust model system for studying the neural mechanisms of dynamic cue reweighting in multisensory perception.
自我运动方向(或朝向)的感知依赖于多种感觉线索的整合,尤其是视觉和前庭系统的线索。然而,感觉信息的可靠性会迅速且不可预测地变化,目前尚不清楚大脑在这种动态不确定性下如何整合多种感觉信号。人类心理物理学研究表明,观察者通过根据可靠性按比例加权这些线索来组合线索,这与从贝叶斯概率论得出的统计最优整合方案一致。值得注意的是,由于线索可靠性在试验中随机变化,因此每个线索的感知权重必须随试验而变化。尚未对视觉和前庭线索的组合进行动态线索重新加权的研究,也没有将贝叶斯线索整合方法应用于实验室动物,这是朝着理解线索整合的神经基础迈出的重要一步。为了解决这些问题,我们在涉及视觉(光流)和前庭(平移运动)线索的朝向辨别任务中测试了人类和猴子受试者。在一部分试验中,这些线索会发生冲突,其相对可靠性会发生变化,以评估受试者在其朝向判断中对每个线索的权重。我们发现,猴子可以根据其可靠性快速重新加权视觉和前庭线索,这是在非人类物种中的首次此类证明。然而,一些猴子和人类倾向于过度加权前庭线索,这与贝叶斯模型的简单预测不一致。尽管如此,我们的发现为研究多感觉感知中动态线索重新加权的神经机制建立了一个强大的模型系统。