A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits
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发表时间：
2019
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通讯作者：
Wenhao Zhang;Si Wu;B. Doiron;T. Lee
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作者：
Wenhao Zhang;Si Wu;B. Doiron;T. Lee
这项研究为如何在神经回路中实施贝叶斯因果推理提供了规范理论。在因果推理等认知过程和线索整合等感知推理中，神经系统在对外部刺激进行推理时需要选择代表潜在因果结构的不同模型。例如，在多感官处理中，神经系统必须根据输入是来自相同还是不同来源，选择是否整合或分离来自不同感官模式的输入来推断感官刺激。做出这种选择是一个模型选择问题，需要计算贝叶斯因子，即集成模型与分离模型之间的似然比。在本文中，我们考虑了多感官处理中的因果推理，并提出了一种基于神经群体代码的新型生成模型，该模型在推理中同时考虑了刺激特征和刺激可靠性。对于诸如航向方向之类的圆形变量，我们的规范理论给出了计算贝叶斯因子的解析解，具有清晰的几何解释，可以通过带有神经群体代码的简单加法机制来实现。数值模拟表明，计算贝叶斯因子的神经元的调整与在背侧内侧上颞叶 (MSTd) 和腹侧顶内 (VIP) 区域中发现的用于视觉前庭处理的“相反神经元”一致。这项研究阐明了大脑中因果推理的潜在神经机制。
This study provides a normative theory for how Bayesian causal inference can be implemented in neural circuits. In both cognitive processes such as causal reasoning and perceptual inference such as cue integration, the nervous systems need to choose different models representing the underlying causal structures when making inferences on external stimuli. In multisensory processing, for example, the nervous system has to choose whether to integrate or segregate inputs from different sensory modalities to infer the sensory stimuli, based on whether the inputs are from the same or different sources. Making this choice is a model selection problem requiring the computation of Bayes factor, the ratio of likelihoods between the integration and the segregation models. In this paper, we consider the causal inference in multisensory processing and propose a novel generative model based on neural population code that takes into account both stimulus feature and stimulus reliability in the inference. In the case of circular variables such as heading direction, our normative theory yields an analytical solution for computing the Bayes factor, with a clear geometric interpretation, which can be implemented by simple additive mechanisms with neural population code. Numerical simulation shows that the tunings of the neurons computing Bayes factor are consistent with the "opposite neurons" discovered in dorsal medial superior temporal (MSTd) and the ventral intraparietal (VIP) areas for visual-vestibular processing. This study illuminates a potential neural mechanism for causal inference in the brain.