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Representations of uncertainty: where art thou?
Current Opinion in Behavioral Sciences ( IF 5 ) Pub Date : 2021-04-01 , DOI: 10.1016/j.cobeha.2021.03.009 Ádám Koblinger 1 , József Fiser 1 , Máté Lengyel 1, 2
Current Opinion in Behavioral Sciences ( IF 5 ) Pub Date : 2021-04-01 , DOI: 10.1016/j.cobeha.2021.03.009 Ádám Koblinger 1 , József Fiser 1 , Máté Lengyel 1, 2
Affiliation
Perception is often described as probabilistic inference requiring an internal representation of uncertainty. However, it is unknown whether uncertainty is represented in a task-dependent manner, solely at the level of decisions, or in a fully Bayesian manner, across the entire perceptual pathway. To address this question, we first codify and evaluate the possible strategies the brain might use to represent uncertainty, and highlight the normative advantages of fully Bayesian representations. In such representations, uncertainty information is explicitly represented at all stages of processing, including early sensory areas, allowing for flexible and efficient computations in a wide variety of situations. Next, we critically review neural and behavioral evidence about the representation of uncertainty in the brain agreeing with fully Bayesian representations. We argue that sufficient behavioral evidence for fully Bayesian representations is lacking and suggest experimental approaches for demonstrating the existence of multivariate posterior distributions along the perceptual pathway.
中文翻译:
不确定性的表征:你在哪里?
感知通常被描述为需要不确定性的内部表示的概率推理。然而,尚不清楚不确定性是否以任务相关的方式(仅在决策层面)表示,还是以完全贝叶斯方式在整个感知路径上表示。为了解决这个问题,我们首先整理和评估大脑可能用来表示不确定性的可能策略,并强调完全贝叶斯表示的规范优势。在这种表示中,不确定性信息在处理的所有阶段都得到明确表示,包括早期感觉区域,从而允许在各种情况下进行灵活有效的计算。接下来,我们批判性地回顾关于大脑中不确定性表示的神经和行为证据,这些证据与完全贝叶斯表示一致。我们认为,缺乏充分的贝叶斯表示的足够的行为证据,并提出了实验方法来证明沿着感知路径存在多元后验分布。
更新日期:2021-04-01
中文翻译:
不确定性的表征:你在哪里?
感知通常被描述为需要不确定性的内部表示的概率推理。然而,尚不清楚不确定性是否以任务相关的方式(仅在决策层面)表示,还是以完全贝叶斯方式在整个感知路径上表示。为了解决这个问题,我们首先整理和评估大脑可能用来表示不确定性的可能策略,并强调完全贝叶斯表示的规范优势。在这种表示中,不确定性信息在处理的所有阶段都得到明确表示,包括早期感觉区域,从而允许在各种情况下进行灵活有效的计算。接下来,我们批判性地回顾关于大脑中不确定性表示的神经和行为证据,这些证据与完全贝叶斯表示一致。我们认为,缺乏充分的贝叶斯表示的足够的行为证据,并提出了实验方法来证明沿着感知路径存在多元后验分布。