School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, 100871, China.
Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
J Neurosci. 2021 Apr 21;41(16):3692-3706. doi: 10.1523/JNEUROSCI.2006-20.2021. Epub 2021 Mar 5.
Humans do not have an accurate representation of probability information in the environment but distort it in a surprisingly stereotyped way ("probability distortion"), as shown in a wide range of judgment and decision-making tasks. Many theories hypothesize that humans automatically compensate for the uncertainty inherent in probability information ("representational uncertainty") and probability distortion is a consequence of uncertainty compensation. Here we examined whether and how the representational uncertainty of probability is quantified in the human brain and its relevance to probability distortion behavior. Human subjects (13 female and 9 male) kept tracking the relative frequency of one color of dot in a sequence of dot arrays while their brain activity was recorded by MEG. We found converging evidence from both neural entrainment and time-resolved decoding analysis that a mathematically derived measure of representational uncertainty is automatically computed in the brain, despite it is not explicitly required by the task. In particular, the encodings of relative frequency and its representational uncertainty, respectively, occur at latencies of ∼300 and 400 ms. The relative strength of the brain responses to these two quantities correlates with the probability distortion behavior. The automatic and fast encoding of the representational uncertainty provides neural basis for the uncertainty compensation hypothesis of probability distortion. More generally, since representational uncertainty is closely related to confidence estimation, our findings exemplify how confidence might emerge before perceptual judgment. Human perception of probabilities and relative frequencies can be markedly distorted, which is a potential source of disastrous decisions. But the brain is not just ignorant of probability; probability distortions are highly patterned and similar across different tasks. Recent theoretical work suggests that probability distortions arise from the brain's compensation of its own uncertainty in representing probability. Is such representational uncertainty really computed in the brain? To answer this question, we asked human subjects to track an ongoing stimulus sequence of relative frequencies and recorded their brain responses using MEG. Indeed, we found that the neural encoding of representational uncertainty accompanies that of relative frequency, although the former is not explicitly required by the task.
人类对环境中的概率信息没有准确的表示，但以一种惊人的刻板方式扭曲了它（“概率扭曲”），这在广泛的判断和决策任务中都有体现。许多理论假设人类会自动补偿概率信息中固有的不确定性（“表示不确定性”），而概率扭曲是不确定性补偿的结果。在这里，我们研究了人类大脑中是否以及如何量化概率的表示不确定性，以及它与概率扭曲行为的关系。人类受试者（13 名女性和 9 名男性）在一系列点数组中保持跟踪一种颜色点的相对频率，同时他们的大脑活动由 MEG 记录。我们从神经同步和时间分辨解码分析中都找到了一致的证据，表明大脑中自动计算了一个数学衍生的表示不确定性度量，尽管任务中并没有明确要求。特别是，相对频率及其表示不确定性的编码分别在大约 300 和 400 毫秒时出现。这两个量的大脑反应的相对强度与概率扭曲行为相关。代表不确定性的自动和快速编码为概率扭曲的不确定性补偿假说提供了神经基础。更一般地说，由于表示不确定性与置信度估计密切相关，我们的发现例证了在感知判断之前，信心是如何产生的。人类对概率和相对频率的感知可能会发生明显的扭曲，这是灾难性决策的潜在来源。但是大脑并不仅仅是对概率一无所知；概率扭曲是高度模式化的，在不同任务中相似。最近的理论工作表明，概率扭曲源于大脑对表示概率的自身不确定性的补偿。这种表示不确定性真的在大脑中计算吗？为了回答这个问题，我们要求人类受试者跟踪一个正在进行的相对频率刺激序列，并使用 MEG 记录他们的大脑反应。事实上，我们发现表示不确定性的神经编码伴随着相对频率的编码，尽管任务中并没有明确要求前者。
