Loued-Khenissi Leyla, Preuschoff Kerstin
Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Swiss Center for Affective Sciences, University of Geneva, Geneva, Switzerland.
Front Artif Intell. 2020 Feb 28;3:5. doi: 10.3389/frai.2020.00005. eCollection 2020.
Uncertainty presents a problem for both human and machine decision-making. While utility maximization has traditionally been viewed as the motive force behind choice behavior, it has been theorized that uncertainty minimization may supersede reward motivation. Beyond reward, decisions are guided by belief, i.e., confidence-weighted expectations. Evidence challenging a belief evokes surprise, which signals a deviation from expectation (stimulus-bound surprise) but also provides an information gain. To support the theory that uncertainty minimization is an essential drive for the brain, we probe the neural trace of uncertainty-related decision variables, namely confidence, surprise, and information gain, in a discrete decision with a deterministic outcome. Confidence and surprise were elicited with a gambling task administered in a functional magnetic resonance imaging experiment, where agents start with a uniform probability distribution, transition to a non-uniform probabilistic state, and end in a fully certain state. After controlling for reward expectation, we find confidence, taken as the negative entropy of a trial, correlates with a response in the hippocampus and temporal lobe. Stimulus-bound surprise, taken as Shannon information, correlates with responses in the insula and striatum. In addition, we also find a neural response to a measure of information gain captured by a confidence error, a quantity we dub accuracy. BOLD responses to accuracy were found in the cerebellum and precuneus, after controlling for reward prediction errors and stimulus-bound surprise at the same time point. Our results suggest that, even absent an overt need for learning, the human brain expends energy on information gain and uncertainty minimization.
不确定性对人类和机器的决策都构成了一个问题。虽然传统上效用最大化被视为选择行为背后的驱动力，但理论认为不确定性最小化可能会取代奖励动机。除了奖励之外，决策还受到信念的引导，即信心加权期望。挑战信念的证据会引发惊讶，这既表明与预期存在偏差（刺激引发的惊讶），也提供了信息增益。为了支持不确定性最小化是大脑的一种基本驱动力这一理论，我们在一个具有确定性结果的离散决策中，探究与不确定性相关的决策变量（即信心、惊讶和信息增益）的神经痕迹。在一项功能磁共振成像实验中通过赌博任务来引发信心和惊讶，在该实验中，参与者从均匀概率分布开始，过渡到非均匀概率状态，最后处于完全确定的状态。在控制了奖励期望之后，我们发现，将信心视为一次试验的负熵，它与海马体和颞叶的反应相关。将刺激引发的惊讶视为香农信息，它与脑岛和纹状体的反应相关。此外，我们还发现了对由信心误差捕获的信息增益度量（我们将这个量称为准确性）的神经反应。在同时控制了奖励预测误差和刺激引发的惊讶之后，在小脑和楔前叶中发现了对准确性的血氧水平依赖（BOLD）反应。我们的结果表明，即使没有明显的学习需求，人类大脑也会在信息增益和不确定性最小化上消耗能量。
