Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY, USA.
Department of Neuroscience, Columbia University, New York, NY, USA.
Commun Biol. 2024 Feb 9;7(1):165. doi: 10.1038/s42003-024-05821-6.
Adaptive decision-making often requires one to infer unobservable states based on incomplete information. Bayesian logic prescribes that individuals should do so by estimating the posterior probability by integrating the prior probability with new information, but the neural basis of this integration is incompletely understood. We record fMRI during a task in which participants infer the posterior probability of a hidden state while we independently modulate the prior probability and likelihood of evidence regarding the state; the task incentivizes participants to make accurate inferences and dissociates expected value from posterior probability. Here we show that activation in a region of left parieto-occipital cortex independently tracks the subjective posterior probability, combining its subcomponents of prior probability and evidence likelihood, and reflecting the individual participants' systematic deviations from objective probabilities. The parieto-occipital cortex is thus a candidate neural substrate for humans' ability to approximate Bayesian inference by integrating prior beliefs with new information.
自适应决策通常需要根据不完整的信息推断不可观察的状态。贝叶斯逻辑规定，个体应该通过将先验概率与新信息相结合来估计后验概率，但这种整合的神经基础还不完全清楚。我们在一项任务中记录 fMRI，参与者在推断隐藏状态的后验概率的同时，我们独立地调节关于状态的先验概率和证据的可能性；任务激励参与者做出准确的推断，并将预期价值与后验概率分开。在这里，我们表明，左顶枕叶皮层的一个区域的激活独立地跟踪主观后验概率，结合其先验概率和证据可能性的子成分，并反映个体参与者从客观概率的系统偏差。因此，顶枕叶皮层是人类通过将先验信念与新信息相结合来近似贝叶斯推理的能力的候选神经基质。
