Mastrogiorgio Antonio
IMT School for Advanced Studies Lucca, Lucca, Italy.
Front Psychol. 2022 Jul 8;13:869894. doi: 10.3389/fpsyg.2022.869894. eCollection 2022.
Predictive brain theory challenges the general assumption of a brain extracting knowledge from sensations and considers the brain as an organ of inference, actively constructing explanations about reality beyond its sensory evidence. Predictive brain has been formalized through Bayesian updating, where top-down predictions are compared with bottom-up evidence. In this article, we propose a different approach to predictive brain based on quantum probability-we call it Quantum Predictive Brain (QPB). QPB is consistent with the Bayesian framework, but considers it as a special case. The tenet of QPB is that top-down predictions and bottom-up evidence are complementary, as they cannot be co-jointly determined to pursue a univocal model of brain functioning. QPB can account for several high-order cognitive phenomena (which are problematic in current predictive brain theories) and offers new insights into the mechanisms of neural reuse.
预测性大脑理论挑战了大脑从感觉中提取知识的一般假设,并将大脑视为一个推理器官,积极构建超越其感官证据的关于现实的解释。预测性大脑已通过贝叶斯更新形式化,其中自上而下的预测与自下而上的证据进行比较。在本文中,我们基于量子概率提出了一种不同的预测性大脑方法——我们称之为量子预测性大脑(QPB)。QPB与贝叶斯框架一致,但将其视为一种特殊情况。QPB的原则是,自上而下的预测和自下而上的证据是互补的,因为它们不能共同确定以追求大脑功能的单一模型。QPB可以解释几种高阶认知现象(这在当前的预测性大脑理论中存在问题),并为神经重用机制提供新的见解。