Department of Psychiatry, Yale University, New Haven, CT 06511, USA.
Behav Brain Sci. 2013 Jun;36(3):298-9. doi: 10.1017/S0140525X12003044.
Pothos & Busemeyer (P&B) argue convincingly that quantum probability offers an improvement over classical Bayesian probability in modeling the empirical data of cognitive science. However, a weakness related to restrictions on the dimensionality of incompatible physical observables flows from the authors' "agnosticism" regarding quantum processes in neural substrates underlying cognition. Addressing this problem will require either future research findings validating quantum neurophysics or theoretical expansion of the uncertainty principle as a new, neurocognitively contextualized, "local" symmetry.
波托斯和布塞迈尔(P&B)令人信服地认为,在对认知科学的经验数据进行建模方面,量子概率为经典贝叶斯概率提供了一种改进。然而,作者对认知神经基质中量子过程的“不可知论”,导致了与不相容物理可观测量的维度限制有关的一个弱点。解决这个问题需要未来的研究结果验证量子神经物理学,或者扩展不确定性原理作为一种新的、神经认知情境化的“局部”对称性。