Mangalam Madhur
Division of Biomechanics and Research Development, Department of Biomechanics, Center for Research in Human Movement Variability, Omaha, NE, 68182, USA.
Eur J Appl Physiol. 2025 Jun 26. doi: 10.1007/s00421-025-05855-6.
The Bayesian brain hypothesis-the idea that neural systems implement or approximate Bayesian inference-has become a dominant framework in cognitive neuroscience over the past two decades. While mathematically elegant and conceptually unifying, this paper argues that the hypothesis occupies an ambiguous territory between useful metaphor and testable, biologically plausible mechanistic explanation. We critically examine the key claims of the Bayesian brain hypothesis, highlighting issues of unfalsifiability, biological implausibility, and inconsistent empirical support. The framework's remarkable flexibility in accommodating diverse findings raises concerns about its explanatory power, as models can often be adjusted post hoc to fit virtually any data pattern. We contrast the Bayesian approach with alternative frameworks, including dynamic systems theory, ecological psychology, and embodied cognition, which conceptualize prediction and adaptive behavior without recourse to probabilistic inference. Despite its limitations, the Bayesian brain hypothesis persists-driven less by empirical grounding than by its mathematical elegance, metaphorical power, and institutional momentum.
贝叶斯大脑假说——即神经系统实现或近似贝叶斯推理的观点——在过去二十年里已成为认知神经科学的主导框架。尽管该假说在数学上优雅且概念上具有统一性，但本文认为它处于有用的隐喻与可检验的、具有生物学合理性的机制性解释之间的模糊地带。我们批判性地审视了贝叶斯大脑假说的关键主张，突出了不可证伪性、生物学上的不合理性以及不一致的实证支持等问题。该框架在容纳各种发现方面具有显著的灵活性，这引发了对其解释力的担忧，因为模型往往可以事后调整以适应几乎任何数据模式。我们将贝叶斯方法与其他框架进行对比，包括动态系统理论、生态心理学和具身认知，这些框架在不借助概率推理的情况下对预测和适应性行为进行概念化。尽管存在局限性，但贝叶斯大脑假说仍然存在——其持续存在的驱动力与其说是基于实证基础，不如说是基于其数学优雅性、隐喻力量和制度势头。
