Brun Cédric, Konsman Jan Pieter, Polger Thomas
University of Bordeaux-Montaigne, Pessac, France.
University of Bordeaux and CNRS, Bordeaux, France.
Eur J Neurosci. 2025 Jan;61(2):e16655. doi: 10.1111/ejn.16655.
The nature of explanation is an important area of inquiry in philosophy of science. Consensus has been that explanation in the cognitive and brain sciences is typically a special case of causal explanation, specifically, mechanistic explanation. But recently there has been increased attention to computational explanation in the brain sciences and to whether that can be understood as a variety of mechanistic explanation. After laying out the stakes for a proper understanding of scientific explanation, we consider the status of computational explanation in the brain sciences by comparing the mechanistic proposal to computational accounts advanced by Piccinini, Milkowski, Cao, Chirimuuta and Ross. We argue that many of these accounts of computational explanation in neuroscience can satisfy the same explanatory criteria as causal explanations, but not all. This has implications for interpretation of those computational explanations that satisfy different criteria.
解释的本质是科学哲学中一个重要的探究领域。人们已达成的共识是，认知科学和脑科学中的解释通常是因果解释的一种特殊情况，具体而言，是机制性解释。但最近，脑科学中的计算解释以及它是否可被理解为机制性解释的一种受到了更多关注。在阐述了正确理解科学解释的利害关系后，我们通过将机制性观点与皮奇尼尼、米尔科夫斯基、曹、奇里穆塔和罗斯提出的计算性解释进行比较，来考量脑科学中计算解释的地位。我们认为，神经科学中许多关于计算解释的观点都能满足与因果解释相同的解释标准，但并非全部如此。这对那些满足不同标准的计算解释的解读具有启示意义。
