Nachev Parashkev, Hacker Peter
a Institute of Neurology , University College London , London , UK.
Cogn Neurosci. 2014;5(3-4):193-208. doi: 10.1080/17588928.2014.934215. Epub 2014 Jun 30.
The inferential standards for testing hypotheses are settled; those for constructing them rarely even discussed. If the fit to the data of a hypothesis matters, then so must its fundamental coherence. That is indeed prior to any other question. Here we make use of conceptual analysis in testing the coherence of hypotheses in cognitive neuroscience and apply it to the study of the antecedents to voluntary action. We show that many influential experiments in the literature are premised-often covertly-on erroneous conceptions that render their hypotheses incoherent. The inferences drawn from the data are therefore invalidated proximally to any objection empirical replication could counter. We further demonstrate the empirical consequences of these errors in generating artifactual observable effects that have no general significance and impede further progress. We conclude with a basic framework for constructing robust hypotheses in this difficult and important field.
检验假设的推理标准已经确定;而构建假设的标准甚至很少被讨论。如果一个假设与数据的契合度很重要,那么其基本的连贯性也必然如此。这确实先于任何其他问题。在这里,我们利用概念分析来检验认知神经科学中假设的连贯性,并将其应用于对自愿行动前提的研究。我们表明,文献中许多有影响力的实验往往暗中基于错误的概念,这些概念使它们的假设缺乏连贯性。因此,从数据中得出的推论在任何实证复制可能反驳的反对意见之前就失效了。我们进一步证明了这些错误在产生没有普遍意义且阻碍进一步进展的人为可观察效应方面的实证后果。我们以一个在这个困难而重要的领域构建稳健假设的基本框架作为结论。