Abductive reasoning in cognitive neuroscience: weak and strong reverse inference

Synthese 200 (2):1-26 (2022)
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Abstract

Reverse inference is a crucial inferential strategy used in cognitive neuroscience to derive conclusions about the engagement of cognitive processes from patterns of brain activation. While widely employed in experimental studies, it is now viewed with increasing scepticism within the neuroscience community. One problem with reverse inference is that it is logically invalid, being an instance of abduction in Peirce’s sense. In this paper, we offer the first systematic analysis of reverse inference as a form of abductive reasoning and highlight some relevant implications for the current debate. We start by formalising an important distinction that has been entirely neglected in the literature, namely the distinction between weak and strong reverse inference. Then, we rely on case studies from recent neuroscientific research to systematically discuss the role and limits of both strong and weak reverse inference; in particular, we offer the first exploration of weak reverse inference as a discovery strategy within cognitive neuroscience.

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Author Profiles

Fabrizio Calzavarini
University of Turin (PhD)
Gustavo Cevolani
IMT School For Advanced Studies Lucca

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References found in this work

Inference to the Best Explanation.Peter Lipton - 1991 - London and New York: Routledge.
Bayesian Philosophy of Science.Jan Sprenger & Stephan Hartmann - 2019 - Oxford and New York: Oxford University Press.
The material theory of induction.John D. Norton - 2021 - Calgary, Alberta, Canada: University of Calgary Press.
The inference to the best explanation.Gilbert H. Harman - 1965 - Philosophical Review 74 (1):88-95.

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