Davide Coraci Igor Douven Gustavo Cevolani

Inference and explanation in cognitive neuroscience

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Abstract

Reverse inference is a reasoning strategy widely used in cognitive neuroscience to draw conclusions about cognitive processes from neural activation data, in particular in functional magnetic resonance imaging studies. In the last few years, this type of inference has raised a hot methodological debate, due to its limitations and weaknesses. Some scholars have defended reverse inference as a form of abduction or inference to the best explanation. However, an accurate analysis of what determines the quality of a reverse inference as inference to the best explanation is still lacking in the literature. The present work aims to bridge this gap by providing a qualified defence of reverse inference as inference to the best explanation, based on some recent philosophical and empirical works. Through the discussion of some case studies and their methodology to analyse data, we identify some criteria, as illustrated by the recent philosophical literature, to assess the reliability of the reverse inference as inference to the best explanation for the available evidence

Keywords

  • reverse inference
  • abduction
  • explanation
  • inference to the best explanation
  • magnetic resonance imaging
  • cognitive neuroscience

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