Abstract
Recently, a version of realism has been offered to address the simplification strategies
used in computational neuroscience (Chirimuuta, 2023; 2024). According to this view, computational
models provide us with knowledge about the brain, but they should not be taken literally in any sense, even
rejecting the idea that the brain performs computations (computationalism). I acknowledge the need for
considerations regarding simplification strategies in neuroscience and how they contribute to our
interpretations of computational models; however, I argue that whether we should accept or reject
computationalism about the brain is a separate issue that can be addressed independently by a philosophical
theory of physical computation. This takes seriously the idea that the brain performs computations while
also taking an analogical stance toward computational models in neuroscience. I call this version of realism
“Analogical Computational Realism.” Analogical Computational Realism is a realist view in virtue of being
committed to computationalism while taking certain computational models to pick out real patterns
(Dennett, 1991; Potochnik, 2017) that provide a how-possibly explanation without also thinking that the
model is literally implemented in the brain.