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Circular and unified analysis in network neuroscience

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  • Rubinov, Mikail

Abstract

Genuinely new discovery transcends existing knowledge. Despite this, many analyses in neuroscience neglect to test new theoretical models against known biological facts. Some of these analyses use circular reasoning to present existing knowledge as new discovery. Here I illustrate the nature of this problem in network neuroscience. I describe that this problem can confound key results. I estimate that the problem has affected roughly three thousand studies over the last decade. I seek to counter the problem by spotlighting some of its enablers, and by describing a unified framework for testing new models against strong rival models. I conclude by proposing ways to prevent the problem in future studies.

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  • Rubinov, Mikail, 2022. "Circular and unified analysis in network neuroscience," OSF Preprints mdqak, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:mdqak
    DOI: 10.31219/osf.io/mdqak
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