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<p>Shiffrin et al. (<CitationRef CitationID="CR13">2026</CitationRef>) explore “illusions of understanding” in science, primarily focusing on linear regression. This comment extends their ideas to Evidence Accumulation Models (EAMs) in cognitive science. I examine four distinct ways EAMs can be understood: as cognitive processes, neural mechanisms, statistical descriptors, and choice rules. I argue that while EAMs may foster illusions of mechanistic transparency, they remain vital “common languages” for bridging behavioral and neural levels of analysis.</p>

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Multiple Ways of Understanding Evidence Accumulation Models: A Comment

  • 期刊论文

  • 发表日期：

    2026年4月9日

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  • Viktor Timokhov

摘要

Shiffrin et al. (2026) explore “illusions of understanding” in science, primarily focusing on linear regression. This comment extends their ideas to Evidence Accumulation Models (EAMs) in cognitive science. I examine four distinct ways EAMs can be understood: as cognitive processes, neural mechanisms, statistical descriptors, and choice rules. I argue that while EAMs may foster illusions of mechanistic transparency, they remain vital “common languages” for bridging behavioral and neural levels of analysis.