Reasoning Goals and Representational Decisions in Computational Cognitive Neuroscience: Lessons From the Drift Diffusion Model DOI

Ari Khoudary,

Megan A. K. Peters, Aaron M. Bornstein

et al.

European Journal of Neuroscience, Journal Year: 2025, Volume and Issue: 61(7)

Published: April 1, 2025

ABSTRACT Computational cognitive models are powerful tools for enhancing the quantitative and theoretical rigor of neuroscience. It is thus imperative that model users—researchers who develop models, use existing or integrate model‐based findings into their own research—understand how these work what factors need to be considered when engaging with them. To this end, we developed a philosophical toolkit addresses core questions about computational in brain behavioral sciences. Drawing on recent advances philosophy modeling, highlight central role users' reasoning goals application interpretation formal models. We demonstrate utility perspective by first offering introduction highly popular drift diffusion (DDM) then providing novel conceptual analysis long‐standing debate decision thresholds DDM. Contrary most work, suggest two structures implicated offer complementary—rather than competing—explanations speeded choice behavior. Further, show type explanation provided each form (parsimonious normative) reflects communities users them (cognitive psychometricians scientists, respectively). conclude our readers principled heuristic deciding which use, concretely demonstrating practical resolving meta‐scientific challenges

Language: Английский

Reasoning Goals and Representational Decisions in Computational Cognitive Neuroscience: Lessons From the Drift Diffusion Model DOI

Ari Khoudary,

Megan A. K. Peters, Aaron M. Bornstein

et al.

European Journal of Neuroscience, Journal Year: 2025, Volume and Issue: 61(7)

Published: April 1, 2025

ABSTRACT Computational cognitive models are powerful tools for enhancing the quantitative and theoretical rigor of neuroscience. It is thus imperative that model users—researchers who develop models, use existing or integrate model‐based findings into their own research—understand how these work what factors need to be considered when engaging with them. To this end, we developed a philosophical toolkit addresses core questions about computational in brain behavioral sciences. Drawing on recent advances philosophy modeling, highlight central role users' reasoning goals application interpretation formal models. We demonstrate utility perspective by first offering introduction highly popular drift diffusion (DDM) then providing novel conceptual analysis long‐standing debate decision thresholds DDM. Contrary most work, suggest two structures implicated offer complementary—rather than competing—explanations speeded choice behavior. Further, show type explanation provided each form (parsimonious normative) reflects communities users them (cognitive psychometricians scientists, respectively). conclude our readers principled heuristic deciding which use, concretely demonstrating practical resolving meta‐scientific challenges

Language: Английский

Citations

0