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Optimality is critical when it comes to testing computation-level hypotheses.

Laura S Geurts¹, Andrey Chetverikov¹, Ruben S van Bergen¹

¹Donders Institute for Brain, Cognition and Behavior,Radboud University Nijmegen,6525 EN Nijmegen,The Netherlands.a.bertana@donders.ru.nla.chetverikov@donders.ru.nljanneke.jehee@donders.ru.nll.geurts@donders.ru.nlr.vanbergen@donders.ru.nly.zhou@donders.ru.nlwww.jeheelab.org.

The Behavioral and Brain Sciences

|February 16, 2019

Summary

This study argues against abandoning optimality in neuroscience research. A normative approach helps test hypotheses about the brain

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Area of Science:

Neuroscience
Cognitive Science
Computational Neuroscience

Background:

Debate exists on the utility of optimality in understanding brain function.
Rahnev & Denison (R&D) proposed abandoning optimality as a research framework.

Purpose of the Study:

To argue for the continued use of a normative, optimality-based approach in neuroscience.
To demonstrate the benefits of normative approaches for testing hypotheses about neural computation.

Main Methods:

Conceptual analysis of research frameworks in neuroscience.
Critique of alternative approaches to understanding brain function.

Main Results:

Normative approaches facilitate hypothesis testing regarding the brain's computational objectives.
Optimality-based research avoids "just-so" explanations.

Conclusions:

Abandoning optimality would limit scientific inquiry into brain function.
A normative framework provides unique insights into neural mechanisms inaccessible through other methods.