Developing Concepts for Neuroscience: A Philosophical Toolkit.
Philipp Haueis, Daniel S Margulies
European Journal of Neuroscience 2026 DOI: 10.1111/ejn.70403 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Topics | Default mode network |
| Keywords | Brain Animals Humans Neurosciences Hierarchy Cortical column Conceptual development Epistemic goals Cortical gradient |
| Key points | Argues that the success or failure of concepts in neuroscience depends on the epistemic goals the field aims to achieve. Through the cases of "default mode network," "cortical column," and "hierarchy," the authors formulate conditions under which introducing, refining, or replacing a concept succeeds or fails, and propose that researchers make explicit which goals they aim to achieve when using a concept. |
Abstract
Alongside models and methods, concepts are crucial tools to study and understand the brain. They help us pursue various goals, such as describing phenomena based on patterns in the data or explaining why these phenomena occur. Yet while terms such as "action potential" or "network" guide our efforts to reach these goals, other concepts have failed to advance our understanding of the brain. In this paper, we draw on recent work from philosophy of science to show that the success or failure of concepts in neuroscience depends on the epistemic goals the field aims to achieve. Looking at cases such as "default mode network," "cortical column," and "hierarchy," we formulate conditions under which introducing, refining, or replacing a concept succeeds or fails. These cases suggest that to better evaluate our concepts, we should make explicit which goals we aim to achieve when using them.