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.

Alongside models and methods, concepts are one of the building blocks of neuroscientific inquiry. They help researchers to pursue various goals, such as describing novel patterns in the data, situate these patterns in existing models, formulate new models or build explanations, e.g., of how the brain processes sensory information. Often the formation of novel or reinterpretation of existing concepts can signal major shifts in how we understand the brain and investigate it scientifically. Yet not every novel concept or reinterpretation produces such a shift, which raises the question of when concepts succeed or fail to change our understanding of the brain. In this paper, we introduce analytical tools developed by philosophers of science and concepts of brain organization as examples to discuss when introducing novel, reinterpreting existing and replacing outdated neuroscientific concepts succeeds or fails. Our discussion opens up novel avenues for neuroscientists and philosophers to collaborate around the limits of old and prospects of new concepts describing how the brain is organized.