Use and usability: concepts of representation in philosophy, neuroscience, cognitive science, and computer science
Representations play a central role in the study of both biological and artificial intelligence, as well as philosophy of mind. Across neuroscience, computer science, and philosophy, a recurring theme is that representations not only carry information but should be “useful” for or “usable” by an agent in some sense. Here, we review how the “usefulness” of representations has been conceptualized and how it figures into different conceptions of representation. We identify and explore four aspects of use and usability: representations generally carry information ; that information may or may not be useful and it may or may not be encoded in a usable format ; and the representations may or may not be used downstream . Building on these four aspects of information and use, we then organize existing perspectives on neural representations into three levels: Representations as Information (Level 1); Representations as Usable (Level 2); and Representations as Used (Level 3). Our account is meant to give readers an appreciation for the diversity of notions of “neural representation,” help them navigate the vast and multi-disciplinary literature on the topic, and help them clarify the appropriate notion of representation for their own investigations. This paper is the result of a Generative Adversarial Collaboration that began at the Cognitive Computational Neuroscience conference in 2021, originally titled “What makes representations ‘useful’?”.
Authors
- Ben Baker (ORCID: https://orcid.org/0000-0003-0027-1372)
- Odelia Schwartz (ORCID: https://orcid.org/0000-0002-6826-1878)
- Richard D. Lange (ORCID: https://orcid.org/0000-0002-1429-8333)
- Andrew Richmond (ORCID: https://orcid.org/0000-0001-7824-7474)
- Rosa Cao (ORCID: https://orcid.org/0000-0002-1726-477X)
- Nikolaus Kriegeskorte
- Xaq Pitkow
Institutions
- Western University (CA)
- U.S. National Science Foundation (US)
- University of Miami (US)
- Rochester Institute of Technology (US)
- Baylor College of Medicine (US)
- Colby College (US)
- University of Rochester (US)
- Rice University (US)
- Carnegie Mellon University (US)
- Columbia University (US)
- Stanford University (US)
Publication Details
- Journal
- Neurons Behavior Data analysis and Theory
- Published
- 2026-04-17
- DOI
- https://doi.org/10.51628/001c.160037
- Primary Topic
- Embodied and Extended Cognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00