Ten simple rules for the computational modeling of behavioral data
University of Arizona · University of California, Berkeley
Abstract
Computational modeling of behavior has revolutionized psychology and neuroscience. By fitting models to experimental data we can probe the algorithms underlying behavior, find neural correlates of computational variables and better understand the effects of drugs, illness and interventions. But with great power comes great responsibility. Here, we offer ten simple rules to ensure that computational modeling is used with care and yields meaningful insights. In particular, we present a beginner-friendly, pragmatic and details-oriented introduction on how to relate models to data. What, exactly, can a model tell us about the mind? To answer this, we apply our rules to the simplest modeling techniques most…
Citation impact
- FWCI
- 58.18
- Percentile
- 100%
- References
- 114
Authors
2Topics & keywords
- Computational model
- Simple (philosophy)
- Computer science
- Computational neuroscience
- Data science
- Artificial intelligence
- Code (set theory)
- Machine learning