How to Explain Behavior?
Open accessAbstract
Unlike behaviorism, cognitive psychology relies on mental concepts to explain behavior. Yet mental processes are not directly observable and multiple explanations are possible, which poses a challenge for finding a useful framework. In this article, I distinguish three new frameworks for explanations that emerged after the cognitive revolution. The first is called tools‐to‐theories : Psychologists' new tools for data analysis, such as computers and statistics, are turned into theories of mind. The second proposes as‐if theories: Expected utility theory and Bayesian statistics are turned into theories of mind, describing an optimal solution of a problem but not its psychological process. The third studies the adaptive toolbox (formal models of heuristics) that describes mental processes in situations of uncertainty where an optimal solution is unknown. Depending on which framework researchers choose, they will model behavior in either situations of risk or of uncertainty, and construct models of cognitive processes or not. The frameworks also determine what questions are asked and what kind of data are generated. What all three frameworks have in common, however, is a clear preference for formal models rather than explanations by general dichotomies or mere verbal concepts. The frameworks have considerable potential to inform each other and to generate points of integration.
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The mathematization of neuroscience reflects broader trends across the sciences, where quantitative approaches tend to displace qualitative ones regardless of explanatory adequacy.
“This “mathematization” of neuroscience reflects broader trends across the sciences, where quantitative approaches tend to displace qualitative ones, regardless of their explanatory adequacy (Gigerenzer and Brighton 2009; Gigerenzer 2020).”
From The myth of the Bayesian brain (2025) · cites this paper as Gigerenzer 2020
Section 4.1 (‘Bayesian brains’; page unavailable) describes quantitative models of cognitive processes, including their neural underpinnings. Section 3.2 (‘Mind as computer’; page unavailable) describes analytical tools shaping theories in other fields and questions whether mathematical sophistication solves genuine problems. The paper does not establish the broader claim that quantitative approaches tend to displace qualitative ones across the sciences regardless of explanatory adequacy. (LLM, conf=0.83)
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“This “mathematization” of neuroscience reflects broader trends across the sciences, where quantitative approaches tend to displace qualitative ones, regardless of their explanatory adequacy (Gigerenzer and Brighton 2009; Gigerenzer 2020).”
- Authors
- Gigerenzer, G.
- Affiliations
- Max Planck Society (DE)
- Corresponding author
- Gigerenzer, Gerd
- ORCID
- Gigerenzer, Gerd
- Venue
- Topics in Cognitive Science
- Publisher
- Wiley
- Published
- 2019-11-06
- Volume
- 12
- Issue
- 4
- Pages
- 1363-1381
- ISSN
- 1756-8757 (ISSN-L)
- 1756-8765
- OpenAlex
- W2985815064
- Cited by
- 48
- References
- 80
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 6 · 2023: 9 · 2022: 10 · 2021: 5 · 2020: 5
- FWCI
- 4.01
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Topics in Cognitive Science (publishedVersion, cc-by)
- PubMed (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Psychology › General Psychology › Academic and Historical Perspectives in Psychology
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- explanation of behavior, cognitive revolution, theory of mind, expected utility theory, Bayesian analysis, adaptive toolbox, heuristics, formal models, risk and uncertainty, cognitive processes, behaviorism
- MeSH terms
- Heuristics, Bayes Theorem, Cognition, Humans
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