Explanatory relevance across disciplinary boundaries: the case of neuroeconomics
Abstract
Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.
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In Dhurandhar et al., the proximity of the selected counterexample to the test point is guaranteed by using an autoencoder.
“However, the proximity of the selected counterexample to the test point is, in this case, guaranteed by using an autoencoder.”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [135]
Dhurandhar et al. address an optimization problem over a perturbation variable to produce a contrastive explanation for the image classification task.
“Similarly, Dhurandhar et al. address an optimization problem over a perturbation variable to produce a contrastive explanation for the image classification task [135].”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [135]
Visual input data are explained by depicting critical regions absent in the input data example that determine what lacks in the image to be classified differently.
“by depicting critical regions absent in the input data example that determine what lacks in the image to be classified differently [135]”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [135]
Cites
What we can do and what we cannot do with fMRI
Logothetis, N. K. (2008) · Nature · doi:10.1038/nature06976 · Cited by 3,612 · see citing works
Making things happen: a theory of causal explanation
(2004) · Choice Reviews Online · doi:10.5860/choice.41-5840 · Cited by 3,383 · see citing works
The person and the situation: perspectives of social psychology
(1992) · Choice Reviews Online · doi:10.5860/choice.29-3604 · Cited by 2,205 · see citing works
Neuroeconomics: How Neuroscience Can Inform Economics
Camerer, C. F., Loewenstein, G. F., & Prelec, D. (2005) · Journal of Economic Literature · doi:10.1257/0022051053737843 · Cited by 2,146 · see citing works
Discovering complexity: decomposition and localization as strategies in scientific research
(1993) · Choice Reviews Online · doi:10.5860/choice.30-6134 · Cited by 1,294 · see citing works
The Neural Basis of Financial Risk Taking
Kuhnen, C. M., & Knutson, B. (2005) · Neuron · doi:10.1016/j.neuron.2005.08.008 · Cited by 1,182 · see citing works
The Seductive Allure of Neuroscience Explanations
Weisberg, D. S., Keil, F. C., Goodstein, J., Rawson, E., & Gray, J. R. (2007) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.20040 · Cited by 1,086 · see citing works
Explaining the brain : mechanisms and the mosaic unity of neuroscience
Craver, C. F. (2007) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199299317.001.0001 · Cited by 986 · see citing works
Social neuroeconomics: the neural circuitry of social preferences
Fehr, E., & Camerer, C. F. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.09.002 · Cited by 779 · see citing works
Material Markets: How Economic Agents are ConstructedPreprint
Mackenzie, D. A. (2008) · RePEc: Research Papers in Economics · Cited by 661 · see citing works
Seeing is believing: The effect of brain images on judgments of scientific reasoning
McCabe, D. P., & Castel, A. D. (2007) · Cognition · doi:10.1016/j.cognition.2007.07.017 · Cited by 658 · see citing works
Risky business: the neuroeconomics of decision making under uncertainty
Platt, M. L., & Huettel, S. A. (2008) · Nature Neuroscience · doi:10.1038/nn2062 · Cited by 556 · see citing works
The Case for Mindless Economics
Gül, F., & Pesendorfer, W. (2008) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195328318.003.0001 · Cited by 541 · see citing works
Mental Mechanisms: Philosophical Perspectives on Cognitive Neuroscience
Bechtel, W. (2007) · Medical Entomology and Zoology · Cited by 466 · see citing works
What can Functional Neuroimaging Tell the Experimental Psychologist?
Henson, R. (2005) · The Quarterly Journal of Experimental Psychology Section A · doi:10.1080/02724980443000502 · Cited by 327 · see citing works
Ylikoski, P., & Kuorikoski, J. (2008) · Philosophical Studies · doi:10.1007/s11098-008-9324-z · Cited by 280 · see citing works
Self-citationThe Mind's Arrows: Bayes Nets and Graphical Causal Models in Psychology
Glymour, C. (2001) · Cited by 279 · see citing works
Glymour, C. (2001) · The MIT Press eBooks · doi:10.7551/mitpress/4638.001.0001 · Cited by 279 · see citing works
How actions create – not just reveal – preferences
Dan Ariely, C., & Norton, M. I. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.10.008 · Cited by 270 · see citing works
NEUROECONOMICS: A CRITICAL RECONSIDERATION
Harrison, G. W. (2008) · Economics and Philosophy · doi:10.1017/s0266267108002009 · Cited by 183 · see citing works
Cacioppo, J. T., Berntson, G. G., Lorig, T. S., Norris, C. J., Rickett, E., & Nusbaum, H. (2003) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.85.4.650 · Cited by 169 · cited 1× · see citing works
“Functional localisation plays an important role in mechanistic research, but every neuroscientist acknowledges that a mere functional localisation does not by itself explain anything (Cacioppo et al. 2003; Henson 2005; Coltheart 2006).”
BackgroundThe Foundations of Positive and Normative Economics: A Handbook
Caplin, A., & Schotter, A. (2008) · OUP Catalogue · Cited by 150 · see citing works
Ross, D. (2008) · Economics and Philosophy · doi:10.1017/s0266267108002095 · Cited by 87 · see citing works
The Illusion of Depth of Understanding in Science
Ylikoski, P. (2017) · University of Pittsburgh Press eBooks · doi:10.2307/j.ctt9qh59s.9 · Cited by 53 · see citing works
Self-citationGraham, K. S., & Gaffan, D. (2005) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/02724990544000059 · Cited by 36 · see citing works
The Illusion of Depth of Understanding in SciencePreprint
Ylikoski, P. (2017) · doi:10.31235/osf.io/qz7sg · Cited by 34 · see citing works
Self-citationTHE IDEA OF CONTRASTIVE EXPLANANDUM
Ylikoski, P. (2007) · Springer eBooks · doi:10.1007/978-1-4020-5581-2_3 · Cited by 31 · see citing works
Self-citationHieke, A., & Leitgeb, H. (2008) · Cited by 2 · see citing works
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Stepin, I., Alonso, J. M., Catala, A., & Pereira-Farina, M. (2021) · IEEE Access · doi:10.1109/access.2021.3051315 · Cited by 376 · see citing works
Evidential Diversity and the Triangulation of Phenomena
Kuorikoski, J., & Marchionni, C. (2016) · Philosophy of Science · doi:10.1086/684960 · Cited by 88 · see citing works
Self-citationGippel, J. (2012) · Australian Journal of Management · doi:10.1177/0312896212461034 · Cited by 37 · see citing works
Concreteness and abstraction in everyday explanation
Bechlivanidis, C., Lagnado, D., Zemla, J. C., & Sloman, S. (2017) · Psychonomic Bulletin & Review · doi:10.3758/s13423-017-1299-3 · Cited by 36 · see citing works
Neurofinance versus the efficient markets hypothesis
Ardalan, K. (2017) · Global Finance Journal · doi:10.1016/j.gfj.2017.10.005 · Cited by 22 · see citing works
Neuroeconomics: more than inspiration, less than revolution
Aydınonat, N. E. (2010) · Journal of Economic Methodology · doi:10.1080/13501781003756444 · Cited by 18 · see citing works
How thin rational choice theory explains choices
Fumagalli, R. (2020) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2020.03.003 · Cited by 16 · see citing works
Neural Findings and Economic Models
Fumagalli, R. (2014) · Philosophy of the Social Sciences · doi:10.1177/0048393114530948 · Cited by 11 · see citing works
Who is afraid of scientific imperialism?
Fumagalli, R. (2017) · Synthese · doi:10.1007/s11229-017-1411-2 · Cited by 10 · see citing works
Are Humans Intuitive Philosophers?
Sloman, S. A., Zemla, J. C., Lagnado, D. A., Bechlivanidis, C., & Hemmatian, B. (2019) · doi:10.1093/oso/9780190860974.003.0012 · Cited by 11 · see citing works
Financial Revolution: From Traditional Finance to Behavioral and Neuro-finance
Rashid, M., Ahmad, R., & Tariq, S. (2022) · South Asian Journal of Social Sciences and Humanities · doi:10.48165/sajssh.2022.3408 · Cited by 9 · see citing works
Fumagalli, R. (2011) · Biology & Philosophy · doi:10.1007/s10539-011-9272-4 · Cited by 9 · see citing works
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Kuorikoski, J., & Marchionni, C. (2024) · Journal of Economic Methodology · doi:10.1080/1350178x.2024.2336048 · Cited by 8 · see citing works
Self-citationBehavioral attitudes toward current economic events: a lesson from neuroeconomics
Ardalan, K. (2018) · Business Economics · doi:10.1057/s11369-018-0089-x · Cited by 8 · see citing works
Neuroeconomics: Hype or Hope? An Answer
Truc, A. (2023) · OEconomia · doi:10.4000/oeconomia.15489 · Cited by 7 · see citing works
For a Few Neurons More: Tractability and Neurally Informed Economic Modelling
Colombo, M. (2014) · The British Journal for the Philosophy of Science · doi:10.1093/bjps/axu013 · Cited by 8 · see citing works
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Fumagalli, R. (2016) · Biology & Philosophy · doi:10.1007/s10539-016-9546-y · Cited by 5 · see citing works
Triangulation across the lab, the scanner and the field: the case of social preferences
Kuorikoski, J., & Marchionni, C. (2016) · European Journal for Philosophy of Science · doi:10.1007/s13194-016-0154-0 · Cited by 3 · see citing works
Self-citationNeurosciences, Neuroeconomics, and Metaphysics
Crespo, R. F. (2015) · Springer eBooks · doi:10.1007/978-3-319-17103-6_4 · Cited by 2 · see citing works
A Coherentist Defense of Economics as an Interdisciplinary Social Science
Cruz‐e‐Silva, V., & Cavalieri, M. (2021) · Journal of Economic Issues · doi:10.1080/00213624.2021.1948278 · Cited by 1 · see citing works
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Campaner, R. (2022) · European studies in philosophy of science · doi:10.1007/978-3-031-05883-7_2
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Virmajoki, V. (2023) · Springer eBooks · doi:10.1007/978-3-031-45929-0_5
Mechanistic Constitution as a Natural Law in Better Best Systems
Harbecke, J. (2025) · Journal for General Philosophy of Science · doi:10.1007/s10838-025-09717-9
- Authors
- Kuorikoski, J., & Ylikoski, P.
- Affiliations
- University of Helsinki (FI)
- University of Tampere (FI)
- Corresponding author
- Kuorikoski, Jaakko
- Venue
- Journal of Economic Methodology
- Publisher
- Informa UK Limited
- Published
- 2010-06
- Volume
- 17
- Issue
- 2
- Pages
- 219-228
- ISSN
- 1350-178X (ISSN-L)
- 1469-9427
- OpenAlex
- W1984802964
- Cited by
- 24
- References
- 31
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 2 · 2020: 1 · 2019: 1 · 2018: 1 · 2017: 3 · 2016: 3 · 2015: 1 · 2014: 2 · 2012: 1
- FWCI
- 8.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Economic Methodology (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic Theory and Institutions
- Keywords
- neuroeconomics, explanatory relevance, causal explanation, psychology of decision making
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