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Rational Attention and Adaptive Coding: A Puzzle and a Solution

Author

Listed:
  • Camillo Padoa-Schioppa
  • Aldo Rustichini
Abstract
Adaptive Coding is the property of the brain to adjust its response to statistical properties of the environment. Its effect is an improved discrimination among signals under the constraints on the dynamic range of its response. It can thus be considered the neural correspondent of Rational Attention, which models how a rational decisionmaker allocates attention among different informative signals. There is strong evidence of existence of widespread adaptive coding. Adaptive coding introduces a dependence of choice from the environment which is not observed in behavior. We discuss potential solutions and propose Hebbian learning as a potentially satisfactory answer.

Suggested Citation

  • Camillo Padoa-Schioppa & Aldo Rustichini, 2014. "Rational Attention and Adaptive Coding: A Puzzle and a Solution," American Economic Review, American Economic Association, vol. 104(5), pages 507-513, May.
    • Handle: RePEc:aea:aecrev:v:104:y:2014:i:5:p:507-13
    Note: DOI: 10.1257/aer.104.5.507
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    Citations

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    Cited by:

    1. Guo, Julie & Tymula, Agnieszka, 2021. "Waterfall illusion in risky choice – exposure to outcome-irrelevant gambles affects subsequent valuation of risky gambles," European Economic Review, Elsevier, vol. 139(C).
    2. Breitmoser, Yves, 2017. "Discrete Choice with Presentation Effects," Rationality and Competition Discussion Paper Series 35, CRC TRR 190 Rationality and Competition.
    3. Breitmoser, Yves & Vorjohann, Pauline, 2022. "Fairness-based Altruism," Center for Mathematical Economics Working Papers 666, Center for Mathematical Economics, Bielefeld University.
    4. Larbi Alaoui & Antonio Penta, 2018. "Cost-benefit analysis in reasoning," Economics Working Papers 1621, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Breitmoser, Yves, 2016. "Stochastic choice, systematic mistakes and preference estimation," MPRA Paper 72779, University Library of Munich, Germany.
    6. Breitmoser, Yves & Vorjohann, Pauline, 2018. "Welfare-Based Altruism," Rationality and Competition Discussion Paper Series 89, CRC TRR 190 Rationality and Competition.
    7. Glimcher, Paul W. & Tymula, Agnieszka A., 2023. "Expected subjective value theory (ESVT): A representation of decision under risk and certainty," Journal of Economic Behavior & Organization, Elsevier, vol. 207(C), pages 110-128.
    8. Joshua B. Miller & Adam Sanjurjo, 2014. "A Cold Shower for the Hot Hand Fallacy," Working Papers 518, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Breitmoser, Yves, 2018. "The Axiomatic Foundation of Logit," Rationality and Competition Discussion Paper Series 78, CRC TRR 190 Rationality and Competition.
    10. Landry, Peter, 2021. "A behavioral economic theory of cue-induced attention- and task-switching with implications for neurodiversity," Journal of Economic Psychology, Elsevier, vol. 86(C).
    11. Yves Breitmoser & Lian Xue & Jiwei Zheng & Daniel John Zizzo, 2023. "Organizational Design and Error Propagation: Theory and Experiment," Discussion Papers Series 666, School of Economics, University of Queensland, Australia.
    12. Aldo Rustichini, 2023. "Economics with a biological foundation," Indian Economic Review, Springer, vol. 58(1), pages 1-40, June.

    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics

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