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Divisive normalization does influence decisions with multiple alternatives

Nature Human Behaviour volume 4, pages 1118–1120 (2020)Cite this article

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Matters Arising to this article was published on 14 September 2020

The Original Article was published on 03 February 2020

arising from S. Gluth et al. Nature Human Behaviour https://doi.org/10.1038/s41562-020-0822-0 (2020)

Divisive normalization, an algorithm prominent in sensory processing and viewed as a canonical neural computation1, has recently been proposed to play a similarly important role in decision-making, capturing aspects of both neural value coding and choice behaviour2,3,4,5,6,7,8,9,10,11,12,13. In a previous study, divisive normalization was proposed to explain context-dependent independence from irrelevant alternatives (IIA) violations, where the relative preference between two given alternatives depends on the value of a third (distracter) alternative14; however, Gluth et al.15 conclude in a replication study that there is no effect of distracter value on choice behaviour in their dataset, instead finding an effect on reaction times. Here, we reanalyse the replication dataset, graciously made available by the authors, using econometric techniques specifically designed to test for the presence of divisive normalization in multi-alternative choice datasets; while we observe some differences between their data and the dataset originally reported by Louie et al.14, overall we find compelling evidence for a divisive normalization effect in choice in their dataset. This discrepancy arises primarily from unnecessarily restrictive assumptions used in previous analyses14,15, emphasizing the importance of deriving the analysis directly from the choice theory itself.

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Fig. 1: Best-performing model fits of the P1/P2 ratio as V3 is varied.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Author information

Authors and Affiliations

  1. Rotman School of Management, University of Toronto, Toronto, Ontario, Canada

    Ryan Webb

  2. Department of Economics, University of Toronto, Toronto, Ontario, Canada

    Ryan Webb

  3. Center for Neural Science, New York University, New York, NY, USA

    Paul W. Glimcher & Kenway Louie

  4. Neuroscience Institute, New York University School of Medicine, New York, NY, USA

    Paul W. Glimcher & Kenway Louie

Authors
  1. Ryan Webb
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  2. Paul W. Glimcher
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  3. Kenway Louie
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Contributions

R.W. and K.L. analysed the data. R.W., P.W.G. and K.L. wrote the paper.

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Correspondence to Kenway Louie.

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Webb, R., Glimcher, P.W. & Louie, K. Divisive normalization does influence decisions with multiple alternatives. Nat Hum Behav 4, 1118–1120 (2020). https://doi.org/10.1038/s41562-020-00941-5

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