Correction: A unifying Bayesian account of contextual effects in value-based choice

• Francesco Rigoli,
• Christoph Mathys,
• Karl J. Friston,
• Raymond J. Dolan

Correction: A unifying Bayesian account of contextual effects in value-based choice

• Francesco Rigoli,
• Christoph Mathys,
• Karl J. Friston,
• Raymond J. Dolan x

Fig 5 and Fig 6 are incorrect. The authors have provided a corrected version here.

Fig 5.

A Empirical evidence (derived from integrating data from available studies as in ) concerning the difference in probability between choosing option A and option B when a third option K is available (P[A|A,B,K] − P[B|A,B,K]). Here options are characterized by two attributes (price p and quality q). For car A, we assign Rp,A = 1 to price (low scores indicate high price) and Rq,A = 10 to quality. For car B, we assign Rp,B = 10 to price and Rq,B = 1 to quality. The graph considers the choice probability difference between option A and option B as a function of the reward amounts Rq,K (for quality; x axis) and Rp,K (for price; y axis) of a third option K. Green areas indicate values for which no difference is expected based on empirical evidence; orange and blue areas indicates values for which a positive and negative difference is expected, respectively. B: The same analysis is performed with data simulated using BCV (100000 trials are simulated for each condition; μC = 0; ; = 1 for simulations).

https://doi.org/10.1371/journal.pcbi.1007366.g001

Fig 6.

Predictions of BCV about the difference in probability between choosing option A and option B when a third option K is available (P[A|A,B,K] − P[B|A,B,K]). Here options are characterized by two attributes (price p and quality q). For car A, we assign Rp,A = 1 to price (low scores indicate high price) and Rq,A = 10 to quality. For car B, we assign Rp,B = 10 to price and Rq,B = 1 to quality. The graph considers the choice probability difference between option A and option B as a function of the reward amounts Rq,K (for quality; x axis) and Rp,K (for price; y axis) of a third option K (100000 trials are simulated for each condition; = 1 for simulations). Different parameter sets are swn. A: Simulation using μC = −2 and . B: Simulation using μC = 2 and . C: Simulation using μC = 0 and . D: Simulation using μC = 0 and .

https://doi.org/10.1371/journal.pcbi.1007366.g002

Reference

1. 1. Rigoli F, Mathys C, Friston KJ, Dolan RJ (2017) A unifying Bayesian account of contextual effects in value-based choice. PLoS Comput Biol 13(10): e1005769. https://doi.org/10.1371/journal.pcbi.1005769 pmid:28981514