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. 2018 Sep 12;38(37):7952–7968. doi: 10.1523/JNEUROSCI.3327-17.2018

Figure 6.

Figure 6.

Hierarchical Bayesian parameter estimates of the influence of neural response on model parameters. A–C, Trial-by-trial fluctuations in the ERP in SOIs for the value-related ERP from 500 to 650 ms (A) were linked with significantly greater influence on the drift rate v of the taste attribute when choosing for Own self and Similar other (B) and the health attribute when choosing for the Dissimilar other (C), suggesting that this response relates to evidence accumulation in the computational model. D–F, Trial-by-trial fluctuations in the response-locked ERP component (D) differentiated choices for the Similar other to a greater extent than Dissimilar or Own choices, consistent with computational model-fitting of the behavioral barrier parameter (E), and likewise demonstrated a significant influence on the barrier for response (F).