## Similar protocols

## Protocol publication

[…] For each condition, we first determined the response proportion given for one of two choices (e.g., how many times does the subject respond “surprised”) at each test level for each subject. Then, we fit the data of the response proportion based on the maximum likelihood fitting procedure (Meeker and Escobar, ) using a logistic function formula as follows:
F(x=α;α,β)=11+exp(−β(x−α))Where x is the morphing strength, F(x) is the probability of response, parameter α corresponds to the point of subjective point [PSE, F(x = α; α, β) = 0.5], and parameter β determines the slope of psychometric function. From these fits, the aftereffect magnitude was quantified as the difference (in morphing strength) between each subject's PSE adapted after one expression in a pair (e.g., happy expression) and that after the other expression (i.e., angry expression).All statistical analyses were run on **SPSS** 19.0 software, and significance levels for all tests were set at p < 0.05. As the Kolmogorov-Smirnov normality test shows that there were no data violating the assumption of normality, we performed a three-way repeated measures ANOVA with the PSE difference of each subject as the dependent variable, facial identity (2 levels, same or different between adaptor and tests), expression configuration (2 levels, same or different between adaptor and tests), and expression type (2 levels, happy-angry expression pair or disgusted-surprise expression pair) as within-subject factors. Significant main effects and interactions were followed up with simple effect analyses, respectively. Paired samples t-tests were run on each condition to determine whether that condition generated a significant aftereffect, with the PSE adapted after one expression in a pair (e.g., happy expression) and that after the other expression (i.e., angry expression) for the same subject as paired variables. Finally, the post-hoc power analyses was performed for Three-way repeated measures ANOVA using SPSS 19.0 and for paired samples t-tests using **G***Power 3.1. […]

## Pipeline specifications

Software tools | SPSS, G*Power |
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Application | Miscellaneous |