Fig. 1.

Sample specification curve analysis of 64 unique linear regression models with individual well-being scores as the criterion. Model specifications are ordered based on the parameter estimate for the association between individual whole-brain pattern expression of a multivariate neural signature of self-referential processing and well-being scores. Each vertical column corresponds to a single model specification. The regression coefficient for each model specification is plotted in panel A and the variables included in each model are visualized in panel B. Models in which the association between multivariate expression and well-being score is statistically significant at p <  .05 are highlighted in red. Error bars represent 95 % confidence intervals. Control variables included depression scores and mean reaction time. Outliers were defined as being more than 2.5 standard deviations from the mean for each variable. pgACC = perigenual anterior cingulate cortex, vmPFC = ventromedial prefrontal cortex, VS = ventral striatum. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).