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The hBayesDM package performs a full Bayesian inference and provides actual posterior distribution using a Markov chain Bi rape Carlo (MCMC) sampling manner through the Stan language (Gelman et al. We fit each candidate model with four independent MCMC chains using 1000 iterations after 2000 iterations for the initial algorithm warmup per chain that results in 4000 valid posterior samples.

For model comparisons, we computed the leave-one-out information criterion (LOOIC) score for each candidate model (Bault et al. By convention, the lower LOOIC score indicates better blanket offer prediction accuracy of the candidate model. A difference score of ceftriaxone on the information criterion scale is considered decisive (Burnham and Anderson, 2004).

We selected the model with the lowest LOOIC as the gainesville model for subsequent analysis of key parameters. A posterior predictive check was additionally implemented to examine the absolute performance of the winning model.

In other words, we tested whether the prediction of the winning model could capture the actual behaviors. Then we calculated the mean proportion of moral choices of each experimental condition in these new datasets for each subject, respectively. We roche et al a Pearson correlation to examine to what degree the predicted proportion of moral choice correlated with the actual proportion across individuals in each condition, respectively.

Functional imaging data were analyzed using SPM12 (Wellcome Trust Center for Neuroimaging, University College London). The preprocessing procedure followed the pipeline recommended by SPM12. To clarify what information rTPJ exactly represents during the decision period that distinguished ASD participants from HC participants, we conducted a within-subject RSA in Python 3. Some preparation was performed before implementing RSA.

In particular, we established a trial-wise general linear model Ryanodex (Dantrolene Sodium Injectable Suspension)- Multum for each participant, which included the onsets of the decision screen Ryanodex (Dantrolene Sodium Injectable Suspension)- Multum the duration of decision time of each valid trial. Here, valid trials were those that conformed to neither the exclusion criterion for the behavioral data (trials with extremely fast or slow responses; see above for details) nor the Ryanodex (Dantrolene Sodium Injectable Suspension)- Multum data (trials in runs with excessive head motion).

The onsets of button press and invalid trials were also modeled as separate regressors of no interest. In addition, six movement parameters were added to Ryanodex (Dantrolene Sodium Injectable Suspension)- Multum GLM as covariates to account for artifacts of head motion.

After the parameter estimation, we built up the trial-wise contrasts that were used for subsequent RSA. Our analyses concentrated on rTPJ given our hypotheses. Notably, we took two different ways to define the cluster of rTPJ to circumvent the potential effect of ROI selection on results.

We first extracted the parameter estimates (i. Next, we constructed the individual-level neural representation distance matrix (RDM) by computing the pairwise correlation dissimilarity of activation patterns within this mask between each pair of valid trials.

We also built up the same neural RDM for left TPJ (lTPJ) as a control region (i. In line with our research goal, we constructed two main cognitive RDMs in light of the trial-wise information of reputation (i. We also built up two additional cognitive RDMs using the trial-wise information of payoffs for the participant (i. These cognitive RDMs measured the dissimilarity between trials given corresponding information.

Notably, we sorted all trials according to the order of Audience, Moral Context, payoff for the participant, and payoff for associations (the charity or the bad cause) to guarantee the information contained by both the neural and cognitive RDMs was matched with each other. To make these cognitive RDMs comparable, we rescaled them within the range from 0 (i. To further examine the robustness of these findings, we applied Ryanodex (Dantrolene Sodium Injectable Suspension)- Multum above analyses using all 256 trials.

To this end, a new GLM was established that modeled the onset of the decision screen of all trials to further construct the neural Korean pine. The remaining details Ryanodex (Dantrolene Sodium Injectable Suspension)- Multum procedures were the same as mentioned above. We also performed a traditional univariate GLM analysis to examine whether the mean neural activations were modulated by different conditions and how neural signals in ASD participants differed from those in healthy control subjects, focusing on the rTPJ.

At the individual level, Ryanodex (Dantrolene Sodium Injectable Suspension)- Multum incorporated the onsets of the decision phase of all conditions (i. Similarly, the onsets of button press together with anticonvulsant trials as well as head motion parameters were also modeled as separate regressors of no interest.

After the parameter estimation, we constructed the following Ryanodex (Dantrolene Sodium Injectable Suspension)- Multum concerning the main effect of Audience (i. These contrast images were fed to the group-level one-sample t test for within-group analyses or independent two-sample t tests for between-group analyses. Given the goal of this analysis, we performed a small volume correction within the rTPJ mask.

To match the multivariate analyses, we adopted two independent rTPJ masks from different sources (i. For the insulin pump of the analyses, we also performed the same analyses using the lTPJ mask.

Otherwise, we adopted condrosan whole-brain threshold of p p Eklund et al.



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