Analysis of 
REGRESSION, REGRESSING
In this section, we present the analysis results of the tDCS study using the density regression Model (1) with different transformations (Regressing on the density after applying the log‐density quantile transform yielded the highest number of significant signals, which reaches its maximum around the 85th percentile. This potentially indicates that stimulation has a consistent tail effect, which is more likely to be aligned by quantile, rather than absolute value. Since the estimated coefficient function is significantly non‐zero only in the positive tail this suggests that the tDCS group had higher connection densities in the tail than the sham group. That is, connectivity among the most connected regions was higher in the tDCS group.A likelihood ratio test was performed to compare logistic regression with only baseline variables and our model including both the baseline variables and the log density quantile term. The resulting We also studied the effect of the estimated function on behavior change. We found that the variable 