To determine if P110 treatment led to different behavioral outcomes, we used principal component analysis (PCA) as used before (Tanaka et al, 2012), to stratify the mice based on their behaviors. For each mouse, we assembled a vector containing normalized values for each behavior measured and identified the top two principal components describing the variation in mouse behavior; these accounted for 35 and 15% of the variance in the data. When we plotted the 28 mice included in the study on these principal components, we found that the WT mice segregated distinctly from the control‐treated SOD1 G93A mice by silhouette score (Fig 3D), and the P110‐treated mice fell between these two groups. Further analysis revealed that the first principal component (PC1) reflected general mobility of the mice: positive values for ambulatory behaviors and negative values for resting time (Fig 3D). The P110‐treated mutant group showed higher values in PC1 as compared to the control‐treatment mutant group, indicating improved movement and suggesting treatment benefit.