Figure 4. Optimal P-value threshold for scaling coefficients.

Naturalistic groupings of the brains were generated using scaling coefficients that differed significantly with at most a specified P-value between groups of participants in our cohort. The optimal P-value of the statistical significance was selected from the plots of sensitivity and specificity, and the number of scaling coefficients, for various P-value thresholds in our cohort of 42 healthy children (HC) and 71 children with Tourette's Syndrome (TS). The scaling coefficients were computed for the right and left amygdalae, hippocampi, global pallidus, putamina, caudate nuclei, thalami, and hemisphere surfaces. At each P-value threshold, we applied hierarchical clustering to all coefficients that differed with at most the specified P-value to generate groupings of the brains. These groupings were analyzed using leave-one-out (LOO) cross validation to compute the sensitivity and specificity of our method for classifying an individual as a healthy child or a child with TS. We independently computed sensitivity and specificities for various P-value thresholds and plotted the sensitivity (SE, solid line) and specificity (SP, dashed line) (Left), and the number of coefficients (Right), as a function of P-value thresholds. For a P-value threshold<10⁻⁷, the method classified an individual with both high sensitivity and high specificity. At this P-value threshold, moreover, the number of coefficients was sufficiently reduced, thereby reducing the dimensionality of the feature space. We therefore applied a P-value<10⁻⁷ as a threshold for classifying an individual among various neuropsychiatric illnesses. SE, sensitivity; SP, specificity.