Table 1. Summary of support vector machine classification model.

Results are based on single- and multi-cluster functional connectivity mean z-score values in a training cohort of 11 cKO and 11 control mice, and evaluated in an independent testing cohort of 7 cKO and 7 control mice. AUC: receiver operating characteristic area under the curve representing sensitivity and specificity in the training cohort; Prediction: 10-fold cross validation classification accuracy in testing cohort. Common slashes separate adjacent regions that comprise a common single-cluster combination of voxels. Individual clusters within multi-cluster combinations are separated by addition signs (+).

Functional connectivity cluster(s)	AUC	Prediction
1. Somatosensory cortex	0.86	71.4
2. Sensory-motor thalamus	0.91	78.6
3. Superior colliculus	0.91	71.4
4. Pons	0.95	78.6
5. Vermis/cerebellar nuclei	0.91	71.4
6. Anisiform lobule	0.91	92.9
7. Thalamus	0.91	85.7
8. Somatosensory cortex + posterior parietal assoc.	0.83	64.3
9. Somatosensory cortex + sensory-motor thalamus	0.82	78.6
10. Somatosensory cortex + vermis/cerebellar nuclei	0.82	92.9
11. Somatosensory cortex + sensory-motor thalamus + vermis + vermis/cerebellar nuclei + anisiform lobule	0.75	92.9
12. Somatosensory cortex + thalamus + superior colliculus + anisiform lobule	0.75	100
13. Somatosensory cortex + sensory-motor thalamus + superior colliculus + anisiform lobule + vermis	0.73	100
14. Somatosensory cortex + hypothalamus/midbrain + geniculate group + anisiform lobule + vermis	0.74	100