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. Author manuscript; available in PMC: 2018 Aug 1.
Published in final edited form as: Pain. 2017 Aug;158(8):1586–1598. doi: 10.1097/j.pain.0000000000000961

Table 2.

Regional brain volumes variance explained by treatment (Vehicle vs Sucrose) in CPCA modeling.

Brain Structure PC1 PC2
Loading P-value Loading P-value

Cerebrum / Cerebral cortex 0.279 0.0021 0.820 0.0000
 Amygdalo piriform transition area 0.255 0.0004 0.685 0.0000
 Caudo medial entorhinal cortex 0.297 0.0070 0.665 0.0000
 Postero lateral cortical amygdaloid area 0.312 0.0013 0.554 0.0000
 Postero medial cortical amygdaloid area 0.225 0.0017 0.748 0.0000
 Rostral amygdalo piriform area 0.271 0.0092 0.525 0.0000
 Ventral tenia tecta 0.191 0.0292 0.399 0.0000
Cerebrum / Cerebral nuclei
 Bed nucleus of stria terminalis 0.279 0.0021 0.820 0.0000
Brainstem
 Medulla 0.203 0.0094 0.351 0.0002
 Superior olivary complex 0.061 0.4517 0.370 0.0001
Cerebellum
 Lobules 4–5: culmen (ventral and dorsal) 0.329 0.0004 0.536 0.0000
 Lobule 7: tuber (or folium) 0.185 0.0129 0.418 0.0000
 Lobule 8: pyramis 0.190 0.0233 0.439 0.0000
 Copula pyramis lobule 8 0.271 0.0020 0.427 0.0000
 Trunk of lobules 6–8 white matter 0.265 0.0009 0.391 0.0000
 Lobule 8 white matter 0.110 0.1854 0.394 0.0001
 Lobule 9: uvula 0.266 0.0006 0.507 0.0000
 Lobule 9 white matter 0.201 0.0106 0.484 0.0000
 Lobule 10: nodulus 0.260 0.0015 0.433 0.0000
 Flocculus FL 0.156 0.0549 0.509 0.0000
 Flocculus white matter 0.099 0.2381 0.397 0.0000
 Paraflocculus PFL 0.250 0.0019 0.329 0.0002
Ventricular system
 Third ventricle 0.410 0.0010 0.483 0.0001

CPCA factor loadings for analysis of treatment effect on regional brain volumes. Component loadings for PC1 and PC2 and their P-values for the 22 brain regions that passed the Bonferroni cut-off (P < 0.013) are listed. Treatment (represented in PC2) loaded uniquely on 22 brain regions, reflecting that mice exposed to Sucrose have significantly smaller volumes in these specific brain areas compared to Vehicle (P < 0.013), n per group 52–57.

CPCA, constrained principal component analysis; PC, principal component.