Table 3.

Components of multivariable linear regression models for predicting cortical and subcortical structure volumes, organized by independent variables of interest.

Independent variable	Coefficient	p	Dependent variable	Participant group
GM CBF	−0.010	0.017	Insula volume	HC + SCD (n = 137)
GM CBF	−0.0053	0.017	Left caudate volume	HC + SCD (n = 137)
GM CBF	−0.0053	0.036	Right caudate volume	HC + SCD (n = 137)
Infarct burden*	−0.11	0.002	Left nucleus accumbens volume	SCD w/ SCI (n = 31)
Infarct burden*	−0.085	0.002	Right nucleus accumbens volume	SCD w/ SCI (n = 31)
Infarct burden*	−0.44	0.009	Right thalamus volume	SCD w/ SCI (n = 31)
Infarct burden*	−0.098	0.002	Anterior corpus callosum volume	SCD w/ SCI (n = 31)

Each row represents a separate regression model. Due to space constraints, only significant models are shown. Corrections for multiple comparisons made using the Benjamini–Hochberg method, treating the p-values from each independent variable as its own set for correction purposes. All regressions include age, sex and ICV as additional covariates. GM, gray matter; WM, white matter; CBF, cerebral blood flow. *Log₁₀ of infarct burden.