TABLE 7.

Multiple linear regression model with neuroimaging features explaining migraine frequency, after controlling for age, BMI, and disease duration.

Model	Predictors	β	SE	T score	p-Value	VIF	R 2	D-W value
1	Age	−0.487	0.742	−0.656	0.516	1.495	0.105	0.763
	BMI	1.375	1.560	0.882	0.384	1.447
	Duration	0.342	0.226	1.513	0.140	1.196
2	Age	−0.078	0.506	−0.155	0.878	1.520	0.617	2.067
	BMI	1.038	1.061	0.978	0.336	1.465
	Duration	0.114	0.163	0.702	0.488	1.361
	ROI 6 to C1	1.659	0.404	4.109	<0.001**	1.053
	ROI 1	−2.587	0.654	−3.953	<0.001**	1.177
3	Age	−0.496	0.458	−1.084	0.288	1.641	0.738	1.856
	BMI	0.813	0.928	0.876	0.389	1.477
	Duration	0.115	0.145	0.790	0.436	1.420
	ROI 6 to C1	1.253	0.389	3.217	0.003**	1.290
	ROI 6 to C2	−0.505	0.375	−1.347	0.189	2.072
	ROI 1	−1.571	0.765	−2.054	0.049*	2.118
	ROI 4	−0.991	0.596	−1.662	0.108	1.644
	ROI 6	−1.070	0.621	−1.722	0.096	1.409

*p < 0.05; **p < 0.01; n = 36. β, parameter estimate; SE, standard error; VIF, Variance Inflation Factor; D-W value, Durbin-Watson value; BMI, body mass index; ROI 6 to C1, the rsFC of left SPG to left MOG; ROI 6 to C2, the rsFC of left SPG to left AG; ROI 1, right supramarginal gyrus; ROI 4, left middle occipital gyrus; ROI 6, left superior parietal gyrus.