Machine learning approach for Migraine Aura Complexity Score prediction based on magnetic resonance imaging data

Table 2 Features with significant correlation with average MACS

Feature	Correlation	p-value
Left parahippocampal gyrus mean Gaussian curvature	-0.4763	0.0019
Left transverse temporal gyrus mean Gaussian curvature	0.4748	0.0020
Left transverse temporal gyrus thickness	0.4693	0.0023
Left pars opercularis thickness	0.4674	0.0024
Left lingual gyrus surface area	-0.4191	0.0071
Right transverse temporal gyrus mean Gaussian curvature	0.4072	0.0091
Left caudal middle frontal gyrus surface area	-0.3964	0.0113
Left entorhinal gyrus volume	-0.3737	0.0175
Right entorhinal gyrus volume	-0.3736	0.0176
Right lingual gyrus surface area	-0.3711	0.0184
Left precuneus gyrus surface area	-0.3572	0.0237
Left pars opercularis surface area	-0.3545	0.0248
Right caudal middle frontal gyrus surface area	-0.3510	0.0264
Right transverse temporal gyrus thickness	0.3480	0.0278
Left caudal middle frontal gyrus volume	-0.3461	0.0287
Left isthmus cingulate surface area	-0.3367	0.0336
Left pericalcarine thickness	0.3286	0.0384
Left caudal anterior cingulate mean Gaussian curvature	0.3284	0.0386
Right entorhinal gyrus surface area	-0.3276	0.0391
Right pericalcarine mean Gaussian curvature	-0.3214	0.0431
Left medial orbitofrontal gyrus folding index	-0.3208	0.0436
Left pars triangularis thickness	0.3186	0.0451
Right caudal middle frontal gyrus folding index	-0.3175	0.0459
Right paracentral gyrus mean Gaussian curvature	0.3167	0.0465
Left lingual gyrus volume	-0.3159	0.0470
Right lingual gyrus volume	-0.3141	0.0484

ISSN: 1129-2377