Table 1.

Model performance for the MKL and SVM models distinguishing between ‘faces’ (F) and ‘houses’ (H), for each atlas (in %, with p-value)

Model	Atlas	Balanced accuracy (%)	True positives (Faces)/ Total positives	True negatives (Houses)/ Total negatives
MKL	AAL	98.15 (p = 0.01)	107/108	105/108
	Brodmann	96.30 (p = 0.01)	104/108	104/108
	HCP	100.0 (p = 0.01)	108/108	108/108
SVM	AAL	93.06 (p = 0.01)	101/108	100/108
	Brodmann	91.20 (p = 0.01)	96/108	101/108
	HCP	94.91 (p = 0.01)	100/108	105/108

True positives (resp. negatives) represent the class accuracy for faces (resp. houses) samples classified correctly as faces (resp. houses). Note that the difference between the SVM models is only the mask used to select the voxels, which is based on the atlas