Table 2 Open in new tab Accuracy and...

Inference method	Accuracy %	Accuracy weighted %	Sensitivity %	Specificity %	Misinference error %
Single source graded
LSC (Fig. 4A)	29	5	100	27	91
LSM (Fig. 4B) LSM_vc	46 62	8 13	100 100	45 61	87 83
MAPP (Fig. 4C)	96	94	100	95	2
MSA (Fig. 4D)	95	89	100	95	7
Double source graded synergistic
LSC	19	19	100	15	89
LSM	33	33	100	30	87
MAPP	53	53	100	50	8
MSA	59	59	100	52	18
Double source graded redundant
LSC	19	19	100	15	89
LSM	33	33	100	30	87
MAPP	52	52	100	50	9
MSA	64	64	100	62	19
Double source graded mutual inhibition
LSC	23	23	99	20	89
LSM	45	45	89	43	89
MAPP	79	79	68	79	17
MSA	94	93	85	94	21

Inference method	Accuracy %	Accuracy weighted %	Sensitivity %	Specificity %	Misinference error %
Single source graded
LSC (Fig. 4A)	29	5	100	27	91
LSM (Fig. 4B) LSM_vc	46 62	8 13	100 100	45 61	87 83
MAPP (Fig. 4C)	96	94	100	95	2
MSA (Fig. 4D)	95	89	100	95	7
Double source graded synergistic
LSC	19	19	100	15	89
LSM	33	33	100	30	87
MAPP	53	53	100	50	8
MSA	59	59	100	52	18
Double source graded redundant
LSC	19	19	100	15	89
LSM	33	33	100	30	87
MAPP	52	52	100	50	9
MSA	64	64	100	62	19
Double source graded mutual inhibition
LSC	23	23	99	20	89
LSM	45	45	89	43	89
MAPP	79	79	68	79	17
MSA	94	93	85	94	21

Table 2

Accuracy and misinference errors of uni- and multivariate evaluations of graded ground-truth models of brain function of single source region and double source regions

Inference method	Accuracy %	Accuracy weighted %	Sensitivity %	Specificity %	Misinference error %
Single source graded
LSC (Fig. 4A)	29	5	100	27	91
LSM (Fig. 4B) LSM_vc	46 62	8 13	100 100	45 61	87 83
MAPP (Fig. 4C)	96	94	100	95	2
MSA (Fig. 4D)	95	89	100	95	7
Double source graded synergistic
LSC	19	19	100	15	89
LSM	33	33	100	30	87
MAPP	53	53	100	50	8
MSA	59	59	100	52	18
Double source graded redundant
LSC	19	19	100	15	89
LSM	33	33	100	30	87
MAPP	52	52	100	50	9
MSA	64	64	100	62	19
Double source graded mutual inhibition
LSC	23	23	99	20	89
LSM	45	45	89	43	89
MAPP	79	79	68	79	17
MSA	94	93	85	94	21

Inference method	Accuracy %	Accuracy weighted %	Sensitivity %	Specificity %	Misinference error %
Single source graded
LSC (Fig. 4A)	29	5	100	27	91
LSM (Fig. 4B) LSM_vc	46 62	8 13	100 100	45 61	87 83
MAPP (Fig. 4C)	96	94	100	95	2
MSA (Fig. 4D)	95	89	100	95	7
Double source graded synergistic
LSC	19	19	100	15	89
LSM	33	33	100	30	87
MAPP	53	53	100	50	8
MSA	59	59	100	52	18
Double source graded redundant
LSC	19	19	100	15	89
LSM	33	33	100	30	87
MAPP	52	52	100	50	9
MSA	64	64	100	62	19
Double source graded mutual inhibition
LSC	23	23	99	20	89
LSM	45	45	89	43	89
MAPP	79	79	68	79	17
MSA	94	93	85	94	21

LSM_vc: LSM volume corrected; TP: true positive; TN: true negative; FP: false positive; FN: false negative. Accuracy = (TP + TN)/(TP + TN + FP + FN); Accuracy_weighted = (TP*(1-var(diag))+TN*(1-sum(off_diag)))/(TP + TN + FP + FN). Sensitivity = TP/(TP + FN); Specificity = TN/(TN + FP); Mis-inference error = sum of all inferred regional contributions beyond the ones of the target/s. All the quantities are computed on the normalized significant values in the matrices (figures instead show all the values in the matrices, without excluding the nonsignificant values). For all simulations, we used a regression tree predictor (default parameters). For all simulations, we considered all the values for the regions not expected to be found by the method (FP and TN).

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