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Table 3. 
Linear Model of Amygdala Pattern Similarity to Trustworthy and Untrustworthy Faces Predicting Neutral Face Bias Scores
 Amygdala ROIInsula ROIFFA ROIFaPrN ROIFaPrN Revised ROIb
βSEtpβSEtpβSEtpβSEtpβSEtp
Intercept −.137 .076 −1.817 .076 −.134 .076 −1.758 .085 −.120 .078 −1.549 .129 −.139 .077 −1.816 .076 −.140 .077 −1.807 .077 
Similaritya .293 .135 2.170 .035 .280 .143 1.962 .056 .227 .153 1.743 .088 .291 .165 1.776 .084 .267 .171 1.559 .126 
R2 .093       .077       .065       .063       .050       
F 4.711       3.851       3.037       3.119       2.432       
AIC 77.877       78.698       75.441       79.408       80.084       
BIC 83.491       84.312       80.926       85.022       85.698       
RMSE .512       .516       .515       .520       .523       
k-Fold R2 .337       .348       .312       .337       .331       
k-Fold RMSE .509       .523       .521       .522       .529       
 Amygdala ROIInsula ROIFFA ROIFaPrN ROIFaPrN Revised ROIb
βSEtpβSEtpβSEtpβSEtpβSEtp
Intercept −.137 .076 −1.817 .076 −.134 .076 −1.758 .085 −.120 .078 −1.549 .129 −.139 .077 −1.816 .076 −.140 .077 −1.807 .077 
Similaritya .293 .135 2.170 .035 .280 .143 1.962 .056 .227 .153 1.743 .088 .291 .165 1.776 .084 .267 .171 1.559 .126 
R2 .093       .077       .065       .063       .050       
F 4.711       3.851       3.037       3.119       2.432       
AIC 77.877       78.698       75.441       79.408       80.084       
BIC 83.491       84.312       80.926       85.022       85.698       
RMSE .512       .516       .515       .520       .523       
k-Fold R2 .337       .348       .312       .337       .331       
k-Fold RMSE .509       .523       .521       .522       .529       

n = 48, except FFA ROI n = 46. AIC = Akaike information criterion, BIC = Bayesian information criterion, RMSE = Root mean square error.

a

Higher values indicate greater pattern similarity between trustworthy and untrustworthy faces.

b

Excludes amygdala and insula voxels from FaPrN ROI.

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