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Table 3. 

Experiment 2: ERP Analysis

ERP Component
Cluster
Contrasts
Hit–CR
Miss–CR
N1 1–4, 11 F(1, 10) = 45.6, p < .0001 F(1, 10) = 1.2, p = .3 
5,6,12 F(1, 10) = 43.9, p < .0001 F(1, 10) = 0.4, p = .5 
7–10 F(1, 10) = 49.3, p < .0001 F(1, 10) = 0.8, p = .4 
N2 1–4, 11 F(1, 10) = 22.4, p = .001 F(1, 10) = 1.8, p = .2 
5,6,12 F(1, 10) = 15.9, p = .003 F(1, 10) = 0.7, p = .4 
7–10 F(1, 10) = 20.6, p = .001 F(1, 10) = 0.5, p = .5 
SP 1,3,11 F(1, 10) = 10.8, p = .01 F(1, 10) = 0.2, p = .7 
2,4 F(1, 10) = 0.3, p = .6 F(1, 10) = 1.1, p = .3 
5,12 F(1, 10) = 10.7, p = .01 F(1, 10) = 0.3, p = .6 
F(1, 10) = 0.1, p = .8 F(1, 10) = 0.04, p = .8 
7–10 F(1, 10) = 1.2, p = .3 F(1, 10) = 1.5, p = .2 
ERP Component
Cluster
Contrasts
Hit–CR
Miss–CR
N1 1–4, 11 F(1, 10) = 45.6, p < .0001 F(1, 10) = 1.2, p = .3 
5,6,12 F(1, 10) = 43.9, p < .0001 F(1, 10) = 0.4, p = .5 
7–10 F(1, 10) = 49.3, p < .0001 F(1, 10) = 0.8, p = .4 
N2 1–4, 11 F(1, 10) = 22.4, p = .001 F(1, 10) = 1.8, p = .2 
5,6,12 F(1, 10) = 15.9, p = .003 F(1, 10) = 0.7, p = .4 
7–10 F(1, 10) = 20.6, p = .001 F(1, 10) = 0.5, p = .5 
SP 1,3,11 F(1, 10) = 10.8, p = .01 F(1, 10) = 0.2, p = .7 
2,4 F(1, 10) = 0.3, p = .6 F(1, 10) = 1.1, p = .3 
5,12 F(1, 10) = 10.7, p = .01 F(1, 10) = 0.3, p = .6 
F(1, 10) = 0.1, p = .8 F(1, 10) = 0.04, p = .8 
7–10 F(1, 10) = 1.2, p = .3 F(1, 10) = 1.5, p = .2 

rm-ANOVA results for N1, N2, and SP components.

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