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. Author manuscript; available in PMC: 2013 Mar 1.
Published in final edited form as: Brain Cogn. 2013 Jan 9;81(2):283–293. doi: 10.1016/j.bandc.2012.11.006

Table 3. Akaike Weights for Each Model.

Freq. Orient. CJ A CJ B GLC Opt. Random
Rule-Based Task
Stimulus Absent
0ms Delay .36 .00 .04 .14 .11 .22 .12
500ms Delay .24 .00 .06 .18 .11 .25 .16
1000ms Delay .30 .00 .01 .17 .16 .19 .17
Stimulus Present
0ms Delay .33 .00 .03 .19 .09 .29 .07
500ms Delay .40 .00 .06 .16 .12 .20 .05
1000ms Delay .41 .00 .04 .17 .13 .25 .00
Information-Integration Task
Stimulus Absent
0ms Delay .08 .05 .19 .18 .13 .26 .10
500ms Delay .03 .00 .13 .04 .40 .37 .02
1000ms Delay .18 .04 .08 .26 .24 .18 .01
Stimulus Present
0ms Delay .09 .00 .11 .20 .28 .05 .25
500ms Delay .07 .06 .13 .14 .22 .14 .25
1000ms Delay .07 .00 .08 .24 .27 .25 .09

Note: Akaike weights for Frequency (Freq.), Orientation (Orient.), and Conjunctive Rule models (CJA and CJB), and for the Information-Integration models, or the General Linear Classifier model (II), the Optimal model for each task (Opt.) and the Random Responder model (Random).