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PNAS Gallistel et al. 10.1073/pnas.0404965101.

Supporting Information

Files in this Data Supplement:

Supporting Figure 12
Supporting Figure 13
Supporting Figure 14
Supporting Figure 15
Supporting Figure 16
Supporting Figure 17
Supporting Figure 18
Supporting Figure 19
Supporting Figure 20
Supporting Figure 21
Supporting Figure 22
Supporting Table 1
Supporting Text
Supporting Data Sets 1–7
Supporting MATLAB Files








Supporting Figure 12

Fig. 12. In this illustration, the algorithm for finding change points is applied to the cumulative record as of Trial 27. (In practice, it is applied iteratively to each successive point in the cumulative record.) In this record, there were no pecks until Trial 20, where pecking began. The slanted dashed line is a straight line drawn between the origin and the cumulative record at end of Trial 27. The cumulative record deviates maximally from this straight line between Trial 19 and 20, so that is the putative change point. The putative change point divides the record up to Trial 27 into two portions: the trials up to and including Trial 19, and the trials from 20 to 27. If the change point is accepted as valid, then the algorithm begins over again, taking Trial 19 as the origin (zero point of the cumulative record) and the pecks on Trial 20 as the first datum (first measurement in the running sum).

 

 

Supporting Figure 13

Fig. 13. Distribution of the interreward intervals (the data in TestData1).

 

 

Supporting Figure 14

Fig. 14. The graph resulting from applying cp_wrapper to TestData1 with a logit (decision criterion) of 2. The top graph is the cumulative record, with the significant change points indicated by the small circles. The bottom graph is the slopes between the change points, that is, the successive rates (of reward), i.e., rewards per minute.

 

 

Supporting Figure 15

Fig. 15. Distribution of the eat latencies, the data in TestData2.

 

 

Supporting Figure 16

Fig. 16. Graphic results from cp_wrapper(’TestData2',1,3,4).

 

 

Supporting Figure 17

Fig. 17. The results of analyzing cumulative correct choices in the + maze TestData3) by using the c 2 test and Crit = 2.

 

 

Supporting Figure 18

Fig. 18. Graphic results from cp_wrapper(’TestData4',1,2,2).

 

 

Supporting Figure 19

Fig. 19. Results from cp_wrapper(’TestData5',1,1,3).

 

 

Supporting Figure 20

Fig. 20. Graphic results from cp_wrapper(’TestData6',1,2,2), By using the K_S test and a decision criterion (logit) of 2, there were no significant change points.

 

 

Supporting Figure 21

Fig. 21. Results from cp_wrapper(’TestData6',1,2,1.3).

 

 

Supporting Figure 22

Fig. 22. Results from cp_wrapper(’TestData6',1,3,2).

 

 

Supporting Data Sets 1–7

Supporting Data Set 1
Supporting Data Set 2
Supporting Data Set 3
Supporting Data Set 4
Supporting Data Set 5
Supporting Data Set 6
Supporting Data Set 7

 

 

Supporting MATLAB Files

binocdf.m
binopdf.m
chi2logit.m
cp_wrapper.m
cpc.m
cpd.m
cpt.m
distchck.m
fishexct.m
ks.m
rrc.m
rrd.m
slopes.m
tcdf.m
trun.m
ttest2.m
xstep.m
ystep.m