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The first measure was the performance index, which was used to visualize the evolution of the performance as a function of the trial.
For the first level analysis we specified a general linear model in which events were sorted into several regressors as a function of the trial component, the distraction condition, and subsequent memory.
The increase in the correlation coefficient can be seen in Fig. 5B, which plots the r-value as a function of the trial block.
The interaction was also statistically significant (F [24,4290] = 15.3; P < 0.001); again, the functions in Figure 1A show that the rate of performance increase as a function of the trial number (until trial 6) was slower as age increased.
The first-order interaction between pathology group and trial was significant (F [6,1320] = 6.62; P < 0.001); the functions in Figure 1 show that the rate of performance increase as a function of the trial was slower for the AD group.
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A well-known example of automatic TO is sequential effects (SEs), which refer to the adjustments in participants' behavioral performance as a function of the trial-by-trial sequential distribution of the foreperiod between two stimuli.
Modifications were expressed as the sum of the absolute value of LTP and LTD as a function of the training trials.
The percentage of rank 2 solutions is shown in Fig. 14A as a function of the number of experimental trials.
Figure 3 shows the percentage of training (panels A C) and test trials (panels D F) that were judged as rotating in the direction predicted by training as a function of the number of training trials for the three experiments.
These shifts were analysed as a function of the nature and length of the trials that preceded it.
Additionally, we compared the overall percent of correct trials in the test as a function of the training regime.
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