In this study, we examined the performance of cross-tests using difficult and easy conditions in both familiar and unfamiliar tasks. We found that the accuracy of predictions remained consistent regardless of whether easy data were classified by a difficult model or difficult data were predicted by an easy model. This suggests that there are common patterns between difficult and easy tasks, and that there is some level of similarity in neural activities. However, we did observe that the offset of above-chance level was more pronounced for familiar tasks than for unfamiliar tasks, indicating that the latencies of each stage may differ. Specifically, we found that in the Fsp condition, the priming effect appears earlier than in the Facc condition. This was also observed in the performance of Facc data classified by the Fsp model, where the above-chance accuracies were tilted to the right side of the diagonal. While the nature of the pattern in unfamiliar conditions was also present, it was less prominent.

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