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. 2018 Jun 19;12:355. doi: 10.3389/fnins.2018.00355

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Copyright © 2018 Habermann, Weusmann, Stein and Koenig.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Results of t-mapping. Left: the ERP mean maps for the expected sentence endings are displayed for day 1 and 2. The resulting t-map is also shown. Day 1 was subtracted from day 2 to parallel the temporal sequence of the conditions, and thus the learning effect. The dialog window also provides further information, including information on the p-value of the TANOVA, and a table with the t-values for each channel. Right: The ERP maps of day 1 and 2, and the corresponding t-map, are shown for the unexpected sentence endings. The t-map for unexpected sentence endings is much flatter than that for the expected sentence endings, and the TANOVA is not significant.