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. 2022 Jun 23;16:835772. doi: 10.3389/fninf.2022.835772

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Copyright © 2022 Fang, Poskanzer and Anzellotti.

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(s) 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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Comparison between neural network (NN) models and linear regression (LR) models. Statistical t-maps computed across subjects from the voxelwise difference between the average variance explained predicted by three NN models (NN_1layer, NN_5layer, NN_5layer_dense), and the average variance explained predicted by two LR models (L2_LR, PCA_LR) with FFA (top) and PPA (bottom) as predictor ROIs, respectively. The SnPM threshold corrected at p <0.05 FWE is 3.78 using FFA as predictor and is 3.65 using PPA as predictor.