Anticipation phase > Baseline

Contributed by taehol on July 19, 2019

Collection: Mothers Driving Game: Self Driving and Observing Child Driving

Description: We created regions of interest (ROIs) by performing an additional standard two-stage mixed effects whole-brain univariate analysis using the observation run in which the anticipation regressor was modeled individually with temporal derivate regressor and nuisance regressors, and individual level anticipation contrasts were inputted into group-level analysis (FLAME 1 + 2; Z > 2.3; one-tailed P = .05). We selected all voxels from [anticipation > baseline] contrast (k, a number of voxels, = 9363), and used them as our anticipation network ROI mask for the pattern extraction. For this analysis, we applied 6-mm smoothing, ICA denoising using an automated signal classification toolbox (Tohka et al., 2008), and spatial normalization for 2-mm MNI template using ANTs (Avants et al., 2011) for individual data.

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