3 63 Looking into troubled waters: Childhood emotional maltreatment modulates neural responses to prolonged gazing into one’s own, but not others’, eyes Statistical analyses Mood and gaze responses were analyzed in R (R Core Team (2013), version 3.6.1) with the following packages: Lme4 for mixed model analysis, psych for descriptive statistics and ggplot2 for figures (Bates et al., 2012; Revelle, 2012; Wickham et al., 2016). Questions that were not answered within 8 s were reported as missing (n = 3/632, 0.5%) and were excluded from further analyses. Significance for analyses on mood and gaze responses was set at p <.05 (two-tailed) and Cohen’s d effect sizes were calculated for significant effects. Eye gaze acquisitions Eye movements were recorded with a tower mounted monocular EyeLink 1000 Hz MRIcompatible eye tracker (SR Research Ltd., Mississauga, Ontario, Canada), placed inside the scanner bore. We used a customized MATLAB (MathWorks, Inc., Natick, MA, version 9.5) script to preprocess raw eye movement data to calculate information on gaze position and duration. Using an established algorithm for face and facial feature detection (Viola & Jones, 2001) we created rectangular areas of interest (AOIs) around the left and right eye of the targets for all videos that were combined into a single AOI of the eye region for further analyses. The primary gaze measure was the percentage of dwell time within the eye region per video relative to the total video duration, in which dwell time is defined as the total amount of time spent looking within an AOI. Collection of gaze data of 31 participants was unsuccessful due to technical problems or a failed calibration procedure. Nine trials of four participants were excluded due to >30% missing gaze data per trial. This resulted in gaze data of 48 (out of 79) participants, including 375 trials (out of 384; 2.3% missing). fMRI Data Acquisition and analyses MR images were acquired using a Philips 3.0T Achieva MRI scanner equipped with a SENSE-32 channel head coil. For the eye contact task, T2*-weighted echo planar imaging (EPI) was used and a structural 3D T1 scan was acquired (see Supplement S3.4 for details on scan parameters). MRI data were preprocessed and analyzed using SPM12 (Wellcome Trust Centre for Neuroimaging, University College London). Functional MR images were slice-time corrected, corrected for field-strength inhomogeneities using b0 field maps, unwarped and realigned, coregistered to subject-specific structural images, normalized to MNI space using the DARTEL toolbox (Ashburner, 2007), and smoothed using an 8-mm full width half maximum isotropic Gaussian kernel. Raw and preprocessed data were checked for quality, registration, and movement. Average head movement did not exceed 1 voxel/3mm for any of the participants (M = 0.09 mm, SD = 0.05 mm, range: 0.002–2.76 mm). Furthermore, we corrected for serial autocorrelations using a first order autoregressive model (AR(1)). We removed low-frequency signals using a high-pass filter (cutoff = 128 s) and included nuisance covariates to remove effects of run.
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