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. 2019 Feb 4;9:66. doi: 10.1038/s41398-019-0380-2

Fig. 1. Overview of the methods used.

Fig. 1

Methods are the same as in the previous study. EEG was recorded while 14-month-old infants watched dynamic videos. At 36 months, a clinical assessment and measurements of dimensional ASD traits were performed. Developmental abilities were assessed at both visits. EEG data were cleaned, preprocessed, and cut into 1-s epochs. After Fast Fourier Transformations, the debiased Weighted Phase Lag Index (dbWPLI) was calculated. Connectivity matrices contain connectivity values for each possible connection pair. These were averaged across the frequencies for the 7–8 Hz band. We used the connectivity matrices of each infant to assess network differences between groups with the Network Based Statistics program. Global dbWPLI was calculated by averaging values below the diagonal of the connectivity matrices. These values were used to assess differences on group level. Finally, average connectivity in selected connections only (here displayed in yellow) was used to investigate the correlations between functional connectivity and dimensional traits. MSEL Mullen Scales for Early Learning, ADI-R Autism Diagnostic Interview–Revised, ADOS-2 Autism Diagnostic Observational Schedule–2, NBS Network Based Statistics, dbWPLI debiased Weighted Phase Lag Index