We regret to inform you about a calculation error we recently detected in the above published article. We re-analyzed the data after discovering this error to determine the impact it had on the results. This error did not affect the main interpretation of the study but it had an impact in the specific network metrics that showed sensitivity to group differences. With the present corrigendum we propose corrections for the result sections 3.2 and 3.3 and removal of supplementary material. The specific error is related to one of the latest steps of the data analysis, in which each EEG segment per participant is exported as an ASCII file to be further analyzed in Brainwave software (http://home.kpn.nl/stam7883/brainwave.html; by C.J. Stam). In Brainwave, functional connectivity and graph network metrics are computed for each of those segments and then averaged across segments for each participant. The ASCII files were exported including a header with the electrode labels and this was not taken into account when selecting the analysis options in Brainwave (the option asks to specify the number of header lines to be ignored and there is a specific warning about this in the software's manual). This resulted in erroneous reading of the initial lines of each data segment. The following report describes the updated results after re-analysis. Comparably to the published article, the main effects are localized in the Theta band and indicate lower network integration in dyslexics compared to controls. Similar to the published report, the group effect in Leaf is significant (at p < 0.05). However, after re-analyzing the data two additional metrics showed significant differences between the groups at p < 0.05, namely Degree and Kappa. The effect in Diameter from our previous report is not significant in the current re-analysis. The interpretation of these metrics is described in the following report. The group effects suggest higher values for those metrics, associated with network integration, in controls vs dyslexic readers. These effects did not reach significance levels in the control analyses presented as supplementary material. The following report concludes with a paragraph in which the significance of these new findings is highlighted. In view of the current report, we consider that the main interpretation of this study remains valid and interesting for the journal's readers. Thus we would be inclined to present a corrigendum note with the corrected report and table, but we entrust the ultimate decision to the editor. On behalf of all coauthors, Dr. Gorka Fraga González The following report contains the corrected text and results. Results: The inspection of individual peak frequencies in the spectra averaged across parietal-occipital sites indicated that for the majority of participants the peak frequency fell within the low alpha (8–10 Hz) and high alpha (10–13 Hz) range (see Section 2.5). We discarded data from children with a peak frequency equal or lower than 8 Hz as this might bias subsequent analysis in the lower frequency bands. A total of 12 subjects were excluded; 8 dyslexics (N = 26) and 4 controls (N = 15). Spectral power and functional connectivity: The power spectra averaged across all electrodes for each group are shown in Fig. 3. Controls and dyslexics both showed prominent peak frequencies in the alpha band, which did not differ between groups. The mixed model ANOVAs performed on the power values in each frequency band revealed no significant differences (in the total average or regional sub-averages) between groups. The analysis of connectivity strength, i.e., PLI, revealed a trend in the Delta band for higher PLI values in dyslexics compared to typical readers, F (1, 59) = 3.67, p =.063, η2 = 0.09. There were no other significant group differences in PLI for any of the other frequency bands, ps >.144. MST analysis: MST analysis yielded significant between group effects in the theta band (see Table 1). Leaf fraction, reflecting the integration of information within the network, was significantly lower in dyslexics relative to typical readers, F (1, 39) = 5.32, p =.027, η2 = 0.12. The group effect on degree, representing the connections that each node has on average with the rest of the network, was significant also, F (1, 39) = 5.62, p =.023, η2 = 0.13 indicating lower degree in dyslexics relative to controls. In addition, there was a significant group effect on kappa, relating to degree diversity within the network, F (1, 39) = 5.91, p =.020, η2 = 0.13, suggesting lower kappa in dyslexics compared to controls. Kappa is specially high in scale-free network models which are characterized by a few nodes (hubs) with an exceptionally high degree compared to the majority of all other nodes in the network (Stam and van Straaten, 2012). Collectively these results indicate a less integrated network organization in dyslexic children compared to controls. Group effects in all other graph measures and frequency bands were not significant, ps >.093. Significance: Graph metrics relate to the intrinsic organization of functional brain networks. The current findings point to a less efficient network configuration in dyslexics relative to a more proficient configuration in the control group. MST metrics could help characterizing the heterogeneity within dyslexia, as different underlying deficits may result in similar reading impairments. This study provides additional insights on the cognitive deficits underlying dyslexia and, thus, may advance our knowledge on reading development. Our findings add to the growing body literature suggesting compromised networks rather than specific dysfunctional brain regions in dyslexia.