## 5 Conclusions  
Network connectivity estimation from hdEEG data can be performed using an electrophysiological source imaging workflow that includes signal pre-processing, head model creation and brain activity reconstruction at the cortical level. In this study, we characterized to what extent head model variations associated with electrode positioning and head tissue segmentation influence EEG connectivity patterns. Our results suggest that inaccuracies in tissue segmentation have a stronger impact than those related to the electrode localization. Additionally, we observed that strongly lateralized networks, such as VAN and LN, were substantially less robust than bilateral networks. We hope that the present study may provide important information for researchers planning new EEG studies, supporting their choice of a suitable electrode positioning and head tissue segmentation approach, respectively. We suggest that future studies could perform test-retest analyses, which offer an alternative way to estimate the reliability of EEG connectivity results with respect to different head modeling approaches. Finally, it may be interesting to extend our findings by testing the impact of head modeling on EEG connectivity using other datasets, collected, for instance, in healthy older adults or in neurological patients. **Supplementary Materials:** The following are available online at [[https://www.mdpi.com/article/10.3390/brainsci11060741/s1](https://www.mdpi.com/article/10.3390/brainsci11060741/s1)]([https://www.mdpi.com/article/10.3390/brainsci11060741/s1](https://www.mdpi.com/article/10.3390/brainsci11060741/s1)), Table S1: Definition of the 21 seeds used for analysis; Table S2: Definition of the simulated electrode localization errors due to different positioning techniques; Table S3: Correspondence between the reference connectivity matrices and those obtained when introducing electrode localization errors; Table S4: Comparative analysis of the z-values expressing the correspondence between the reference connectivity matrices and the matrices obtained when introducing errors in the head model; Figure S1: Representation of the head tissues in template space; Figure S2: Comparison of intra- and inter-network connectivity values for each frequency band and network; Figure S3: Estimated marginal means plots for each of the four factors included in the ANOVA test for electrode localization errors; Figure S4: Estimated marginal means plots for each of the three factors included in the ANOVA test for the data processed with different head tissue segmentation methods; Figure S5: Contrasts between intra- and inter-network connectivity, for different headmodels; Figure S6: Scatterplots of intra- and inter-network connectivity differences for different head models, compared to the corresponding values obtained using the reference analysis workflow. Conceptualization, D.M. and G.A.T. ; Methodology, D.M., G.A.T. and J.S. ; Software, G.A.T. and J.S. ; Validation, D.M., G.A.T., J.S. and M.M. ; Formal Analysis, D.M., G.A.T. and J.S. ; Investigation, D.M., G.A.T., J.S. and M.M. ; Resources, D.M. ; Data Curation, G.A.T. and J.S. ; Writing--Original Draft Preparation, G.A.T., J.S. and M.M. ; Writing--Review and Editing, D.M. ; Visualization, G.A.T. and J.S. ; Supervision, D.M. ; Project Administration, D.M. ; Funding Acquisition, D.M. and M.M. All authors have read and agreed to the published version of the manuscript. The study was supported by the KU Leuven Special Research Fund (grant C16/15/070), Research Foundation--Flanders (FWO) (grants GOF76.16 N, G0936.16 N, EOS.30446199 and postdoctoral fellowship 1211820N to M.M.) and Italian Ministry of Health (grant RF-2018-12366899). The computing resources and services used in the study were provided by the VSC (Flemish Supercomputer Center), funded by the FWO and the Flemish Government. The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of ETH Zurich (EC 2013-N-06).