No relationship between frontal alpha asymmetry and depressive disorders in a multiverse analysis of five studies

For decades, the frontal alpha asymmetry (FAA) – a disproportion in EEG alpha oscillations power between right and left frontal channels – has been one of the most popular measures of depressive disorders (DD) in electrophysiology studies. Patients with DD often manifest a left-sided FAA: relatively higher alpha power in the left versus right frontal lobe. Recently, however, multiple studies failed to confirm this effect, questioning its reproducibility. Our purpose is to thoroughly test the validity of FAA in depression by conducting a multiverse analysis – running many related analyses and testing the sensitivity of the effect to changes in the analytical approach – on data from five independent studies. Only 13 of the 270 analyses revealed significant results. We conclude the paper by discussing theoretical assumptions underlying the FAA and suggest a list of guidelines for improving and expanding the EEG data analysis in future FAA studies.

Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: In each study the decision on the sample size was based on common sample sizes reported in previous literature on alpha asymmetry in depression. Two of the studies used in our paper were recorded in the past, when sample size estimation was not common. It should also be noted that recruiting depressed participants is a difficult and lengthy process, and the final sample size is an effect of cost-benefit analysis (also taking into account project length and available funding). Two other datasets we use in the paper (Study IV and V) are publicly available data and the size of the groups did not depend on our judgement. We overcome the sample size limitations of single studies by presenting results for all five studies in a multiverse approach.

Replicates
• You should report how often each experiment was performed • You should include a definition of biological versus technical replication • The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates • If you encountered any outliers, you should describe how these were handled • Criteria for exclusion/inclusion of data should be clearly stated • High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: The exclusion criteria for subjects are detailed in the Methods -Participants section while the exclusion criteria for channels, signal segments and ICA components are described in Methods -Data preprocessing section.

Statistical reporting
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Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Signal processing and statistical analysis methods were described in sections: Signal analysis and Statistical analysis.
We presented the results with the required details in section Results and Supplementary materials , figures ( Figures 3 -7 ) and tables ( Tables 1 -8 ). The effect size and its 95% confidence interval is given only for single channel pair analyses ( Table 1 and 2; Figure 8 and Figure 8-supplement 1 ) because there is no common standard for calculating and reporting effect sizes and confidence intervals for cluster based permutation test results, especially when no clusters were found.
(For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
• Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied • Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: We described above information in section: Methods -Participants.
Additional data files ("source data") • We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table • Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table • Include model definition files including the full list of parameters used • Include code used for data analysis (e.g., R, MatLab) • Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: Due to the fact that in our article we conduct many analyses we included supplemental figures with legends to all results in the section Supplemental Figures . The code used for data analysis and visualisation is publicly available on Github ( https://github.com/mmagnuski/DiamSar ). Information about other python packages used in the analyses is included in Methods section and relevant entries are present in the References . The data for the three studies are deposited to Dryad repository.