Genetic analysis was conducted in GWAF (Genome-Wide Association analyses with Family)41 on 6,832,792 SNPs using a linear mixed model (LMM) incorporating a genetic relationship matrix to control for the relatedness in the family sample41-42. Principal components (PCs) derived from GWAS data were used to assign ancestry in the genotyped sample, and families were classified as European ancestry (EA) or African ancestry (AA) according to the ancestry of the greatest proportion of family members. Analyses were conducted separately in the families of AA and EA, using identical phenotypic definitions, covariates, SNP QC standards, MAF thresholds and imputation protocols. Subsequently, MTAG44 (multi- trait analyses of GWAS) was run to include summary statistics from all eight theta EEG coherences phenotypes, both low and high theta for the four pairs described in the EEG Recording & Processing section. MTAG is a multi-trait approach that leverages the common genetic information across multiple correlated traits to boost the power of each individual trait44. MTAG is also powerful at disentangling spurious sources of genetic correlation, such as due to overlapping samples, using Linkage Disequilibrium Score Regression45. Meta-analysis
