Our very large EEG database allows us to not just investigate the genetics of EEG parameters, but also to plot normative developmental curves across the wide age range available in our datasets (Table 1), possibly extended with other developmental samples (Anokhin et al., 2017; Obeid & Picone, 2016; Smit & Anokhin, 2016). These data are valuable to investigate neurodevelopmental disorders and deviant brain development, such as ADHD and autism, with ample power to detect differences. Further, polygenic risk scores based on the ENIGMA‐EEG discovery genome‐wide association meta‐analysis (GWAMA) can be constructed to provide liability indices that may be associated with mental disorders, individual differences in cognition, brain development, and connectivity patterns. The advantage of such an approach is that the subjects reflect the full range of individual variation across the population (Martin et al., 2018; Simmons & Quinn, 2014).
