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Abnormal EEG features are a hallmark of epilepsy, and abnormal frequency and network features are apparent in EEGs from people with idiopathic generalised epilepsy in both ictal and interictal states. Here, we characterise differences in the resting-state EEG of individuals with juvenile myoclonic epilepsy and assess factors influencing the heterogeneity of EEG features. We collected EEG data from 147 participants with juvenile myoclonic epilepsy through the Biology of Juvenile Myoclonic Epilepsy study. 95 control EEGs were acquired from two independent studies (Chowdhury et al. (2014) and EU-AIMS Longitudinal European Autism Project). We extracted frequency and functional network-based features from 10-20 s epochs of resting-state EEG, including relative power spectral density, peak alpha frequency, network topology measures and brain network ictogenicity: a computational measure of the propensity of networks to generate seizure dynamics. We tested for differences between epilepsy and control EEGs using univariate, multivariable and receiver operating curve analysis. Additionally, we explored the heterogeneity of EEG features within and between cohorts by testing for associations with potentially influential factors such as age, sex, epoch length and time, as well as testing for associations with clinical phenotypes including anti-seizure medication, and seizure characteristics in the epilepsy cohort. P-values were corrected for multiple comparisons. Univariate analysis showed significant differences in power spectral density in delta (2-5 Hz) (p = 0.0007, hedges’ g = 0.55) and low-alpha (6-9 Hz) (p = 2.9 × 10−8, g = 0.80) frequency bands, peak alpha frequency (p = 0.000007, g = 0.66), functional network mean degree (p = 0.0006, g = 0.48) and brain network ictogenicity (p = 0.00006, g = 0.56) between epilepsy and controls. Since age (p = 0.009) and epoch length (p = 1.7 × 10−8) differed between the two groups and were potential confounders, we controlled for these covariates in multivariable analysis where disparities in EEG features between epilepsy and controls remained. Receiver operating curve analysis showed low-alpha power spectral density was optimal at distinguishing epilepsy from controls, with an area under the curve of 0.72. Lower average normalized clustering coefficient and shorter average normalized path length were associated with poorer seizure control in epilepsy patients. To conclude, individuals with juvenile myoclonic epilepsy have increased power of neural oscillatory activity at low-alpha frequencies, and increased brain network ictogenicity compared to controls, supporting evidence from studies in other epilepsies with considerable external validity. In addition, the impact of confounders on different frequency-based and network-based EEG features observed in this study highlights the need for careful consideration and control of these factors in future EEG research in idiopathic generalised epilepsy particularly for their use as biomarkers.

What kind of reality is reflected in children's literature? In this article Anne Scott MacLeod suggests that one can come to understand a society's mood—the concerns of individuals about what is and what should be—by analyzing the literature written for children in that society. Viewing children's fiction of the early nineteenth century against the social background of the time, the author shows how the stories reveal Jacksonian Americans' concerns for the conservation of a particular kind of moral character that appeared threatened by social change. Thus,MacLeod argues that the primary function of children's fiction in Jacksonian America was not entertainment but the moral education of a new generation, emphasizing social responsibility in contrast to the spirit of individual aggrandizement that seemed, to these authors, to endanger their world.

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