Post by Shireen Parimoo

What’s the science?

Sleep electroencephalogram (EEG) measures, such as spindle and slow wave activity (SWA), are associated with cognitive and behavioral outcomes. For instance, sleep spindles are related to synaptic plasticity underlying learning and memory, and slow wave activity during sleep is thought to be restorative. Deficits in spindle activity and slow wave activity are associated with neuropsychiatric disorders like schizophrenia and depression. Sleep EEG recordings in adults are heritable (i.e. genetically inherited), and differ from those in adolescents. This is because the brain is still developing during adolescence and undergoes structural changes that influence oscillatory activity. The role of genes in sleep EEG in adolescents is currently unknown. This week in the Journal of Neuroscience, Rusterholz and colleagues used high-density EEG to examine sleep-specific oscillations and their heritability across various brain regions in adolescent twins.

How did they do it?

Eighteen pairs of monozygotic (MZ) and 12 pairs of dizygotic (DZ) adolescent twins between the ages of 11 and 14 years took part in this study. Their sleep was monitored for at least five nights to ensure that they were getting adequate sleep each night, after which high-density sleep EEG was recorded for two consecutive nights. The first night served as adaptation to the sleep EEG equipment. EEG recorded on the second (baseline) night was used in subsequent analyses, except when data quality was poor, in which case EEG data from the adaptation night was used instead. The measures of interest included sleep EEG power (strength of the oscillations) in various frequency bands, ranging from slow oscillations between 0.6 – 1.2 Hz to gamma oscillations (at a higher frequency) in the 24 – 44 Hz frequency band. The authors also examined spindle characteristics like amplitude, duration, density, and integrated spindle activity, which is the integrated spindle amplitude over time (i.e. intensity of spindles). Structural equation modeling (SEM) was used to estimate the contribution of genetics and environmental factors to the sleep EEG measures, while differentiating between shared and unique environmental factors that the twins were exposed to during development.

What did they find?

Genes strongly contributed to slow wave activity in many cortical regions, accounting for 60 – 93% of variance in slow wave activity, whereas unique environmental factors explained 30 – 44% of variance in slow wave activity in frontal regions. Shared environmental factors did not significantly contribute to slow wave activity. Sleep spindles in posterior regions of the brain were influenced strongly by genetic factors, whereas shared environmental factors contributed to spindles in more anterior regions. Shared environmental factors contributed to spindle amplitude and integrated spindle activity in anterior brain regions for slow (10 – 12 Hz) and fast (12 – 16 Hz) spindles. Moreover, both shared and unique environmental factors contributed to the density and duration of sleep spindles. Specifically, shared environmental factors contributed to the density and duration of fast spindles in fronto-central brain regions, and unique environmental factors influenced the density and duration of fast spindles in posterior brain regions.