Outer Brain Oscillations in Down Syndrome - Ruiz-Mejias, Marcel (Frontiers in Systems Neuroscience, 2019)
Unraveling the alterations of the underlying circuits in neurobiological disorders is with no doubt one of the most interesting applications of studying brain oscillatory activity. Sleep and brain oscillatory activity in Down syndrome (DS) is a particularly explored field of study, with early findings in sleep alterations in DS patients. Nowadays it is well accepted the relationship of sleep with cognitive function, due to its implication in processes such as memory consolidation. As well, rhythmic activity of neural networks such as alpha or gamma waves has been related widely to cognition in the last decades. Both sleep and oscillatory activity are tightly related, as the major oscillatory feature of sleep -the slow oscillation (∼1Hz)- shows an exquisite interplay of different forms of rhythmic neuronal activity. Sleep and oscillatory activity in DS has been studied from the mid 20th century, but literature has appeared sporadically in the last decades. From the early descriptive studies, few works reported the differential features of sleep in DS individuals, showing a wide diversity of results. Some studies, addressed network oscillatory activity emerging from external brain circuits of DS individuals, with results related to different frequency bands of the electroencephalogram (EEG) signal. Even fewer studies have been published in models, but interestingly, some of them focused in the network mechanisms that may explain intellectual disability and cognitive deficits observed in DS. Here, a review is presented that aims to gather the work performed in the field and provide a wide and global view about the diversity of published studies. We aim to highlight the importance of studying network oscillatory activity in mouse models to infer alterations in the underlying circuits related to cognition, such as in intellectual disability. In this direction, we claim alpha and gamma rhythms generated by the cerebral cortex as a tool for evaluating an unbalance between excitation and inhibition in DS, which points out toward an over-inhibited network. Finally, we also aim to situate oscillatory activity as a key phenomenon that may be used as a biomarker for monitoring as well the effect of novel therapeutic strategies.