Individual differences in slow wave sleep architecture relate to variation in white matter microstructure across adulthood.

Sleep plays a key role in supporting brain function and resilience to brain decline. It is well known that sleep changes substantially with aging and that aging is associated with deterioration of brain structure. In this study, we sought to characterize the relationship between slow wave slope (SWslope)-a key marker of sleep architecture and an indirect proxy of sleep quality-and microstructure of white matter pathways in healthy adults with no sleep complaints. Participants were 12 young (24-27 years) and 12 older (50-79 years) adults. Sleep was assessed with nocturnal electroencephalography (EEG) and the Pittsburgh Sleep Quality Index (PSQI). White matter integrity was assessed using tract-based spatial statistics (TBSS) on tensor-based metrics such as Fractional Anisotropy (FA) and Mean Diffusivity (MD). Global PSQI score did not differ between younger (n = 11) and older (n = 11) adults (U = 50, p = 0.505), but EEG revealed that younger adults had a steeper SWslope at both frontal electrode sites (F3: U = 2, p < 0.001, F4: U = 4, p < 0.001, n = 12 younger, 10 older). There were widespread correlations between various diffusion tensor-based metrics of white matter integrity and sleep SWslope, over and above effects of age (n = 11 younger, 9 older). This was particularly evident for the corpus callosum, corona radiata, superior longitudinal fasciculus, internal and external capsule. This indicates that reduced sleep slow waves may be associated with widespread white matter deterioration. Future studies should investigate whether interventions targeted at improving sleep architecture also impact on decline in white matter microstructure in older adults.

Sleep and Motor Learning: Implications for Physical Rehabilitation After Stroke.

Sleep is essential for healthy brain function and plasticity underlying learning and memory. In the context of physical impairment such as following a stroke, sleep may be particularly important for supporting critical recovery of motor function through similar processes of reorganization in the brain. Despite a link between stroke and poor sleep, current approaches to rehabilitative care often neglect the importance of sleep in clinical assessment and treatment. This review assimilates current evidence on the role of sleep in motor learning, with a focus on the implications for physical rehabilitation after stroke. We further outline practical considerations for integrating sleep assessment as a vital part of clinical care.

Sleep-dependent motor memory consolidation in older adults depends on task demands.

It is often suggested that sleep-dependent consolidation of motor learning is impaired in older adults. The current study challenges this view and suggests that the degree of motor consolidation seen with sleep in older age groups depends on the kinematic demands of the task. We show that, when tested with a classic sequence learning task, requiring individuated finger movements, older adults did not show sleep-dependent consolidation. By contrast, when tested with an adapted sequence learning task, in which movements were performed with the whole hand, sleep-dependent motor improvement was observed in older adults. We suggest that age-related decline in fine motor dexterity may in part be responsible for the previously described deficit in sleep-dependent motor consolidation with aging.

Local GABA concentration is related to network-level resting functional connectivity.

Anatomically plausible networks of functionally inter-connected regions have been reliably demonstrated at rest, although the neurochemical basis of these 'resting state networks' is not well understood. In this study, we combined magnetic resonance spectroscopy (MRS) and resting state fMRI and demonstrated an inverse relationship between levels of the inhibitory neurotransmitter GABA within the primary motor cortex (M1) and the strength of functional connectivity across the resting motor network. This relationship was both neurochemically and anatomically specific. We then went on to show that anodal transcranial direct current stimulation (tDCS), an intervention previously shown to decrease GABA levels within M1, increased resting motor network connectivity. We therefore suggest that network-level functional connectivity within the motor system is related to the degree of inhibition in M1, a major node within the motor network, a finding in line with converging evidence from both simulation and empirical studies. DOI: http://dx.doi.org/10.7554/eLife.01465.001.