Modulation of the brain’s functional network architecture in the transition from wake to sleep

Abstract

The transition from quiet wakeful rest to sleep represents a period over which attention to the external environment fades. Neuroimaging methodologies have provided much information on the shift in neural activity patterns in sleep, but the dynamic restructuring of human brain networks in the transitional period from wake to sleep remains poorly understood. Analysis of electrophysiological measures and functional network connectivity of these early transitional states shows subtle shifts in network architecture that are consistent with reduced external attentiveness and increased internal and self-referential processing. Further, descent to sleep is accompanied by the loss of connectivity in anterior and posterior portions of the default-mode network and more locally organized global network architecture. These data clarify the complex and dynamic nature of the transitional period between wake and sleep and suggest the need for more studies investigating the dynamics of these processes.

Unraveling the Miswired Connectome: A Developmental Perspective

“…In particular, similarities between the awake and sleeping connectomes cannot be assumed to infer equivalence. In adult sleep staging studies, despite overall similarities, state-related differences between wakefulness and non-REM sleep are consistently observed (e.g., Boly et al, 2012; Horovitz et al, 2009; Larson-Prior et al, 2011; Spoormaker et al, 2012). These findings parallel the sleep-related cortical ‘breakdown’ described in the EEG literature: as sleep deepens, cortical intrinsic functional connectivity decreases (Massimini et al, 2005).…”

Studying Brain Organization via Spontaneous fMRI Signal

“…This concern is lessened by several findings across states of consciousness and animal models. First, in humans, the low-frequency correlation structure is similar at rest and in the early stages of sleep (Horovitz et al, 2009; Larson-Prior et al, 2011). Second, organized low-frequency fluctuations in fMRI signal are also found in awake and anesthetized macaques (Hutchison et al, 2011; Moeller et al, 2009; Vincent et al, 2007), marmosets (Liu et al, 2013), rats (Hutchison et al, 2010; Liang et al, 2011), mice (Jonckers et al, 2013; Jonckers et al, 2011; Sforazzini et al, 2014), and awake pigeons (De Groof et al, 2013).…”

Applications of Resting State Functional MR Imaging to Neuropsychiatric Diseases

“…A particular issue to pay attention to is that patients may show different DMN activity from control groups 28,45,46,47–50 in terms of coherence, spatial extent, relative magnitude of ICNs due to diverse factors that are epiphenomena of the illness under consideration related to treatment, lifestyle, demographic, and cognitive features 51,52 . Some of these specifics include medication, sleep 53,54 (one reason to acquire resting state data with the subjects eyes open, is to maximize the chance that subjects are awake during data-gathering acquisition, with consequently stronger temporal BOLD signal 35 . Physiological variables such as breathing and cardiac rate 55,56 can affect data, – for example a shared blood supply between different brain regions may falsely suggest shared variance in resting state FC.…”