The sleeping brain as a complex system

Abstract

'Complexity science' is a rapidly developing research direction with applications in a multitude of fields that study complex systems consisting of a number of nonlinear elements with interesting dynamics and mutual interactions. This Theme Issue 'The complexity of sleep' aims at fostering the application of complexity science to sleep research, because the brain in its different sleep stages adopts different global states that express distinct activity patterns in large and complex networks of neural circuits. This introduction discusses the contributions collected in the present Theme Issue. We highlight the potential and challenges of a complex systems approach to develop an understanding of the brain in general and the sleeping brain in particular. Basically, we focus on two topics: the complex networks approach to understand the changes in the functional connectivity of the brain during sleep, and the complex dynamics of sleep, including sleep regulation. We hope that this Theme Issue will stimulate and intensify the interdisciplinary communication to advance our understanding of the complex dynamics of the brain that underlies sleep and consciousness.

Increment Entropy as a Measure of Complexity for Time Series

“…Nowadays, the notion of complexity has been ubiquitously used to examine a variety of time series, ranging from diverse physiological signals [1][2][3][4][5][6][7][8][9] to financial time series [10,11] and ecological time series [12]. There there is not an established universal definition of complexity to date [13].…”

Lempel-Ziv complexity of cortical activity during sleep and waking in rats

“…Therefore, caution is warranted in generalizing these findings to other brain regions, anatomically distinct from the cortex, and other species, especially humans, in which the EEG is usually recorded from the scalp, and the underlying neuronal activity data are not available. Second, it should be kept in mind that the signals under scrutiny usually represent just a tiny fraction of the infinitely complex brain dynamics occurring at many spatio-temporal scales and produced by multiple independent and interacting components ( Olbrich et al 2011 ; Vyazovskiy and Delogu 2014 ), which poses a significant challenge for interpreting their origin and functional significance. Third, although our results suggest that LZC may appear extremely useful and provide important insights into the mechanisms underlying large-scale changes in EEG signals, at present, it remains a speculation.…”

“…More generally, the regulatory mechanisms of sleep remain, in many parts, poorly understood because of an enormous neuroanatomical complexity of circuits relevant for sleep regulation and the multitude of spatial and temporal scales at which sleep regulation is manifested ( Brown et al 2012 ; Olbrich et al 2011 ; Vyazovskiy and Delogu 2014 ). Therefore, the development of novel signal analysis approaches will not merely provide additional information but may appear crucially important for understanding the general principles underlying sleep dynamics.…”

Critical Dynamics and Coupling in Bursts of Cortical Rhythms Indicate Non-Homeostatic Mechanism for Sleep-Stage Transitions and Dual Role of VLPO Neurons in Both Sleep and Wake

“…This constitutes a challenge to the current homeostatic framework for sleep regulation, which considers sleep as an equilibrium process, and focuses on factors modulating sleep over large time scales, such as homeostatic sleep drive, sleep propensity and inertia, and ultradian and circadian rhythms (Borbély and Achermann, 1999;Saper et al, 2005;Brown et al, 2012). Existing homeostatic models, although successfully providing a good description of consolidated sleep and wakefulness over time scales of hours (Borbély and Achermann, 1999;Achermann and Borbély, 2003;Saper et al, 2001Saper et al, , 2010, do not capture the emergent complexity of transient and abrupt behaviors at scales of seconds and minutes (Lo et al, 2004;Olbrich et al, 2011), and do not account for the related dynamics of bursts in cortical rhythms.…”