Sleep, neuroengineering and dynamics

Altered Coactive Micropattern Connectivity in the Default-Mode Network during the Sleep-Wake Cycle

The default-mode network (DMN) is believed to be associated with levels of consciousness, but how the functional connectivity (FC) of the DMN changes across different states of consciousness is still unclear. In the current work, we addressed this issue by exploring the coactive micropattern (CAMP) networks of the DMN according to the CAMPs of rat DMN activity during the sleep-wake cycle and tracking their topological alterations among different states of consciousness. Three CAMP networks were observed in DMN activity, and they displayed greater FC and higher efficiency than the original DMN structure in all states of consciousness, implying more efficient information processing in the CAMP networks. Furthermore, no significant differences in FC or network properties were found among the three CAMP networks in the waking state. However, the three networks were distinct in their characteristics in two sleep states, indicating that different CAMP networks played specific roles in distinct sleep states. In addition, we found that the changes in the FC and network properties of the CAMP networks were similar to those in the original DMN structure, suggesting intrinsic effects of various states of consciousness on DMN dynamics. Our findings revealed three underlying CAMP networks within the DMN dynamics and deepened the current knowledge concerning FC alterations in the DMN during conscious changes in the sleep-wake cycle.

Relationships between short and fast brain timescales

Brain electric activity exhibits two important features: oscillations with different timescales, characterized by diverse functional and psychological outcomes, and a temporal power law distribution. In order to further investigate the relationships between low- and high- frequency spikes in the brain, we used a variant of the Borsuk-Ulam theorem which states that, when we assess the nervous activity as embedded in a sphere equipped with a fractal dimension, we achieve two antipodal points with similar features (the slow and fast, scale-free oscillations). We demonstrate that slow and fast nervous oscillations mirror each other over time via a sinusoid relationship and provide, through the Bloch theorem from solid-state physics, the possible equation which links the two timescale activities. We show that, based on topological findings, nervous activities occurring in micro-levels are projected to single activities at meso- and macro-levels. This means that brain functions assessed at the higher scale of the whole brain necessarily display a counterpart in the lower ones, and vice versa. Our topological approach makes it possible to assess brain functions both based on entropy, and in the general terms of particle trajectories taking place on donut-like manifolds. Condensed brain activities might give rise to ideas and concepts by combination of different functional and anatomical levels. Furthermore, cognitive phenomena, as well as social activity can be described by the laws of quantum mechanics; memories and decisions exhibit holographic organization. In physics, the term duality refers to a case where two seemingly different systems turn out to be equivalent. This topological duality holds for all the types of spatio-temporal brain activities, independent of their inter- and intra-level relationships, strength, magnitude and boundaries, allowing us to connect the physiological manifestations of consciousness to the electric activities of the brain.

Sleep as spatiotemporal integration of biological processes that evolved to periodically reinforce neurodynamic and metabolic homeostasis: The 2m3d paradigm of sleep

Sleep continues to perplex scientists and researchers. Despite decades of sleep research, we still lack a clear understanding of the biological functions and evolution of sleep. In this review, we will examine sleep from a functional and phylogenetic perspective and describe some important conceptual gaps in understanding sleep. Classical theories of the biology and evolution of sleep emphasize sensory activation, energy balance, and metabolic homeostasis. Advances in electrophysiology, functional neuroimaging, and neuroplasticity allow us to view sleep within the framework of neural dynamics. With this paradigm shift, we have come to realize the importance of neurodynamic homeostasis in shaping the biology of sleep. Evidently, animals sleep to achieve neurodynamic and metabolic homeostasis. We are not aware of any framework for understanding sleep where neurodynamic, metabolic, homeostatic, chronophasic, and afferent variables are all taken into account. This motivated us to propose the two-mode three-drive (2m3d) paradigm of sleep. In the 2m3d paradigm, local neurodynamic/metabolic (N/M) processes switch between two modes-m0 and m1-in response to three drives-afferent, chronophasic, and homeostatic. The spatiotemporal integration of local m0/m1 operations gives rise to the global states of sleep and wakefulness. As a framework of evolution, the 2m3d paradigm allows us to view sleep as a robust adaptive strategy that evolved so animals can periodically reinforce neurodynamic and metabolic homeostasis while remaining sensitive to their internal and external environment.