Self-organized criticality in brain dynamics and network interactions among organ systems

Over the last decades sleep research has focused on epidemiological studies of how different factors affect sleep, and how sleep influences other physiologic and cognitive functions. However, the complex dynamics of sleep stage transitions and arousals which occur at time scales of seconds to minutes during healthy sleep and constitute the sleep micro-architecture are not yet understood. I analyze long-term continuous EEG recordings in rats and human, and dissect emergent signatures of criticality in the dynamics of cortical rhythm bursts in relation to their correlation properties and reciprocal coupling. I show that active states durations follow a power-law distribution while the quiet states durations follow an exponential-like behavior. Such emerging bursting activity in the brain rhythm dynamics described by power-laws and exhibiting long-range spatio-temporal correlations has been proposed as an indication of self-organized criticality (SOC). To have a deeper understanding of SOC in cortical rhythm bursting dynamics, it is essential to study the dynamical evolution of an entire network of physiologic interactions in the context of different physiologic states and pathologic conditions. The human organism comprises various physiological systems, each with its own structural organization and dynamic complexity, leading to transient, fluctuating and nonlinear signals. Understanding integrated physiologic function as emergent phenomena from complex interactions among diverse organ systems is the main focus of a new field, Network Physiology. I apply Network Physiology approach and the novel concept of time delay stability (TDS), and I demonstrate their utility to study transient synchronous bursts in systems dynamics as a fundamental form of physiologic network communications. My results demonstrate that during a given physiological state, the physiological network is characterized by a specific topology and coupling strength between systems. Probing physiological network connectivity and the stability of physiological coupling across physiological states provide new insights on integrated physiological function.2023-03-04T00:00:00