Ensemble of coupling forms and networks among brain rhythms as function of states and cognition

Dynamic networks of cortico-muscular interactions in sleep and neurodegenerative disorders

The brain plays central role in regulating physiological systems, including the skeleto-muscular and locomotor system. Studies of cortico-muscular coordination have primarily focused on associations between movement tasks and dynamics of specific brain waves. However, the brain-muscle functional networks of synchronous coordination among brain waves and muscle activity rhythms that underlie locomotor control remain unknown. Here we address the following fundamental questions: what are the structure and dynamics of cortico-muscular networks; whether specific brain waves are main network mediators in locomotor control; how the hierarchical network organization relates to distinct physiological states under autonomic regulation such as wake, sleep, sleep stages; and how network dynamics are altered with neurodegenerative disorders. We study the interactions between all physiologically relevant brain waves across cortical locations with distinct rhythms in leg and chin muscle activity in healthy and Parkinson's disease (PD) subjects. Utilizing Network Physiology framework and time delay stability approach, we find that 1) each physiological state is characterized by a unique network of cortico-muscular interactions with specific hierarchical organization and profile of links strength; 2) particular brain waves play role as main mediators in cortico-muscular interactions during each state; 3) PD leads to muscle-specific breakdown of cortico-muscular networks, altering the sleep-stage stratification pattern in network connectivity and links strength. In healthy subjects cortico-muscular networks exhibit a pronounced stratification with stronger links during wake and light sleep, and weaker links during REM and deep sleep. In contrast, network interactions reorganize in PD with decline in connectivity and links strength during wake and non-REM sleep, and increase during REM, leading to markedly different stratification with gradual decline in network links strength from wake to REM, light and deep sleep. Further, we find that wake and sleep stages are characterized by specific links strength profiles, which are altered with PD, indicating disruption in the synchronous activity and network communication among brain waves and muscle rhythms. Our findings demonstrate the presence of previously unrecognized functional networks and basic principles of brain control of locomotion, with potential clinical implications for novel network-based biomarkers for early detection of Parkinson's and neurodegenerative disorders, movement, and sleep disorders.

Network of muscle fibers activation facilitates inter-muscular coordination, adapts to fatigue and reflects muscle function

Fundamental movement patterns require continuous skeletal muscle coordination, where muscle fibers with different timing of activation synchronize their dynamics across muscles with distinct functions. It is unknown how muscle fibers integrate as a network to generate and fine tune movements. We investigate how distinct muscle fiber types synchronize across arm and chest muscles, and respond to fatigue during maximal push-up exercise. We uncover that a complex inter-muscular network of muscle fiber cross-frequency interactions underlies push-up movements. The network exhibits hierarchical organization (sub-networks/modules) with specific links strength stratification profile, reflecting distinct functions of muscles involved in push-up movements. We find network reorganization with fatigue where network modules follow distinct phase-space trajectories reflecting their functional role and adaptation to fatigue. Consistent with earlier observations for squat movements under same protocol, our findings point to general principles of inter-muscular coordination for fundamental movements, and open a new area of research, Network Physiology of Exercise.

Dysfunction of NRG1/ErbB4 Signaling in the Hippocampus Might Mediate Long-term Memory Decline After Systemic Inflammation

Accumulating evidence has suggested that a great proportion of sepsis survivors suffer from long-term cognitive impairments after hospital discharge, leading to decreased life quality and substantial caregiving burdens for family members. However, the underlying mechanism remains unclear. In the present study, we established a mouse model of systemic inflammation by repeated lipopolysaccharide (LPS) injections. A combination of behavioral tests, biochemical, and in vivo electrophysiology techniques were conducted to test whether abnormal NRG1/ErbB4 signaling, parvalbumin (PV) interneurons, and hippocampal neural oscillations were involved in memory decline after repeated LPS injections. Here, we showed that LPS induced long-term memory decline, which was accompanied by dysfunction of NRG1/ErbB4 signaling and PV interneurons, and decreased theta and gamma oscillations. Notably, NRG1 treatment reversed LPS-induced decreases in p-ErbB4 and PV expressions, abnormalities in theta and gamma oscillations, and long-term memory decline. Together, our study demonstrated that dysfunction of NRG1/ErbB4 signaling in the hippocampus might mediate long-term memory decline in a mouse model of systemic inflammation induced by repeated LPS injections. Thus, targeting NRG1/ErbB4 signaling in the hippocampus may be promising for the prevention and treatment of this long-term memory decline.

Case report: Cortico-ocular interaction networks in NBA2K

The sport industry has never seen growth such as eSports'. Using synchronized monitoring of two biological processes on a 25-year-old gamer, we investigated how his brain (via EEG) and eyes (via pupil dilation) interacted dynamically over time as an integrated network during NBA2K playing time. After the spectral decomposition of the different Brain and Eye signals into seven frequency bands, we calculated the bivariate equal-time Pearson's cross-correlation between each pair of EEG/Eye spectral power time series. On average, our results show a reorganization of the cortico-muscular network across three sessions (e.g., new interactions, hemispheric asymmetry). These preliminary findings highlight the potential need for individualized, specific, adaptive, and periodized interventions and encourage the continuation of this line of research for the creation of general theories of networks in eSports gaming. Future studies should recruit larger samples, investigate different games, and explore cross-frequency coordination among other key organ systems.

Inter-muscular networks of synchronous muscle fiber activation

Skeletal muscles continuously coordinate to facilitate a wide range of movements. Muscle fiber composition and timing of activation account for distinct muscle functions and dynamics necessary to fine tune muscle coordination and generate movements. Here we address the fundamental question of how distinct muscle fiber types dynamically synchronize and integrate as a network across muscles with different functions. We uncover that physiological states are characterized by unique inter-muscular network of muscle fiber cross-frequency interactions with hierarchical organization of distinct sub-networks and modules, and a stratification profile of links strength specific for each state. We establish how this network reorganizes with transition from rest to exercise and fatigue-a complex process where network modules follow distinct phase-space trajectories reflecting their functional role in movements and adaptation to fatigue. This opens a new area of research, Network Physiology of Exercise, leading to novel network-based biomarkers of health, fitness and clinical conditions.

Extreme conditions affect neuronal oscillations of cerebral cortices in humans in the China Space Station and on Earth

Rhythmical oscillations of neural populations can reflect working memory performance. However, whether neuronal oscillations of the cerebral cortex change in extreme environments, especially in a space station, remains unclear. Here, we recorded electroencephalography (EEG) signals when volunteers and astronauts were executing a memory task in extreme working conditions. Our experiments showed that two extreme conditions affect neuronal oscillations of the cerebral cortex and manifest in different ways. Lengthy periods of mental work impairs the gating mechanism formed by theta-gamma phase-amplitude coupling of two cortical areas, and sleep deprivation disrupts synaptic homeostasis, as reflected by the substantial increase in theta wave activity in the cortical frontal-central area. In addition, we excluded the possibility that nutritional supply or psychological situations caused decoupled theta-gamma phase-amplitude coupling or an imbalance in theta wave activity increase. Therefore, we speculate that the decoupled theta-gamma phase-amplitude coupling detected in astronauts results from their lengthy periods of mental work in the China Space Station. Furthermore, comparing preflight and inflight experiments, we find that long-term spaceflight and other hazards in the space station could worsen this decoupling evolution. This particular neuronal oscillation mechanism in the cerebral cortex could guide countermeasures for the inadaptability of humans working in spaceflight.