About this Research Topic
The field of Network Physiology explores the multi-scale, multi-dimensional nature of the body's systems through interactions among organs, which communicate via hemodynamic, metabolic, hormonal, and neuronal pathways in their interaction with the environment. The focus here is on the interdependence between, the brain - composed of neurons that function both as nodes (somas) and connectors (axons), forming intricate Neuronal Networks (NN)- and muscular effectors, aware that this interplay works only via the multimodal sensory feedback. Networks can be defined by nodes that receive environmental (outside the network) inputs and produce outputs, with connections that are both excitatory and inhibitory. A key Research Topic aim is deepening understanding of how time-structured patterns of electrical activity, called local neurodynamics, of specific nodes emerge from the muscular-central interaction, providing the goal-directed behaviour.
Building on existing knowledge, we propose the feedback-synchrony-plasticity triad as a fundamental organizing principle for neuronal networks across multiple scales. This triad may explain the fractal properties observed in neurodynamics and it would be very interesting to connect such features with the muscular patterns producing behaviour. From a translational perspective, we propose to utilize both invasive and non-invasive electrophysiological techniques alongside invasive and non-invasive brain stimulation to enhance our understanding and treatment of neurodynamic dysfunctions. This approach aligns with the emerging field of neuromodulation, which focuses on treating ailments through precise electrical communication.
Such coordinated communication between central networks and muscle effectors. tunes up along life, with progressive fine-tuning of frequency coding and dynamic properties within corticospinal networks. In later life, this tuning attenuates, and network integration breaks down. The fine-tuning of central networks relies on continuous sensory integration with feedback circuits, reflecting in muscle-specific spectral profiles. These profiles are robust across various timescales, universal among subjects, and follow a developmental pathway affected by fatigue and aging.
Understanding cortico-muscular synchronizations and their interaction provides insights into age-related changes, autonomic regulation, and chronic fatigue. This research focuses on developing novel analytic and computational methods within the Network Physiology framework, applicable to clinical conditions such as multiple sclerosis, muscle dystrophy, neurodegenerative disorders, sports trauma, injuries and behavioural disorders including eating shopping gaming disorders to depression and suicide. Identifying state and synchronization measures specific to complex systems will capture the richness of information transfer and network sensitivity to behavioral and structural conditions, particularly in manual control networks.
Building on existing knowledge, we propose the feedback-synchrony-plasticity triad as a fundamental organizing principle for neuronal networks across multiple scales. This triad may explain the fractal properties observed in neurodynamics and it would be very interesting to connect such features with the muscular patterns producing behaviour. From a translational perspective, we propose to utilize both invasive and non-invasive electrophysiological techniques alongside invasive and non-invasive brain stimulation to enhance our understanding and treatment of neurodynamic dysfunctions. This approach aligns with the emerging field of neuromodulation, which focuses on treating ailments through precise electrical communication.
Such coordinated communication between central networks and muscle effectors. tunes up along life, with progressive fine-tuning of frequency coding and dynamic properties within corticospinal networks. In later life, this tuning attenuates, and network integration breaks down. The fine-tuning of central networks relies on continuous sensory integration with feedback circuits, reflecting in muscle-specific spectral profiles. These profiles are robust across various timescales, universal among subjects, and follow a developmental pathway affected by fatigue and aging.
Understanding cortico-muscular synchronizations and their interaction provides insights into age-related changes, autonomic regulation, and chronic fatigue. This research focuses on developing novel analytic and computational methods within the Network Physiology framework, applicable to clinical conditions such as multiple sclerosis, muscle dystrophy, neurodegenerative disorders, sports trauma, injuries and behavioural disorders including eating shopping gaming disorders to depression and suicide. Identifying state and synchronization measures specific to complex systems will capture the richness of information transfer and network sensitivity to behavioral and structural conditions, particularly in manual control networks.
Keywords: brain-muscular synchronizations, maturation, electroencephalography, electromyography, fatigue, feedback, plasticity, sleep, network physiology, sensorimotor control
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