Universal spectral profile and dynamic evolution of muscle activation: a hallmark of muscle type and physiological state.

The skeletal muscle is an integrated multicomponent system with complex dynamics of continuous myoelectrical activation of various muscle types across time scales to facilitate muscle coordination among units and adaptation to physiological states. To understand the multiscale dynamics of neuromuscular activity, we investigated spectral characteristics of different muscle types across time scales and their evolution with physiological states. We hypothesized that each muscle type is characterized by a specific spectral profile, reflecting muscle composition and function, that remains invariant over time scales and is universal across subjects. Furthermore, we hypothesized that the myoelectrical activation and corresponding spectral profile during certain movements exhibit an evolution path in time that is unique for each muscle type and reflects responses in muscle dynamics to exercise, fatigue, and aging. To probe the multiscale mechanism of neuromuscular regulation, we developed a novel protocol of repeated squat exercise segments, each performed until exhaustion, and we analyzed differentiated spectral power responses over a range of frequency bands for leg and back muscle activation in young and old subjects. We found that leg and back muscle activation is characterized by muscle-specific spectral profiles, with differentiated frequency band contribution, and a muscle-specific evolution path in response to fatigue and aging that is universal across subjects in each age group. The uncovered universality among subjects in the spectral profile of each muscle at a given physiological state, as well as the robustness in the evolution of these profiles over a range of time scales and states, reveals a previously unrecognized multiscale mechanism underlying the differentiated response of distinct muscle types to exercise-induced fatigue and aging.NEW & NOTEWORTHY To understand coordinated function of distinct fibers in a muscle, we investigated spectral dynamics of muscle activation during maximal exercise across a range of frequency bands and time scales of observation. We discovered a spectral profile that is specific for each muscle type, robust at short, intermediate, and large time scales, universal across subjects, and characterized by a muscle-specific evolution path with accumulation of fatigue and aging, indicating a previously unrecognized multiscale mechanism of muscle tone regulation.

Modular organization of brain resting state networks in chronic back pain patients.

Recent work on functional magnetic resonance imaging large-scale brain networks under resting conditions demonstrated its potential to evaluate the integrity of brain function under normal and pathological conditions. A similar approach is used in this work to study a group of chronic back pain patients and healthy controls to determine the impact of long enduring pain over brain dynamics. Correlation networks were constructed from the mutual partial correlations of brain activity's time series selected from ninety regions using a well validated brain parcellation atlas. The study of the resulting networks revealed an organization of up to six communities with similar modularity in both groups, but with important differences in the membership of key communities of frontal and temporal regions. The bulk of these findings were confirmed by a surprisingly naive analysis based on the pairwise correlations of the strongest and weakest correlated healthy regions. Beside confirming the brain effects of long enduring pain, these results provide a framework to study the effect of other chronic conditions over cortical function.