Detecting Psychological Interventions Using Bilateral Electromyographic Wearable Sensors.

This study investigated the impact of auditory stimuli on muscular activation patterns using wearable surface electromyography (EMG) sensors. Employing four key muscles (Sternocleidomastoid Muscle (SCM), Cervical Erector Muscle (CEM), Quadricep Muscles (QMs), and Tibialis Muscle (TM)) and time domain features, we differentiated the effects of four interventions: silence, music, positive reinforcement, and negative reinforcement. The results demonstrated distinct muscle responses to the interventions, with the SCM and CEM being the most sensitive to changes and the TM being the most active and stimulus dependent. Post hoc analyses revealed significant intervention-specific activations in the CEM and TM for specific time points and intervention pairs, suggesting dynamic modulation and time-dependent integration. Multi-feature analysis identified both statistical and Hjorth features as potent discriminators, reflecting diverse adaptations in muscle recruitment, activation intensity, control, and signal dynamics. These features hold promise as potential biomarkers for monitoring muscle function in various clinical and research applications. Finally, muscle-specific Random Forest classification achieved the highest accuracy and Area Under the ROC Curve for the TM, indicating its potential for differentiating interventions with high precision. This study paves the way for personalized neuroadaptive interventions in rehabilitation, sports science, ergonomics, and healthcare by exploiting the diverse and dynamic landscape of muscle responses to auditory stimuli.

Age-related breakdown in networks of inter-muscular coordination.

Assessing inter-muscular coordination in older adults is crucial, as it directly impacts an individual's ability for independent functioning, injury prevention, and active engagement in daily activities. However, the precise mechanisms by which distinct muscle fiber types synchronize their activity across muscles to generate coordinated movements in older adults remain unknown. Our objective is to investigate how distinct muscle groups dynamically synchronize with each other in young and older adults during exercise. Thirty-five young adults and nine older adults performed one bodyweight squat set until exhaustion. Simultaneous surface electromyography (sEMG) recordings were taken from the left and right vastus lateralis, and left and right erector spinae. To quantify inter-muscular coordination, we first obtained ten time series of sEMG band power for each muscle, representing the dynamics of different muscle fiber types. Next, we calculated the bivariate equal-time Pearson's cross-correlation for each pair of sEMG band power time series across all leg and back muscles. The main results show (i) an overall reduction in the degree of inter-muscular coordination, and (ii) increased stratification of the inter-muscular network in older adults compared to young adults. These findings suggest that as individuals age, the global inter-muscular network becomes less flexible and adaptable, hindering its ability to reorganize effectively in response to fatigue or other stimuli. This network approach opens new avenues for developing novel network-based markers to characterize multilevel inter-muscular interactions, which can help target functional deficits and potentially reduce the risk of falls and neuro-muscular injuries in older adults.

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.

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.

Cardiorespiratory Coordination in Collegiate Rowing: A Network Approach to Cardiorespiratory Exercise Testing.

Collegiate rowing performance is often assessed by a cardiopulmonary exercise test (CPET). Rowers' on-water performance involves non-linear dynamic interactions and synergetic reconfigurations of the cardiorespiratory system. Cardiorespiratory coordination (CRC) method measures the co-variation among cardiorespiratory variables. Novice (n = 9) vs. Intermediate (n = 9) rowers' CRC (H0: Novice CRC = Intermediate CRC; HA: Novice CRC < Intermediate CRC) was evaluated through principal components analysis (PCA). A female NCAA Division II team (N = 18) grouped based on their off-water performance on 6000 m time trial. Rowers completed a customized CPET to exhaustion and a variety of cardiorespiratory values were recorded. The number of principal components (PCs) and respective PC eigenvalues per group were computed on SPSS vs28. Intermediate (77%) and Novice (33%) groups showed one PC1. Novice group formed an added PC2 due to the shift of expired fraction of oxygen or, alternatively, heart rate/ventilation, from the PC1 cluster of examined variables. Intermediate rowers presented a higher degree of CRC, possible due to their increased ability to utilize the bicarbonate buffering system during the CPET. CRC may be an alternative measure to assess aerobic fitness providing insights to the complex cardiorespiratory interactions involved in rowing during a CPET.

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.

Effects of Acute Partial Sleep Deprivation and High-Intensity Interval Exercise on Postprandial Network Interactions.

Introduction: High-intensity interval exercise (HIIE) is deemed effective for cardiovascular and autonomic nervous system (ANS) health-related benefits, while ANS disturbance increases the risk for cardiovascular disease (CVD). Postprandial lipemia and acute-partial sleep deprivation (APSD) are considered as CVD risk factors due to their respective changes in ANS. Exercising in the morning hours after APSD and have a high-fat breakfast afterwards may alter the interactions of the cardiovascular, autonomic regulation, and postprandial lipemic systems threatening individuals' health. This study examined postprandial network interactions between autonomic regulation through heart rate variability (HRV) and lipemia via low-density lipoprotein (LDL) cholesterol in response to APSD and HIIE. Methods: Fifteen apparently healthy and habitually good sleepers (age 31 ± 5.2 SD yrs) completed an acute bout of an isocaloric HIIE (in form of 3:2 work-to-rest ratio at 90 and 40% of VO2 reserve) after both a reference sleep (RSX) and 3-3.5 h of acute-partial sleep deprivation (SSX) conditions. HRV time and frequency domains and LDL were evaluated in six and seven time points surrounding sleep and exercise, respectively. To identify postprandial network interactions, we constructed one correlation analysis and one physiological network for each experimental condition. To quantify the interactions within the physiological networks, we also computed the number of links (i.e., number of significant correlations). Results: We observed an irruption of negative links (i.e., negative correlations) between HRV and LDL in the SSX physiological network compared to RSX. Discussion: We recognize that a correlation analysis does not constitute a true network analysis due to the absence of analysis of a time series of the original examined physiological variables. Nonetheless, the presence of negative links in SSX reflected the impact of sleep deprivation on the autonomic regulation and lipemia and, thus, revealed the inability of HIIE to remain cardioprotective under APSD. These findings underlie the need to further investigate the effects of APSD and HIIE on the interactions among physiological systems.

Dynamic networks of physiologic interactions of brain waves and rhythms in muscle activity.

The brain plays a central role in facilitating vital body functions and in regulating physiological and organ systems, including the skeleto-muscular and locomotor system. While neural control is essential to synchronize and coordinate activation of various muscle groups and muscle fibers within muscle groups in relation to body movements and distinct physiologic states, the dynamic networks of brain-muscle interactions have not been explored and the complex regulatory mechanism of brain-muscle control remains unknown. Here we present a first study of network interactions between brain waves at different cortical locations and peripheral muscle activity across key physiologic states - wake, sleep and distinct sleep stages. Utilizing a novel approach based on the Network Physiology framework and the concept of time delay stability, we find that for each physiologic state the network of cortico-muscular interactions is characterized by a specific hierarchical organization of network topology and network links strength, where particular brain waves are main mediators of interaction and control of muscular activity. Further, we uncover that with transition from one physiological state to another, the brain-muscle interaction network undergoes marked reorganization in the profile of network links strength, indicating a direct association between network structure and physiological state and function. The pronounced stratification in brain-muscle network characteristics across sleep stages is consistent for chin and leg muscle groups and persists across subjects, indicating a remarkable universality and a previously unrecognized basic physiologic mechanism that regulates muscle activity even during rest and in the absence targeted direct movement. Our findings demonstrate previously unrecognized coordination between brain waves and activation of different muscle fiber types within muscle groups, laws of brain-muscle cross-communication and principles of network integration and control. These investigations demonstrate the potential of network-based biomarkers for classification of distinct physiological states and conditions, for the diagnosis and prognosis of neurodegenerative, movement and sleep disorders, and for developing efficient treatment strategies.

Network Physiology of Exercise: Beyond Molecular and Omics Perspectives.

Molecular Exercise Physiology and Omics approaches represent an important step toward synthesis and integration, the original essence of Physiology. Despite the significant progress they have introduced in Exercise Physiology (EP), some of their theoretical and methodological assumptions are still limiting the understanding of the complexity of sport-related phenomena. Based on general principles of biological evolution and supported by complex network science, this paper aims to contrast theoretical and methodological aspects of molecular and network-based approaches to EP. After explaining the main EP challenges and why sport-related phenomena cannot be understood if reduced to the molecular level, the paper proposes some methodological research advances related to the type of studied variables and measures, the data acquisition techniques, the type of data analysis and the assumed relations among physiological levels. Inspired by Network Physiology, Network Physiology of Exercise provides a new paradigm and formalism to quantify cross-communication among diverse systems across levels and time scales to improve our understanding of exercise-related phenomena and opens new horizons for exercise testing in health and disease.

Effects of Crawling before Walking: Network Interactions and Longitudinal Associations in 7-Year-Old Children.

BACKGROUND: To study the impact of crawling before walking (CBW) on network interactions among body composition, the cardiovascular system, lung function, motor competence and physical fitness, at age 7, and to assess the longitudinal association between CBW and body composition, the cardiovascular system, lung function, motor competence, physical fitness and physical activity parameters, at age 7. METHOD: CBW, body composition, cardiovascular system, lung function, motor competence, physical fitness and physical activity were assessed in seventy-seven healthy Caucasian children. RESULTS: Network analyses revealed that the crawling group had a greater number of links among all the studied variables compared with the non-crawling group. In the longitudinal study, using multiple regression analyses, crawling was independently associated with fat mass (%), fat-to-muscle ratio and systolic blood pressure, with models explaining up to 56.3%, 56.7% and 29.9% of their variance, respectively. CONCLUSIONS: CBW during child's development is a possible modulator in the network interactions between body systems and it could influence future metabolic and cardiovascular health.

Cardiorespiratory Coordination During Exercise in Adults With Down Syndrome.

Introduction: Down syndrome (DS) is a chromosomal disorder affecting simultaneously cardiovascular and respiratory systems. There is no research studying the coupling between these systems during cardiorespiratory exercise testing in a population with DS. Cardiorespiratory coordination (CRC), evaluated through principal component analysis (PCA), measures the covariation of cardiorespiratory variables during exercise. Objective: To investigate and compare CRC in adults with and without DS during maximal cardiorespiratory exercise testing. Methods: Fifteen adults with DS and 15 adults without disabilities performed a maximal cardiorespiratory exercise test on a treadmill. First, the slope, and afterward the velocity was increased regularly until participants reached exhaustion. The time series of six selected cardiorespiratory variables [ventilation per minute, an expired fraction of O2, the expired fraction of CO2, heart rate, systolic blood pressure (SBP), and diastolic blood pressure (DBP)] were extracted for the analysis. The number of principal components (PCs), the first PC eigenvalues (PC1), and the information entropy were computed for each group (non-DS and DS) and compared using a t-test or a Mann-Whitney U test. Results: Two PCs in the non-DS group and three PCs in the DS group captured the variance of the studied cardiorespiratory variables. The formation of an additional PC in the DS group was the result of the shift of SBP and DBP from the PC1 cluster of variables. Eigenvalues of PC1 were higher in the non-DS (U = 30; p = 0.02; d = 1.47) than in the DS group, and the entropy measure was higher in the DS compared with the non-DS group (U = 37.5; p = 0.008; d = 0.70). Conclusion: Adults with Down syndrome showed higher CRC dimensionality and a higher entropy measure than participants without disabilities. Both findings point toward a lower efficiency of the cardiorespiratory function during exercise in participants with DS. CRC appears as an alternative measure to investigate the cardiorespiratory function and its response to exercise in the DS population.

Network Physiology of Exercise: Vision and Perspectives.

The basic theoretical assumptions of Exercise Physiology and its research directions, strongly influenced by reductionism, may hamper the full potential of basic science investigations, and various practical applications to sports performance and exercise as medicine. The aim of this perspective and programmatic article is to: (i) revise the current paradigm of Exercise Physiology and related research on the basis of principles and empirical findings in the new emerging field of Network Physiology and Complex Systems Science; (ii) initiate a new area in Exercise and Sport Science, Network Physiology of Exercise (NPE), with focus on basic laws of interactions and principles of coordination and integration among diverse physiological systems across spatio-temporal scales (from the sub-cellular level to the entire organism), to understand how physiological states and functions emerge, and to improve the efficacy of exercise in health and sport performance; and (iii) to create a forum for developing new research methodologies applicable to the new NPE field, to infer and quantify nonlinear dynamic forms of coupling among diverse systems and establish basic principles of coordination and network organization of physiological systems. Here, we present a programmatic approach for future research directions and potential practical applications. By focusing on research efforts to improve the knowledge about nested dynamics of vertical network interactions, and particularly, the horizontal integration of key organ systems during exercise, NPE may enrich Basic Physiology and diverse fields like Exercise and Sports Physiology, Sports Medicine, Sports Rehabilitation, Sport Science or Training Science and improve the understanding of diverse exercise-related phenomena such as sports performance, fatigue, overtraining, or sport injuries.

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.

DNA Methylation Reorganization of Skeletal Muscle-Specific Genes in Response to Gestational Obesity.

The goals were to investigate in umbilical cord tissue if gestational obesity: (1) was associated with changes in DNA methylation of skeletal muscle-specific genes; (2) could modulate the co-methylation interactions among these genes. Additionally, we assessed the associations between DNA methylation levels and infant's variables at birth and at age 6. DNA methylation was measured in sixteen pregnant women [8-gestational obesity group; 8-control group] in umbilical cord using the Infinium Methylation EPIC Bead Chip microarray. Differentially methylated CpGs were identified with Beta Regression Models [false discovery rate (FDR) < 0.05 and an Odds Ratio > 1.5 or < 0.67]. DNA methylation interactions between CpGs of skeletal muscle-specific genes were studied using data from Pearson correlation matrices. In order to quantify the interactions within each network, the number of links was computed. This identification analysis reported 38 differential methylated CpGs within skeletal muscle-specific genes (comprising 4 categories: contractibility, structure, myokines, and myogenesis). Compared to control group, gestational obesity (1) promotes hypermethylation in highly methylated genes and hypomethylation in low methylated genes; (2) CpGs in regions close to transcription sites and with high CpG density are hypomethylated while regions distant to transcriptions sites and with low CpG density are hypermethylated; (3) diminishes the number of total interactions in the co-methylation network. Interestingly, the associations between infant's fasting glucose at age 6 and MYL6, MYH11, TNNT3, TPM2, CXCL2, and NCAM1 were still relevant after correcting for multiple testing. In conclusion, our study showed a complex interaction between gestational obesity and the epigenetic status of muscle-specific genes in umbilical cord tissue. Additionally, gestational obesity may alter the functional co-methylation connectivity of CpG within skeletal muscle-specific genes interactions, our results revealing an extensive reorganization of methylation in response to maternal overweight. Finally, changes in methylation levels of skeletal muscle specific genes may have persistent effects on the offspring of mothers with gestational obesity.

Principal component analysis as a novel approach for cardiorespiratory exercise testing evaluation.

OBJECTIVE: Our purpose was to apply a principal component analysis (PCA) approach to cardiorespiratory exercise to test evaluation and its sensitivity to workload accumulation. APPROACH: Twenty-five healthy young adults performed a progressive and maximal cycling test, which was divided into two parts: moderate and high workload intensities, using a ventilatory threshold as a cut point. A PCA of the time series of cardiovascular and respiratory variables was performed in each part and the number of principal components (PCs), the eigenvalues of the first PC (PC1), and the information entropy were calculated. MAIN RESULTS: The number of PCs increased, the eigenvalues of PC1 decreased (t = 5.32; p  < 0.001; d = 1.39) and entropy was significantly higher (Z = 3.10; p  = .002; d = 1.16) at high workload intensities, compared to moderate intensities. SIGNIFICANCE: Results showed the sensitivity of the PCA approach to workload accumulation and corroborates its potential for improving the evaluation and interpretation of cardiorespiratory exercise testing. In particular, it points to being a good candidate to objectively detect qualitative changes or thresholds.

Physiological- and performance-related effects of acute olive oil supplementation at moderate exercise intensity.

BACKGROUND: The consumption of olive oil is associated with a diminished risk of cardiovascular disorders and mortality, but the impact of olive oil supplementation on endurance performance is still unclear. Since the beneficial effects of olive oil are observed at a systemic level, its effectiveness may not be precisely measured through the commonly registered maximal and threshold values of some physiological and performance parameters. In contrast, we suggest evaluating it through variables able to capture the coordinated behaviour of physiological systems. Thus, the aim of the current research was to assess the effect of an acute extra virgin olive oil supplementation on cardiorespiratory coordination (CRC) and performance, compared to palm oil. METHODS: Three separate effort test sessions were carried out separated by 7-day interval. During each session, participants (n = 7) repeated the same progressive and maximal walking test, but under different dietary supplementations in a randomized order: (1) olive oil, (2) palm oil, and (3) placebo. A principal component (PC) analysis of selected cardiovascular and cardiorespiratory variables was carried out to evaluate CRC. Eigenvalues of the first PC (PC1) and the loadings of the cardiorespiratory variables onto PC1 were compared among dietary supplementations. In order to more accurately evaluate CRC, all the tests were divided into 3 equal sections, corresponding to low, moderate, and high exercise intensities, and the aforementioned procedure was repeated for each section in all the tests. RESULTS: Statistically significant differences were observed regarding PC1 eigenvalues among dietary supplementations (χ2 (8,2) = 6.3; p = .04), only at moderate intensity exercise. Specifically, PC1 eigenvalues were higher under olive oil compared to palm oil (2.63 ± 0.51 vs. 2.30 ± 0.28; Z = 2.03; p = .04; d = 0.80) and placebo supplementations (2.63 ± 0.51 vs. 2.38 ± 0.36; Z = 2.20; p = .03; d = 0.57). CONCLUSIONS: Supplementation with extra virgin olive oil increased CRC during a progressive walking test at moderate intensity, although did not change performance and other physiological markers. CRC analysis appears as a sensitive tool to investigate the physiological and performance effects of dietary supplementations.

Cardiorespiratory Coordination in Repeated Maximal Exercise.

Increases in cardiorespiratory coordination (CRC) after training with no differences in performance and physiological variables have recently been reported using a principal component analysis approach. However, no research has yet evaluated the short-term effects of exercise on CRC. The aim of this study was to delineate the behavior of CRC under different physiological initial conditions produced by repeated maximal exercises. Fifteen participants performed 2 consecutive graded and maximal cycling tests. Test 1 was performed without any previous exercise, and Test 2 6 min after Test 1. Both tests started at 0 W and the workload was increased by 25 W/min in males and 20 W/min in females, until they were not able to maintain the prescribed cycling frequency of 70 rpm for more than 5 consecutive seconds. A principal component (PC) analysis of selected cardiovascular and cardiorespiratory variables (expired fraction of O2, expired fraction of CO2, ventilation, systolic blood pressure, diastolic blood pressure, and heart rate) was performed to evaluate the CRC defined by the number of PCs in both tests. In order to quantify the degree of coordination, the information entropy was calculated and the eigenvalues of the first PC (PC1) were compared between tests. Although no significant differences were found between the tests with respect to the performed maximal workload (Wmax), maximal oxygen consumption (VO2 max), or ventilatory threshold (VT), an increase in the number of PCs and/or a decrease of eigenvalues of PC1 (t = 2.95; p = 0.01; d = 1.08) was found in Test 2 compared to Test 1. Moreover, entropy was significantly higher (Z = 2.33; p = 0.02; d = 1.43) in the last test. In conclusion, despite the fact that no significant differences were observed in the conventionally explored maximal performance and physiological variables (Wmax, VO2 max, and VT) between tests, a reduction of CRC was observed in Test 2. These results emphasize the interest of CRC evaluation in the assessment and interpretation of cardiorespiratory exercise testing.