The research team, led by Philipp Bauer and João R. Vaz of the Egas Moniz School of Health and Science in Portugal, together with collaborators at the University of Essex, George Mason University and Monash University, recruited 38 healthy older adults aged 60 to 87 and 46 healthy young adults aged 18 to 34. Each participant completed a single laboratory session involving two very different motor tasks: a stationary ankle-force test and twelve minutes of continuous treadmill walking at their preferred speed. The key question was whether the finesse with which the nervous system modulates force at the ankle is statistically linked to the finesse of the stepping pattern itself, and whether that link depends on age.

To measure finesse, the researchers turned to a nonlinear signal analysis tool called sample entropy. Unlike conventional statistics that summarize a signal with an average or a coefficient of variation, sample entropy quantifies the temporal structure of a time series: it estimates the inverse probability that short sequences of data points will repeat themselves across the record. A value approaching zero describes a highly predictable, almost mechanical signal, in which similar patterns recur relentlessly. A high value describes a signal so irregular that no pattern ever repeats. Neither extreme is healthy. The most capable physiological systems occupy a middle ground, balancing enough regularity to remain controlled with enough unpredictability to adapt flexibly to stress. The researchers note that this framework has precedent in cardiology, where reduced heart-rate entropy distinguishes patients with congestive heart failure from people with normal sinus rhythm.

In the force task, participants sat in a reclined isokinetic dynamometer with hip and knee flexed at 60 degrees, their dominant foot strapped to a locked lever arm. After maximal voluntary contractions established each person’s strength ceiling, they performed 30-second isometric pushes at 40 percent of their maximum, tracking a target line on a screen. The steady portion of the torque signal was down-sampled to 25 hertz and analyzed for entropy. In the walking task, heel strikes were detected from vertical ground reaction forces on an instrumented treadmill, and the intervals between consecutive heel strikes of the same foot were compiled into a stride-interval series, also scored for sample entropy. Crucially, the two tasks were performed separately, so any shared signal between them could not be a mechanical artifact of simultaneous measurement.

The results were striking in their asymmetry. Among older adults, torque entropy and gait entropy were positively correlated, with a Kendall’s tau of 0.245 and a Bayes factor of 3.985, indicating moderate evidence for the association. Among young adults, the correlation was essentially absent, at tau of −0.079 with a Bayes factor of 0.257, which itself constitutes moderate evidence for no link. A Bayesian comparison of the two correlations showed that the association was significantly stronger in the older group, with a difference in tau of 0.324 and a Bayes factor of 3.456. In plain terms: in youth, being good at modulating force tells you nothing about the texture of someone’s stride; in older age, the two seem to rise and fall together.

The authors interpret this through the lens of network physiology, a framework that views the organism as a web of interacting subsystems rather than a collection of isolated parts. In this view, healthy function is characterized by flexible, appropriately weighted interactions among components, and by high network dimensionality, meaning that many independent degrees of freedom are available for control. Aging, according to the framework, compresses this network: interactions become stronger and more rigid, and the effective number of dimensions shrinks. One measurable consequence is that motor outputs which once varied independently across individuals begin to co-vary. That is precisely the pattern the study observed. It is also consistent with recent work showing that aging produces a breakdown and stratification in networks of inter-muscular coordination, suggesting muscles that once operated with task-specific flexibility become locked into less adaptable configurations.

The researchers are careful about what the finding does and does not prove. Because torque and gait were measured in separate tasks, the study cannot demonstrate direct, time-resolved coupling between the force-producing and gait-controlling subsystems. Nor does the cross-sectional design establish causation: it remains possible that torque complexity causally shapes gait complexity, or that both are downstream of shared upstream factors such as motor unit discharge properties, neuronal loss, altered synaptic characteristics, or unmeasured variables like physical activity level and general health. The effect size itself is modest, and the credible intervals are wide, extending close to zero. The older cohort, with a mean age of 70.4, was relatively young and healthy, with a mean BMI within recommended ranges, which may mean the more dramatic network changes of advanced aging were not yet present. The achieved statistical power was roughly 74 percent, slightly below the targeted 80, and the treadmill setting may not generalize to overground walking in daily life.

Why does any of this matter? Because falls remain a leading cause of injury, disability and loss of independence in older adults, and gait entropy has emerged as a marker of fall vulnerability. As biological inputs to the locomotor system decline with age, stepping patterns become simplified and rigid, an overly regular system with impaired capacity to respond to the environment, whether that means a uneven curb, a slippery floor or a stumble. The ankle plantar flexors are central to this story: they stabilize the body and generate forward propulsion during stance, and their strength correlates with walking speed and with the ability to recover from a trip. Computational modeling suggests that it is not only the magnitude of ankle force but the temporal characteristics of the ankle response that determine whether a trip becomes a fall.

The most consequential implication is that torque complexity may be a modifiable factor. If the entropy of ankle force output and the entropy of gait genuinely co-vary in aging, then interventions that restore richness to force control, such as resistance training, might in principle ripple outward into more adaptable walking and lower fall risk. Testing that possibility requires longitudinal and interventional designs in which torque control is deliberately manipulated and gait entropy is tracked in parallel. The authors also point toward future studies using simultaneous signal acquisition and time-delay stability analysis to test whether the neuromuscular subsystems of older adults are truly over-synchronized, and toward clinical populations where the loss of network dimensionality is expected to be more advanced. Aging itself cannot be reversed, the researchers conclude, but its neuromuscular manifestations may be modifiable, and restoring complexity to the way the body generates force could be one of the levers worth pulling.

Subject of Research: Age-related covariation of plantar flexor torque complexity and gait complexity in neuromuscular aging

Article Title: Complexity of plantar flexor torque and gait covaries in older adults: a network physiology approach to neuromuscular aging

Article References: Bauer, P., Gomes, J. S., Marques, T., Lourenço, S., Oliveira, J. H., Tallent, J., Cortes, N., & Vaz, J. R. (2026). Complexity of plantar flexor torque and gait covaries in older adults: a network physiology approach to neuromuscular aging. Frontiers in Network Physiology, 6, Article 1947848. https://doi.org/10.3389/fnetp.2026.1947848

Image Credits: AI Generated

DOI: 10.3389/fnetp.2026.1947848

Keywords: neuromuscular aging, sample entropy, gait complexity, plantar flexor torque, network physiology, fall risk, motor control, nonlinear dynamics, resistance training, older adults, physiological complexity, Bayesian statistics

The study drew on the COmPLETE cohort, a cross-sectional investigation conducted at the University of Basel in Switzerland in collaboration with the Royal Brompton Hospital in London. All participants were free from cardiopulmonary disease, screened for active respiratory infection, and assessed with spirometry interpreted according to European Respiratory Society and American Thoracic Society guidelines using race-neutral Global Lung Initiative reference values. Each volunteer then completed a maximal cardiopulmonary exercise test on a cycle ergometer, with ventilation measured on a breath-by-breath basis and averaged over 10-second intervals. The cohort was remarkably balanced: women made up 52 percent of participants, body mass index averaged 23.7 kilograms per square meter, and lung function sat comfortably within normal limits, with predicted forced expiratory volume in one second at 107 percent and predicted forced vital capacity at 110 percent. In other words, these were genuinely healthy adults, not patients, which makes the age-related changes all the more telling.

The researchers framed their investigation around a growing appreciation in physiology that the irregularity, or complexity, of a biological signal can itself be a marker of health. In cardiology, reduced heart rate variability is a well-established signal of autonomic dysfunction and disease risk. But the application of entropy analysis to breathing during exercise has been far more limited. Sample entropy works by asking how predictable a time series is: a highly repetitive, regular pattern scores low, while a complex, irregular pattern scores high. The team calculated sample entropy for minute ventilation, breathing frequency, and tidal volume in every participant, using an embedding dimension of two and a tolerance coefficient of 0.2. Their initial hypothesis, modeled on the heart rate variability literature, was that aging would reduce ventilatory irregularity, constraining the breathing pattern in older adults. The data told a different story.

First, the conventional measures. As expected, exercise capacity declined steadily with age. Peak power output, peak oxygen uptake, peak minute ventilation, peak tidal volume, and peak breathing frequency all fell progressively across the decades, with correlations ranging from modest to strong. Peak oxygen uptake dropped from roughly 45 milliliters per kilogram per minute in the twenties to under 23 in the oldest group. But the striking finding was the shape of the change in breathing strategy. At the first ventilatory threshold, breathing frequency remained essentially flat across the entire age range, hovering around 20 to 22 breaths per minute regardless of whether a participant was 25 or 85. Yet the ratio of breathing frequency to minute ventilation traced a non-linear curve: stable from age 20 to about 55, then inflecting sharply upward. At peak exercise the same pattern emerged, with the frequency-to-ventilation ratio rising markedly in the 70-to-79 and 80-plus decades, indicating a shift toward a tachypneic, or rapid-and-shallow, breathing strategy.

This shift makes mechanical sense. Healthy aging is associated with loss of lung elastic recoil, stiffening of the chest wall, reduced respiratory muscle strength, and declining tidal volumes relative to lung capacity. As the lungs lose their spring, breathing deep becomes expensive. Older adults compensate by breathing more often rather than more deeply, achieving the required ventilation through frequency rather than depth. The study found that the tidal volume to forced vital capacity ratio rose with age at both threshold and peak exercise, confirming that older breathers were working closer to their volumetric limits. Age and peak breathing frequency emerged as independent predictors of ventilatory reserve utilization, the percentage of estimated maximal voluntary ventilation consumed during exercise. Meanwhile ventilatory efficiency deteriorated, with the ventilatory equivalent for carbon dioxide nadir climbing from 24 in the youngest group to 32 in those over 80, meaning older adults had to move substantially more air to eliminate the same amount of carbon dioxide.

Then came the entropy results, which overturned the researchers’ expectations. After adjusting for sex, body mass index, peak oxygen uptake, forced expiratory volume in one second, and exercise duration, generalized additive models revealed a non-linear relationship between age and ventilatory sample entropy across all three signals. Entropy values held steady through early and middle adulthood, then climbed progressively from approximately age 60 onward. The pattern appeared in minute ventilation entropy, tidal volume entropy, and breathing frequency entropy, with the models for minute ventilation explaining just over a quarter of the deviance. Far from becoming more rigid and predictable, the breathing of older adults became demonstrably more chaotic during exercise. The team had hypothesized a decline in irregularity with age, mirroring the well-documented decline in heart rate variability, and the opposite occurred.

The authors offer several plausible mechanisms, while cautioning that the observational design cannot settle the question definitively. One possibility is altered central respiratory drive or impaired integration of afferent feedback within the brainstem, a form of neural dedifferentiation consistent with the broader concept of loss of physiological complexity in aging. Elevated entropy has previously been documented in dysfunctional breathing and in post-COVID unexplained breathlessness, conditions where patients report exertional breathlessness without any underlying cardiorespiratory pathology. Intriguingly, the age-related rise in entropy coincides with the period when around a quarter of people over 65 report breathlessness in the absence of diagnosed disease. The stability of breathing frequency at the first ventilatory threshold suggests that at submaximal intensities, age-related mechanical constraints have not yet compromised ventilation; the irregularity and tachypneic shift become evident only as exercise intensity climbs into higher domains. Sex differences added another layer: males showed higher minute ventilation entropy than females, possibly because larger lung volumes and airway dimensions in males produce a broader, less constrained ventilatory response that registers as a more irregular time series.

The study also connected ventilatory irregularity to fitness. In secondary analyses, higher peak oxygen uptake was associated with lower sample entropy across all three ventilatory signals, and peak oxygen uptake was the primary determinant of minute ventilation and frequency entropy in models adjusted for age and body mass index. The authors are careful to note that this may reflect shared age-related influences rather than a direct mechanistic relationship, since cardiorespiratory fitness declines steadily after the fifth decade, roughly the same point at which entropy begins its ascent. Still, the possibility that fitness protects the fine-grained organization of breathing control is a tantalizing lead. The findings also fit into a developmental arc suggested by prior work in children and adolescents, where entropy values decline during maturation, indicating increasing refinement of respiratory control. Taken together, these studies sketch a lifespan trajectory in which breathing control is refined through childhood and adolescence, stabilizes through adulthood, and then de-differentiates in later life, echoing patterns observed in frailty research across multiple physiological systems.

Limitations are candidly acknowledged. The analysis was retrospective and cross-sectional, so longitudinal data would be needed to track how individual breathing patterns evolve with age. All testing occurred at a single Swiss center in a predominantly Caucasian cohort, which limits generalizability, and no perceptual breathlessness ratings such as Borg scale scores were collected, preventing a direct link between entropy and symptom intensity in this cohort. The use of estimated rather than directly measured maximal voluntary ventilation is a further caveat, though the two are strongly correlated in healthy people. Crucially, the proportion of the exercise test spent above the first ventilatory threshold was comparable across all age decades, between 52 and 54 percent, suggesting that differences in relative exercise intensity did not confound the entropy findings. The authors also provide normative entropy values across the age span, a reference standard intended to anchor future studies of breathlessness in older adults.

The bigger picture is compelling: the study demonstrates that the aged respiratory system is forced into a mechanically inefficient, frequency-dominant pattern accompanied by rising signal irregularity, a kind of neuromechanical dissociation that may underpin the heightened perception of breathlessness so commonly reported with healthy aging. Because breathing frequency tracks perceived exertion closely, the tachypneic shift documented here provides a physiological bridge between the aging lung and the everyday experience of getting winded. Future prospective studies correlating entropy with breathlessness scores, and longitudinal designs tracking entropy within individuals over time, will be needed to convert these cross-sectional patterns into clinical insight. But the message already resonates: aging does not simply dim the respiratory system, it rewires its control, and the mathematical fingerprint of that rewiring becomes visible somewhere around our sixtieth birthday.

Subject of Research: Age-related changes in ventilatory pattern and irregularity during exercise in healthy adults

Article Title: The ventilatory response pattern to exercise across the age‐span in healthy adults

Article References: Williams, Z. J., Cenerini, G., Schwendinger, F., Knaier, R., Wagner, J., Hull, J. H., & Schmidt‐Trucksäss, A. (2026). The ventilatory response pattern to exercise across the age‐span in healthy adults. Physiological Reports, 14(17), Article e71065. https://doi.org/10.14814/phy2.71065

Image Credits: AI Generated

DOI: 10.14814/phy2.71065

Keywords: healthy aging, ventilatory response, sample entropy, cardiopulmonary exercise testing, breathing frequency, tidal volume, exertional breathlessness, respiratory mechanics, physiological complexity, cardiorespiratory fitness, ventilatory threshold, COmPLETE study