J. S. Gomes, J. H. Oliveira, P. Bauer, L. Sousa, A. Sel, N. Cortes, J. R. Vaz
Ageing is associated with impaired gait adaptability, which leads to an increased fall risk in older adults. The study of the temporal structure of stride‐to‐stride fluctuations may help mitigate these inherent risks, as it has been proposed as a marker of locomotor functionality and motor control. However, the underlying mechanisms responsible for the progressive deterioration of stride‐to‐stride fluctuations in older adults are yet to be fully unravelled. Recent research suggests several central and peripheral factors can influence the walking adaptation process with the corticospinal tract playing a key role in motor control during gait. Thus, the purpose of this study was to investigate whether lower‐leg corticospinal drive significantly explains the temporal structure of gait stride-to-stride fluctuations. Thirty‐four older adults underwent transcranial magnetic stimulation (TMS) assessments of the tibialis anterior in one experimental session, where corticospinal excitability (CSE), silent period duration (SP), and short‐interval intracortical inhibition (SICI) were quantified. Immediately after the TMS intervention, they also performed a 12‐min treadmill walking trial at preferred walking speed, during which inter‐stride intervals were extracted and analysed using detrended fluctuation analysis to obtain the fractal scaling exponent (αISIs). Multiple linear regression analysis was used to examine whether CSE, SP and SICI predicted αISIs. The results of the linear regression model indicated that none of the corticospinal measures significantly predicted gait’s temporal dynamics (F(3,28) = 0.20, p = 0.896, R 2 = 0.021). These findings suggest that gait adaptability does not seem to be explained by corticospinal function, likely emerging from distributed, multilevel neural control processes involving spinal, supraspinal, and peripheral mechanisms rather than corticospinal contributions alone.
Arthur S. Bezerra, Robin Van Den Abeele, Bram Van Landeghem, Bjorn Verstraeten, Sebastiaan Lootens, Viktor Van Nieuwenhuize, Sander Hendrickx, Vincent F. M. Segers, Mattias Duytschaever, Nele Vandersickel
Atrial arrhythmias, notably atrial fibrillation (AF), exhibit complex spatiotemporal patterns that remain incompletely characterized. Based on topological constraints requiring counter-rotating reentries in two-dimensional manifolds, we present a framework classifying all atrial wavefronts into two fundamental archetypes: open and closed waves. Open waves are line-like structures bounded by endpoints that tend to self-perpetuate; closed waves are ring-like structures lacking endpoints that tend toward self-termination. We demonstrate that complex wavefront interactions reduce to five elementary processes: (1) Open wave creation, (2) Open wave annihilation, (3) Closed wave creation, (4) Closed wave annihilation and (5) Open wave collision. Validation within a cohort of 600 patient-specific AF simulations showed that all observed events adhered to these constructed topological rules, suggesting that complexity of fibrillatory conduction within the studied computational framework arises from simple underlying principles. Furthermore, closing all open waves, achieved a 100% success rate when electrical silence was used as the primary criteria for efficacy. This unified framework reconciles existing electrophysiological theories, including the multiple wavelet hypothesis, the mother rotor hypothesis, meandering rotors, and focal sources, while providing a foundation for optimizing clinical interventions.
Madhur Mangalam, Brian Schlattmann, Christopher Deans, Elizabeth Wellsandt
Unilateral hip osteoarthritis (HOA) reshapes whole-body movement, and total hip arthroplasty (THA) restores function only partially—but conventional kinematic analyses fall short of characterizing how the body’s distributed coordination reorganizes. Network analyses of inter-segment kinematic coupling offer a systems-level alternative, but they conventionally collapse the sign of coupling, treating two mechanically distinct relationships as equivalent: segments whose displacement amplitudes covary, rising and falling together, and segments whose amplitudes trade off, one displacing little while the other displaces a great deal. Here, we introduce a signed partial-correlation decomposition of marker-displacement coordination into parallel covarying (W +) and trading-off (W −) networks, applied to gait from 80 healthy adults and 106 HOA patients assessed before and 6 months after THA (ClinicalTrials.gov Identifier: NCT01907503). HOA reorganizes the two networks in opposite directions: covarying coordination loses modular structure and small-worldness, while trading-off coordination becomes more locally clustered and more small-world; global efficiency falls in both. This is consistent with pain-driven splinting that consolidates a few fixed trading-off configurations. Surgery acts predominantly on covarying coordination, partially restoring its topology, while the trading-off network’s reorganization persists across the six-month post-surgical window—and on one measure, i.e., how broadly each segment spreads its trading-off partners, a deficit emerges during recovery that was absent before surgery. A node-level sign-balance metric shows that the proportion of each segment’s coordination carried by covarying relationships returns to healthy values by 6 months, even though the underlying networks remain structurally altered. Standard post-surgical care thus restores the gross balance of coordination within 6 months, while the underlying architecture remains reorganized at that mid-recovery time-point—and, on at least one measure, consolidates further. Whether this reorganization reflects protective motor strategies, and whether training targeted at segmental differentiation would reverse it, are hypotheses that the present observational data raise but cannot test.
Philipp Bauer, João S. Gomes, Tiago Marques, Sandrina Lourenço, João H. Oliveira, Jamie Tallent, Nelson Cortes, João R. Vaz
Falls are a leading cause of injury, disability, and loss of independence in older adults, and are closely linked to age-related declines in neuromuscular function. Underlying these declines is a loss of physiological complexity, reflected in more predictable and repetitive temporal structures (i.e., decreased entropy) of motor output. Within a network physiology framework, this loss of complexity may manifest as reduced network dimensionality. It may also be consistent with an increased co-variation between motor outputs in different tasks. Therefore, the present study examined the relationship between the complexity of plantar flexor torque and gait in young and older adults. Thirty-eight healthy older adults and forty-six healthy young adults participated in a single laboratory session. Plantar flexor torque and gait were assessed in separate tasks: submaximal isometric contractions and continuous treadmill walking, respectively. Complexity was inferred from sample entropy, which quantifies the temporal structure of both signals. A positive Bayesian correlation between torque and gait complexity was observed in older adults (τ = 0.245, BF 10 = 3.985). In contrast, an absence of such correlation was found in young adults (τ = −0.079, BF 10 = 0.257). The Bayesian comparison of the two correlations revealed a stronger association between gait and torque in older adults compared to young adults (Δτ = 0.324, BF 10 = 3.456). These findings are consistent with, but do not directly demonstrate, an age-related loss of dimensionality in the neuromuscular network, in which motor outputs that vary independently in young adults co-vary in older adults. By identifying plantar-flexor torque complexity as a potential modifiable factor that is associated with gait complexity in older adults, these results motivate longitudinal work testing whether interventions that target torque control, such as resistance training, can elicit corresponding improvements in gait and thereby reduce fall risk.
Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality and is typically characterized by a terminal cascade of respiratory failure, cardiac arrhythmia, and cerebral suppression. Although epilepsy has long been regarded as a neuron-proprietary disorder, accumulating evidence indicates that glial cells, particularly astrocytes, play pivotal roles in both epileptogenesis and the progression to SUDEP. Astrocytes maintain neuronal homeostasis by regulating extracellular potassium through the inwardly rectifying potassium channel Kir4.1 and by clearing extracellular glutamate. Impairment of these homeostatic functions, together with reactive astrogliosis and the release of pro-inflammatory cytokines, including interleukin-1β and tumor necrosis factor-α, promotes neuronal hypersynchrony and lowers the seizure threshold. Severe hypoxia, a critical consequence in respiratory disturbance, sequentially activates microglia and astrocytes, thereby facilitating seizure generation and further depression of respiratory output. Furthermore, seizure propagation or spreading depolarization into brainstem respiratory centers, including the pre-Bötzinger complex and the nucleus tractus solitarius, may induce fatal central apnea or upper airway obstruction. Neuropathological evidence of neuronal and astrocytic loss in the ventrolateral medulla further suggests that chronic brainstem dysfunction increases susceptibility to respiratory failure. Experimental studies demonstrate that pharmacological inhibition of astrocytic activation delays hypoxia-induced seizures and respiratory arrest, highlighting astrocytes as a potential therapeutic target. A deeper understanding of neuron-glia interactions within the active neural milieu will facilitate the development of novel preventive strategies for SUDEP.
