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        <title>Frontiers in Network Physiology | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/network-physiology</link>
        <description>RSS Feed for Frontiers in Network Physiology | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-10-29T17:04:18.191+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1745246</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1745246</link>
        <title><![CDATA[Exercise monitoring from a Network Physiology approach]]></title>
        <pubdate>2026-10-29T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Lluc Montull</author><author>Sergi Garcia-Retortillo</author><author>Óscar Abenza</author><author>Yaopeng J. X. Ma</author><author>Robert Hristovski</author><author>Plamen Ch. Ivanov</author><author>Natàlia Balagué</author>
        <description><![CDATA[Advancements in big data, artificial intelligence and related technology are shaping the future of exercise monitoring, yet current monitoring strategies may not fully capture the physiological complexity of athletes’ health and performance. The multidisciplinary field of Network Physiology provides a conceptual and analytical framework to investigate the dynamic interactions, coordination and network integration among physiological systems in athletes during exercise, and thus, opens new directions in Exercise Physiology. This article aims to summarize the current advances, vision and perspectives within this framework, focusing on how investigations of the inter-organ dynamic networks (cardio-respiratory, cardio-muscular, cortico-cardiac, cortico-muscular, inter-muscular, etc.) can lead to valuable insights into athletes’ performance, exercise monitoring, the underlying regulatory mechanisms of systems adaptation and coordination in response to exercise-induced stress, and to identify a novel class of network-based biomarkers related to training, levels of fitness, fatigue, and recovery.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1970105</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1970105</link>
        <title><![CDATA[Metabolomic signatures associated with muscle dysfunction during the SIRIUS-21 space analog mission]]></title>
        <pubdate>2026-10-26T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Adel B. Elmoselhi</author><author>Catherine Taylor</author><author>Vishwajeet Shankhwar</author><author>Andrew Blaber</author><author>Zeinab Ibrahim</author><author>Hamza M. Al-Hroub</author><author>Nelson C. Soares</author><author>Nandu Goswami</author>
        <description><![CDATA[IntroductionThere is growing interest in exploring outer space to expand scientific knowledge and access valuable material resources. However, progress is limited by the harsh space environment, including microgravity, ionizing radiation, isolation and confinement (IC), disrupted circadian rhythms, and nutritional challenges. These stressors contribute to health problems across multiple organ systems, particularly the musculoskeletal, immune, renal/urinary, and cardiovascular systems. Although we have extensive insight into skeletal muscle pathophysiological changes induced by these spaceflight-related stressors, the molecular mechanisms underlying functional alterations caused by prolonged IC in skeletal muscle remain incompletely understood.MethodsDuring the 8-month SIRIUS-21 space analog mission, five participants (3 males, 2 females) underwent plasma and saliva sampling and electromyography (EMG) assessment at five time points: baseline (Ingress), early, mid, and late isolation and confinement (IC), and 14 days post-mission (Egress). Metabolites were analyzed by LC-MS/MS. Longitudinal metabolite changes were assessed using repeated-measures ANOVA with Tukey HSD post hoc testing, and direct metabolite-EMG relationships were explored using Spearman rank correlations.ResultsMetabolomic profiling identified 45 skeletal muscle-related metabolites with nominally significant longitudinal changes (p < 0.0001–0.05): 8 were detected in both plasma and saliva, 26 only in plasma, and 11 only in saliva. Direct exploratory Spearman correlations with EMG metrics were identified for a subset of metabolites, including pipecolic acid, phenylacetic acid, L-phenylalanine, L-acetylcarnitine, L-glutamine, and pyruvaldehyde. EMG findings showed a progressive decline in muscle activation and fatigue resistance during prolonged IC, with partial recovery after egress. Exploratory sex-related analyses were interpreted descriptively because the cohort included only two females and three males.ConclusionProlonged IC was accompanied by coordinated changes in muscle function and circulating or salivary metabolites. The identified metabolites represent candidate metabolic signatures associated with muscle dysfunction and require validation in larger independent cohorts before diagnostic or therapeutic utility can be established.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1945351</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1945351</link>
        <title><![CDATA[Impact of low-voltage area burden and topological obstacles on atrial fibrillation recurrence after pulmonary vein antrum isolation]]></title>
        <pubdate>2026-10-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>JungMin Choi</author><author>Young-Hae Go</author><author>Soonil Kwon</author><author>Kyung-Yeon Lee</author><author>Hyo-Jeong Ahn</author><author>So-Ryoung Lee</author><author>Taehun Kim</author><author>Jung Chan Lee</author><author>Eue-Keun Choi</author><author>Seil Oh</author>
        <description><![CDATA[BackgroundTopological obstacles (TOs), electrically isolated regions such as the mitral annulus and atrial scars, can provide reentry circuits in the left atrium. Their quantity and relationship with low-voltage area (LVA) burden may influence recurrent atrial fibrillation (AF), but this impact remains poorly understood. We aimed to investigate the association between TO count, LVA burden, and post-ablation AF recurrence in patients undergoing de novo AF ablation.MethodsPatients were categorized by TO counts, identified using pulmonary vein antrum isolation lines and voltage maps. LVA burden (<0.5 mV) was quantified and grouped into quartiles. One-year AF/atrial tachycardia (AT) recurrence was evaluated across groups.ResultsAmong 237 patients (mean age 62.4 ± 8.8 years; 27.0% female, paroxysmal AF 42.6%, follow-up 1.0 ± 0. years), the majority had an intermediate TO count (TO = 3, 75.9%). Patients with the lowest TO count (TO = 1, 5.5%) were significantly older, had higher CHA2DS2-VASc scores, worse echocardiographic parameters, and the highest mean LVA burden (36.6% ± 24.8%). AF/AT recurrence occurred in 35.4% of patients. Although recurrence rates were numerically higher in patients with extreme TO counts (TO = 1 or ≥4) and lower in those with intermediate counts (TO = 2 or 3), these differences were not statistically significant (p = 0.433), and the TO group remained non-significantly associated with recurrence after multivariable adjustment for age, AF clinical type, left atrial diameter, left ventricular ejection fraction, CHA2DS2-VASc score, and LVA burden. TO counts differed significantly across LVA burden quartiles (p < 0.001), with the greatest variation observed in the group with the highest LVA burden. Dominant frequency and organization index showed no significant intergroup differences.ConclusionPatients with extreme TO counts (TO = 1 or ≥4) showed a numerically higher, although not statistically significant, trend toward post-ablation recurrence compared with those with intermediate counts. TO quantity varied significantly with LVA burden, suggesting that atrial substrate heterogeneity may influence AF recurrence patterns.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1894335</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1894335</link>
        <title><![CDATA[Investigating cardiorespiratory fitness, cerebral blood flow, and brain metabolism in epilepsy]]></title>
        <pubdate>2026-10-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yun Lien</author><author>Brandon S. Mitchell</author><author>Jerzy P. Szaflarski</author><author>Lawrence Ver Hoef</author><author>Thomas W. Buford</author><author>Adam M. Goodman</author><author>William R. Willoughby</author><author>Charity J. Morgan</author><author>Anna Moyana</author><author>Jennifer Pilkington</author><author>Amy R. August</author><author>Joshua T. Bennett</author><author>Jane B. Allendorfer</author>
        <description><![CDATA[IntroductionIdiopathic generalized epilepsies (IGEs) are characterized by seizures that propagate through widespread thalamocortical networks including the anterior cingulate cortex (ACC). Poor cardiorespiratory fitness may exacerbate neurovascular and metabolic vulnerability including heightened susceptibility to sudden unexpected death in epilepsy. We aimed to examine cardiorespiratory fitness, regional cerebral blood flow (CBF), and metabolite concentrations in patients with IGEs (PwIGEs) and to determine the effect of seizure control status on these physiological and neurochemical measures.MethodsForty-six participants (31 PwIGEs, 15 healthy controls) underwent a graded exercise test to assess maximal oxygen uptake (VO2peak) as a measure of cardiorespiratory fitness and completed 3T MRI including multi-delayed pseudo-continuous arterial spin labeling (pCASL) to assess CBF and single-voxel spectroscopy (SVS) to assess ratios of N-acetylaspartate and glutamate/glutamine complex to total creatine (NAA/tCr and Glx/tCr, respectively) in the ACC and thalamus. Group differences and seizure control effects in PwIGEs were examined using analysis of covariance (ANCOVA).ResultsVO2peak, thalamic CBF, ACC NAA/tCr, and ACC Glx/tCr did not significantly differ between groups. PwIGEs exhibited higher ACC CBF (p = 0.039) and lower thalamic NAA/tCr (p = 0.012) than healthy controls. PwIGEs with active seizures showed significantly lower thalamic Glx/tCr compared to those who were seizure-free (p = 0.003).DiscussionThese findings suggest poor cardiorespiratory fitness is not epilepsy-specific and likely attributable to lifestyle and that region-specific alterations in perfusion and metabolic milieu in PwIGEs characterized by higher ACC CBF and lower thalamic NAA/tCr and Glx/tCr in those with active seizures. The multimodal neuroimaging approach provides convergent evidence of thalamocortical network dysregulation underlying IGE pathophysiology.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1913383</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1913383</link>
        <title><![CDATA[Acute cardiovascular responses to slow and deep breathing in normotensive non-pregnant and pregnant women]]></title>
        <pubdate>2026-10-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Malika Felton</author><author>Stephanie Grigsby</author><author>Vanora A. Hundley</author>
        <description><![CDATA[ObjectiveTo compare the acute cardiovascular responses of non-pregnant and pregnant women to slow and deep breathing (SDB) at a range of breathing frequencies. Participants: Forty-one women (23 non-pregnant and 18 pregnant).MethodsParticipants completed five different breathing conditions in a randomised order (5-min duration); spontaneous breathing (Sfr), dynamic SDB breathing frequency (Dfr), and three fixed breathing frequencies of 4 breaths. min−1 (4Ffr), 6 breaths. min−1 (6Ffr), and 8 breaths. min−1 (8Ffr). Main Outcome Measures: Non-invasive beat-to-beat arterial blood pressure, heart rate and respired airflow were monitored continuously.ResultsThe maximum amplitude of respiratory sinus arrhythmia (RSA) during SDB was 2.1 times higher than during spontaneous breathing (Sfr) for both groups, maximising at 6 breaths. min−1 (0.25s ± 0.1 non-pregnant, 0.15s ± 0.1 pregnant). Although absolute RSA was significantly lower in pregnant women during spontaneous breathing (Sfr; 0.07s vs. 0.12s non-pregnant), SDB increased RSA to the same level as non-pregnant women’s spontaneous breathing levels. In both groups, the amplitude of blood pressure oscillations (both systolic and diastolic blood pressure) increased as breathing frequency declined, reaching a peak at 4 breaths. min−1 (4Ffr), which was up to 4.5 times higher (14.3%, 10 mmHg) than during spontaneous breathing (Sfr).ConclusionCardiovascular responses maximised at ≤6 breaths. min−1 and acute haemodynamic responses to SDB are similar in pregnant and non-pregnant women, despite absolute differences under spontaneous breathing conditions. If blood pressure oscillations underpin the anti-hypertensive effect of SDB, the data indicate that these can be amplified in pregnant women at frequencies between 4 and 6 breaths. min−1.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1966953</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1966953</link>
        <title><![CDATA[Integrating polyspikes and excitability markers for epileptic network identification]]></title>
        <pubdate>2026-10-14T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>James E. Niemeyer</author><author>Benjamin L. Barnes</author><author>Nitish Seenarine</author><author>Meritxell Sainz Barrionuevo</author><author>Theodore H. Schwartz</author>
        <description><![CDATA[Epilepsy is increasingly recognized as a disorder of distributed brain networks rather than a disease arising from a single seizure focus. Although clinical practice remains centered on localization of the seizure onset zone (SOZ), persistent seizures following apparently successful resection suggest that epileptogenic activity is often supported by broader networks of interconnected regions. A major challenge for both surgical and neuromodulatory treatment is identifying not only where seizures occur, but also which connected brain structures are components of a network that may underlie the generation of seizures. Here, we propose network excitability mapping as a translational framework for characterizing epileptic networks. In this view, epileptic networks can be described along two complementary dimensions: 1) local excitability and 2) network recruitment. We highlight evidence that the aperiodic (1/f) slope of field-potential recordings provides a mechanistically grounded measure of local excitability, while polyspike structure can reflect the degree to which epileptiform activity recruits distributed network nodes. Recent studies, and preliminary data presented here, combining electrophysiology, calcium imaging, and computational modeling suggest that these measures capture distinct but related aspects of epileptic network function. Together, these approaches support a shift from SOZ-based paradigms toward functional mapping of epileptic networks. We argue that combining measures of excitability and recruitment may enable construction of individualized excitability maps capable of informing surgical planning, optimizing neurostimulation, and improving seizure control. Establishing translational biomarkers of network engagement will be critical for advancing precision therapies in epilepsy.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1961712</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1961712</link>
        <title><![CDATA[Regulatory capacity is not a scalar: metrics, perturbations, and viability in network physiology]]></title>
        <pubdate>2026-10-13T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Lori Hogenkamp</author>
        <description><![CDATA[Biological regulatory capacity is commonly represented by a scalar: a summed biomarker index, standardized composite, risk count, or single recovery parameter. Such measures can be useful, but they do not identify capacity independently of the conditions under which they are constructed. This article argues that regulatory capacity is not an intrinsic scalar property of an organism. It is a conditional relation among the architecture and current state of a regulatory system, the perturbations that reach it, the metric or cost functional used to evaluate its response, the viability criterion, and the time horizon. Near an operating state, systems with identical eigenvalue spectra can incur different integrated burdens and reverse their apparent ranking when the perturbation channel or burden metric changes. For a declared quadratic burden in a stable local linearization, the observability Gramian associated with a virtual cost output represents accumulated weighted recovery burden, and the measurement map, burden-evaluation map, and latent state representation must be distinguished. For network physiology, allostasis, and allostatic-load measurement, routine choices about biomarkers, scaling, thresholds, and challenge paradigms are therefore constitutive assumptions rather than neutral preprocessing. Biological adaptation is likewise not equated with stability, compensation, recovery, or continued viability: it is indexed to a specified level of organization, protected function, reference or counterfactual, time horizon, and outcome or cost criterion. Regulatory Bandwidth is developed as a conditional perturbation-response profile rather than a universal scalar. Its contribution is a measurement architecture that requires the regulatory system, perturbation ecology, burden criterion, viability endpoint, and horizon to be declared before scalarization. The primary falsifiable comparison is between a flexible scalar-capacity model, which predicts one preserved ordering across declared perturbation classes, and a conditional-profile model tested on held-out sessions, contexts, or perturbations. Rejection of the scalar model supports conditional structure without establishing architectural heterogeneity, which requires a further shared-architecture comparison; this distinction bears directly on neurodiversity and person-environment fit. A worked orthostatic-challenge specification shows how measured outputs, constructed burden, viability, measurement error, and mechanistic interpretation can be separated in practice. The framework preserves the usefulness of scalar summaries while restricting the claims they can support.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1946459</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1946459</link>
        <title><![CDATA[Corticospinal function does not predict stride-to-stride gait dynamics in older adults]]></title>
        <pubdate>2026-10-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>J. S. Gomes</author><author>J. H. Oliveira</author><author>P. Bauer</author><author>L. Sousa</author><author>A. Sel</author><author>N. Cortes</author><author>J. R. Vaz</author>
        <description><![CDATA[IntroductionAgeing 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.MethodsThirty‐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.ResultsThe 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, R2 = 0.021).DiscussionThese 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.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1940428</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1940428</link>
        <title><![CDATA[Open wavefront ablation terminates rotor-driven atrial fibrillation]]></title>
        <pubdate>2026-10-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Arthur S. Bezerra</author><author>Robin Van Den Abeele</author><author>Bram Van Landeghem</author><author>Bjorn Verstraeten</author><author>Sebastiaan Lootens</author><author>Viktor Van Nieuwenhuize</author><author>Sander Hendrickx</author><author>Vincent F. M. Segers</author><author>Mattias Duytschaever</author><author>Nele Vandersickel</author>
        <description><![CDATA[IntroductionAtrial 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.Methods and ResultsWe 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.DiscussionThis 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.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1947848</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1947848</link>
        <title><![CDATA[Complexity of plantar flexor torque and gait covaries in older adults: a network physiology approach to neuromuscular aging]]></title>
        <pubdate>2026-10-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Philipp Bauer</author><author>João S. Gomes</author><author>Tiago Marques</author><author>Sandrina Lourenço</author><author>João H. Oliveira</author><author>Jamie Tallent</author><author>Nelson Cortes</author><author>João R. Vaz</author>
        <description><![CDATA[IntroductionFalls 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.MethodsThirty-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.ResultsA positive Bayesian correlation between torque and gait complexity was observed in older adults (τ = 0.245, BF10 = 3.985). In contrast, an absence of such correlation was found in young adults (τ = −0.079, BF10 = 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, BF10 = 3.456).DiscussionThese 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.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1916345</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1916345</link>
        <title><![CDATA[Network analysis reveals that total hip arthroplasty restores shared segmental motion before segmental differentiation]]></title>
        <pubdate>2026-10-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Madhur Mangalam</author><author>Brian Schlattmann</author><author>Christopher Deans</author><author>Elizabeth Wellsandt</author>
        <description><![CDATA[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.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1955271</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1955271</link>
        <title><![CDATA[Astrocytes at the interface of peri-ictal breathing dysfunction and SUDEP]]></title>
        <pubdate>2026-10-01T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Isato Fukushi</author><author>Isamu Ozaki</author><author>Mieczyslaw Pokorski</author><author>Yasumasa Okada</author>
        <description><![CDATA[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.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1967461</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1967461</link>
        <title><![CDATA[Bioenergetic impedance: a network physiology framework for stress adaptation, maladaptation, and recovery]]></title>
        <pubdate>2026-09-29T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Torsak Tippairote</author><author>Pruettithada Hoonkaew</author>
        <description><![CDATA[Stress adaptation depends not only on challenge magnitude but on the capacity of physiological systems to conduct, transform, buffer, and recover energetic demands. We propose bioenergetic impedance as a Network Physiology construct describing the time-dependent constraint on energetic throughput and recovery that arises when energetic pressure exceeds available biological capacity. Resistance, delay, congestion, and buffering burden may reflect mechanisms or manifestations of this mismatch, whereas compensatory rerouting may represent an adaptive response to constrained throughput. At the cellular level, substrate congestion and redox backpressure provide plausible mechanistic anchors, while metabolic rerouting and mitochondrial stress signaling may represent compensatory or signaling responses through which local energetic constraints may be accommodated or communicated. Their physiological consequence depends critically on reversibility. In adaptive impedance cycling, challenges that transiently exceed available capacity produce impedance followed by recovery, restoration or adaptive recalibration of flexible cross-system organization, and potentially expanded reserve. In impedance lock-in, repeated or unresolved challenge produces incomplete recovery, persistent residual constraint, compensatory allocation, reduced network flexibility, and constrained adaptive reserve. The framework therefore places recovery dynamics at the center of resilience and generates a testable prediction: adaptive states should show temporary, context-appropriate reconfiguration of cross-system interactions followed by restoration of flexible network organization, whereas maladaptive states should show incomplete recovery and persistent or functionally inappropriate network reconfiguration. Bioenergetic impedance thus provides a systems-level framework linking cellular energetic constraints with stress adaptation, maladaptation, and recovery across physiological networks.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1881914</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1881914</link>
        <title><![CDATA[Brain-heart coupling in tourette syndrome: a precision functional mapping study of discordant siblings]]></title>
        <pubdate>2026-09-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sana A. Ali</author><author>Damion V. Demeter</author><author>Abigail R. Baim</author><author>Jonathan Ahern</author><author>J. H. Ben Ahn</author><author>Sarah E. Chang</author><author>Emily M. Koithan</author><author>Sujin Park</author><author>Benjamin L. Smarr</author><author>Deanna J. Greene</author>
        <description><![CDATA[Tourette syndrome (TS) is a neurodevelopmental disorder characterized by motor and vocal tics that are modulated by internal physiological state and interoceptive state, including premonitory urges and associated changes in short-timescale parasympathetic variability. Since tic expression is thought to be linked to fluctuations in autonomic state, understanding how brain networks integrate physiological signals may provide insight into the neural mechanisms contributing to tic generation and suppression. In recent years, there has been increasing interest in understanding interactions between the brain and autonomic physiology, given their shared central role in shaping cognition, emotion, and behavior. Methodological advances have enabled the study of brain–heart coupling, yet much of this work has focused on static or region-based approaches, limiting insight into how autonomic fluctuations are integrated within dynamic, large-scale brain networks. Here, we examined time-resolved brain-heart interactions using densely sampled resting-state fMRI data and concurrent pulse oximetry in two sibling pairs (n = 4) discordant for Tourette syndrome (TS). Using two targeted network analyses organized around interoceptive/urge awareness and inhibitory control/action regulation processes, we quantified coupling between pulse-derived RMSSD and between-network functional connectivity using sliding-window analyses and Bayesian linear mixed-effects models. We observed marked individual variability in functional network organization and autonomic measures. The most consistent observation was a pattern of opposing coupling directions between individuals with and without TS: those with TS showed positive associations between pulse-derived RMSSD with connectivity between internal-state and attentional networks, as well as among action-related systems, while unaffected siblings showed positive associations along broader integrative pathways linking internal-state and action-control networks. These preliminary findings generate hypotheses regarding individualized patterns of brain-heart coupling in TS and illustrate the potential value of integrating individualized network mapping with time-resolved physiological measures in clinical populations.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1913737</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1913737</link>
        <title><![CDATA[Informational stress in cognitive systems: a review and conceptual synthesis]]></title>
        <pubdate>2026-09-21T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Elina Asriyan</author><author>Ruben Gevorgyan</author>
        <description><![CDATA[Modern cognitive environments expose individuals to sustained streams of information that may be complex, uncertain, rapidly changing, or emotionally salient. Such environments can support learning and decision-making but may also require continuing regulation of attention, effort, and information selection. This narrative review examines informational stress as a process-level perspective on the conditions under which sustained informational demands may become stress-related. Drawing on stress appraisal and allostasis, attention and cognitive load, compensatory control, information theory, rational inattention, resource rationality, scarcity, deliberate ignorance, and critical ignoring, we distinguish informational demand from the stress-related response it may generate. Informational stress is defined here as a regulatory process that may arise when sustained informational demands are appraised as taxing and require continued adjustment beyond routine processing. We distinguish this process from information overload, cognitive load, mental fatigue, and specific strategies of selective non-processing. We also outline an operational approach linking structural properties of informational input with appraisal, regulatory responses, behavioral and physiological outcomes, and recovery over time. The perspective is intended as a testable conceptual synthesis rather than a unified theory, and its value depends on demonstrating explanatory contribution beyond established accounts of cognitive demand and regulation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1930617</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1930617</link>
        <title><![CDATA[Robust information transfer calculation reveals dynamic networks during sleep arousal]]></title>
        <pubdate>2026-09-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Richard Hohmuth</author><author>Jakob J. Müller</author><author>Hagen Malberg</author><author>Martin Schmidt</author>
        <description><![CDATA[Understanding the influence of cardiovascular diseases (CVD) on human regulatory functions is a major challenge in modern healthcare. This study explores whether the autonomic response to sleep arousals can serve as a diagnostic marker of the health of physiological networks. We introduce a novel method for the robust calculation of information transfer, based on the optimization of embedding parameters for transfer entropy (TE) calculation. Using this approach, we analyzed the information transfer dynamics of 8,136 sleep arousals from 1,956 subjects from the SHHS follow-up visit. Compared to three state-of-the-art approaches, our newly introduced method, max. TE, achieved a 17.9% more stable TE estimate than the second-best approach. Our results indicate a significantly (p<0.001) lower TE in patients with CVD (85.4±0.8 mnats) than that in healthy controls (87.9±0.5 mnats), indicating an impairment of regulatory control mechanisms. Furthermore, the TE decreases linearly with increasing age and shows significant differences between sleep stages, with the highest TE occurring during REM sleep (p<0.001). These findings demonstrate that sleep arousals, as a physiological stimulus, can reveal sleep stage- and disease-related changes in cardiovascular networks and that our approach provides a robust group-level embedding strategy for physiological information-transfer analysis.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1973521</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1973521</link>
        <title><![CDATA[Editorial: The network theory of epilepsy at twenty]]></title>
        <pubdate>2026-09-15T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Hitten P. Zaveri</author><author>Klaus Lehnertz</author><author>Dennis D. Spencer</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1895622</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1895622</link>
        <title><![CDATA[“Stand by me”: astrocyte–microglia crosstalk in central nervous system development, homeostasis, injury, and disease]]></title>
        <pubdate>2026-09-15T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Alberto Javier Ramos</author><author>Alejandro Villarreal</author>
        <description><![CDATA[During central nervous system (CNS) development, astrocytes and microglia arise from distinct embryonic origins; however, during early development, both cell types coordinately participate in brain circuit formation and neuronal network establishment. Later, in the healthy adult CNS, astrocytes are known to play essential roles in maintaining homeostasis. Although the microglia primarily function as the resident immune cells of the CNS, it is now well established that these cells, together with the astrocytes, participate actively in synaptic regulation, neuronal circuitry functioning, and cognition. In response to acute injury or chronic disease, both cell types undergo profound phenotypic changes and engage in a dynamic bidirectional crosstalk that critically shapes neuroinflammatory responses and influences CNS damage progression. This review synthesizes current knowledge and provides updated insights into the mechanisms by which astrocytes and microglia communicate during embryonic development of the CNS, participate in network physiology in the adult CNS, and engage in cellular responses to disease, highlighting how their interactions contribute to pathology and enabling identification of potential avenues for therapeutic interventions. Specifically, we focused on reviewing articles that directly address astrocyte–microglia communication. As an interesting outcome of our literature survey, we identified a significant bias toward studies investigating astrocyte–microglia crosstalk in pathological contexts compared to development and healthy adulthood. This observation reveals underexplored research avenues and emphasizes the need for studies addressing the roles of astrocyte–microglia interactions during physiological development and adult homeostasis. Finally, we briefly review novel approaches to overcome the difficulties of addressing astrocyte–microglia crosstalk.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1842320</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1842320</link>
        <title><![CDATA[The nephron arterial network and its interactions: nonlinear and information theoretic analyses]]></title>
        <pubdate>2026-09-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Donald J. Marsh</author><author>Niels-Henrik Holstein-Rathlou</author>
        <description><![CDATA[Nephrons receive blood from a tree-shaped network of arteries and arterioles and regulate demand by actions that affect the diameters of their afferent arterioles. The network structure is asymmetric. The flow of blood requires a gradient of hydrostatic pressure so that the blood pressure at the origins of different afferent arterioles must differ from each other. Nephron mechanisms that act on afferent arterioles include a myogenic mechanism, a common feature of smooth muscle cells throughout the body, and tubuloglomerular feedback (TGF), a negative feedback mechanism that senses concentrations of common electrolytes in tubular fluid as it passes from the thick ascending limb into the distal tubule. The myogenic mechanism generates an autonomous oscillation in the electrical potential difference of the plasma membrane. The TGF signal also oscillates, albeit at a lower frequency, and modulates the frequency and amplitude of the myogenic mechanism’s potential difference oscillation. The interaction of TGF with the myogenic mechanism generates a bimodal electrical signal that enters the adjacent arterial segment. The arterial segments of the network are electrically conductive, providing a channel for nephrons to interact with each other. In addition, the oscillation of nephron blood flow caused by the myogenic-TGF interaction leads to changes in local arterial blood pressure, providing a hemodynamic interaction among nephrons. We developed a mathematical model that incorporates these features. The model demonstrates renal autoregulation and the oscillations in tubular fluid flow and pressure found in experiments. The results illustrate the effects of interactions on the network. In this paper we estimate Lyapunov exponents to establish the dynamic state of each nephron, and mutual information to provide quantitative evaluations of the importance of each of the information streams on nephron dynamics. The results indicate that all nephrons operate in a state of weak chaotic dynamics and that electrical signaling through the arteries exerts a greater influence on nephron dynamics than do hemodynamic interactions. Chaotic attractors are sensitive to initial conditions, and we suggest that the nephron cluster is therefore sensitive to the information streams in the system, enabling the cluster to adapt to changing external conditions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnetp.2026.1889331</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnetp.2026.1889331</link>
        <title><![CDATA[Quantitative assessment of heart-brain coupling in neonates with hypoxic-ischemic encephalopathy]]></title>
        <pubdate>2026-09-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Danylo Reznichenko</author><author>Alina Frunza</author><author>Anastasiya Babintseva</author><author>Yevhenii Karpliuk</author><author>Oleksandr Romanchuk</author><author>Anton Popov</author><author>Kateryna Ivanko</author><author>Illya Chaikovsky</author>
        <description><![CDATA[Hypoxic-ischemic encephalopathy (HIE) remains a critical challenge in neonatal intensive care, requiring precise bedside monitoring to mitigate long-term neurological morbidity. While individual assessment of cerebral and cardiovascular activity is standard, the dynamic interaction between these systems provides untapped diagnostic value. This pilot study investigates neuro-cardiac coupling using synchronized long-term EEG and ECG recordings, focusing primarily on a core subset of 61 neonates classified by clinical HIE severity (Sarnat Stage 1 vs. Stage 2). We employed cross-modal analysis to evaluate the relationship between the amplitude-integrated EEG (aEEG) envelope and heart rate variability (HRV) metrics. Our results demonstrate that neuro-cardiac interaction is significantly modulated by HIE severity and electrocortical background patterns. Neonates with healthy continuous normal voltage (CNV) patterns exhibited robust neuro-cardiac synchronization (median Spearman’s r=0.22), which was significantly reduced by approximately 60% in patients with abnormal EEG backgrounds (median Spearman’s r=0.09, p=0.015). To ensure robust translation, machine learning models were evaluated across diverse parameter grids. While isolated hyperparameter configurations yielded peak performance metrics–such as an overall maximum accuracy of 90.22% using combined cardiocycle and spectral ECG features with XGBoost–the feature space demonstrated strong, un-biased baseline stability, yielding reliable average accuracies across window lengths (e.g., 77.27% mean F1-score for EEG-based Logistic Regression and 72.73% mean F1 for ECG-based XGBoost). These findings suggest that multi-modal coupling metrics offer enhanced physiological insight for automated HIE grading in a pilot setting.]]></description>
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