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The route to chaos and the phase dynamics of the large scales in a rotating shallow-water model have been rigorously examined through the construction of an autonomous five-mode Galerkin truncated system employing complex variables, useful in investigating how large/meso-scales are destabilized and how their dynamics evolves and transits to chaos. This investigation revealed two distinct transitions into chaotic behaviour as the level of energy introduced into the system was incrementally increased. The initial transition manifests through a succession of bifurcations that adhere to the established Feigenbaum sequence. Conversely, the subsequent transition, which emerges at elevated levels of injected energy, is marked by a pronounced shift from quasi-periodic states to chaotic regimes. The genesis of the first chaotic state is predominantly attributed to the preeminence of inertial forces in governing nonlinear interactions. The second chaotic state, however, arises from the augmented significance of free surface elevation in the dynamical process. A novel reformulation of the system, employing phase and amplitude representations for each truncated variable, elucidated that the phase components present a temporal piece-wise locking behaviour by maintaining a constant value for a protracted interval, preceding an abrupt transition characterised by a simple rotation of ±π, even as the amplitudes display chaotic behaviour. It was observed that the duration of phase stability diminishes with an increase in injected energy, culminating in the onset of chaos within the phase components at high energy levels. This phenomenon is attributed to the nonlinear term of the equations, wherein the phase components are introduced through linear combinations of triads encompassing disparate modes. When the locking durations vary across modes, the resultant dynamics is a stochastic interplay of multiple π phase shifts, generating a stochastic dynamic within the coupled phase triads, observable even at minimal energy injections. [ABSTRACT FROM AUTHOR]

Multivalent polymers are a key structural component of many biocondensates. When interacting with their cognate binding proteins, multivalent polymers such as RNA and modular proteins have been shown to influence the liquid-liquid phase separation (LLPS) boundary to both control condensate formation and to influence condensate dynamics after phase separation. Much is still unknown about the function and formation of these condensed droplets, but changes in their dynamics or phase separation are associated with neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and Alzheimer's Disease. Therefore, investigation into how the structure of multivalent polymers relates to changes in biocondensate formation and maturation is essential to understanding and treating these diseases. Here, we use a coarse-grain, Brownian Dynamics simulation with reactive binding that mimics specific interactions in order to investigate the difference between non-specific and specific multivalent binding polymers. We show that non-specific binding interactions can lead to much larger changes in droplet formation at lower protein-polymer interaction energies than their specific, valence-limited counterparts. We also demonstrate the effects of solvent conditions and polymer length on phase separation, and we present how modulating binding energy to the polymer can change the organization of a droplet in a three component system of polymer, binding protein, and solvent. Finally, we compare the effects of surface tension and polymer binding on the condensed phase dynamics, and show that both lower protein solubilities and higher attraction/affinity of the protein to the polymer result in slower droplet dynamics. This research will help to better understand experimental systems and provides additional insight into how multivalent polymers can control LLPS. [ABSTRACT FROM AUTHOR]

The initial phase dynamics of an epidemic without containment measures is commonly well modelled using exponential growth models. However, in the presence of containment measures, the exponential model becomes less appropriate. Under the implementation of an isolation measure for detected infectives, we propose to model epidemic dynamics by fitting a flexible growth model curve to reported positive cases, and to infer the overall epidemic dynamics by introducing information on the detection/testing effort and recovery and death rates. The resulting modelling approach is close to the Susceptible-Infectious-Quarantined-Recovered model framework. We focused on predicting the peaks (time and size) in positive cases, active cases and new infections. We applied the approach to data from the COVID-19 outbreak in Italy. Fits on limited data before the observed peaks illustrate the ability of the flexible growth model to approach the estimates from the whole data. [ABSTRACT FROM AUTHOR]

This study presents a novel non-autonomous mathematical model to explore the intricate relationship between temperature and desert locust population dynamics, considering the influence of both solitarious and gregarious phases across all life stages. The model incorporates temperature-dependent parameters for key biological processes, including egg development, hopper growth, adult maturation, and reproduction. Theoretical analysis reveals the model's capacity for complex dynamical behaviors, such as multiple stable states and backward bifurcations, suggesting the potential for sudden and unpredictable population shifts. Sensitivity analysis identifies temperature-related parameters as critical drivers of population fluctuations, highlighting the importance of accurate temperature predictions for effective management. Numerical simulations demonstrate the significant impact of temperature on population growth, with optimal conditions promoting rapid development and increased survival, while extreme temperatures can hinder population growth and trigger phase transitions. By providing a deeper understanding of temperature-driven population shifts, this model enhances the ability to predict locust outbreaks, optimize control strategies, and reduce the socio-economic and ecological impacts of locust invasions. [ABSTRACT FROM AUTHOR]

Cortical signals have been shown to track acoustic and linguistic properties of continuous speech. This phenomenon has been measured in both children and adults, reflecting speech understanding by adults as well as cognitive functions such as attention and prediction. Furthermore, atypical low-frequency cortical tracking of speech is found in children with phonological difficulties (developmental dyslexia). Accordingly, low-frequency cortical signals may play a critical role in language acquisition. A recent investigation with infants Attaheri et al., 2022 [1] probed cortical tracking mechanisms at the ages of 4, 7 and 11 months as participants listened to sung speech. Results from temporal response function (TRF), phase-amplitude coupling (PAC) and dynamic theta-delta power (PSD) analyses indicated speech envelope tracking and stimulus-related power (PSD) for delta and theta neural signals. Furthermore, delta- and theta-driven PAC was found at all ages, with theta phases displaying stronger PAC with high-frequency amplitudes than delta. The present study tests whether these previous findings replicate in the second half of the full cohort of infants (N = 122) who were participating in this longitudinal study (first half: N = 61, (1); second half: N = 61). In addition to demonstrating good replication, we investigate whether cortical tracking in the first year of life predicts later language acquisition for the full cohort (122 infants recruited, 113 retained) using both infant-led and parent-estimated measures and multivariate and univariate analyses. Increased delta cortical tracking in the univariate analyses, increased ~2Hz PSD power and stronger theta-gamma PAC in both multivariate and univariate analyses were related to better language outcomes using both infant-led and parent-estimated measures. By contrast, increased ~4Hz PSD power in the multi-variate analyses, increased delta-beta PAC and a higher theta/delta power ratio in the multi-variate analyses were related to worse language outcomes. The data are interpreted within a "Temporal Sampling" framework for developmental language trajectories. [ABSTRACT FROM AUTHOR]

Synchronized oscillatory gamma-band activity (30-100Hz) has been suggested to constitute a key mechanism to dynamically orchestrate sensory information integration across multiple spatio-temporal scales. We here tested whether interhemispheric functional connectivity and ensuing auditory perception can selectively be modulated by high-density transcranial alternating current stimulation (HD-tACS). For this purpose, we applied multi-site HD-tACS at 40Hz bilaterally with a phase lag of 180° and recorded a 64-channel EEG to study the oscillatory phase dynamics at the source-space level during a dichotic listening (DL) task in twenty-six healthy participants. In this study, we revealed an oscillatory phase signature at 40Hz which reflects different temporal profiles of the phase asymmetries during left and right ear percept. Here we report that 180°-tACS did not affect the right ear advantage during DL at group level. However, a follow-up analysis revealed that the intrinsic phase asymmetries during sham-tACS determined the directionality of the behavioral modulations: While a shift to left ear percept was associated with augmented interhemispheric asymmetry (closer to 180°), a shift to right ear processing was elicited in subjects with lower asymmetry (closer to 0°). Crucially, the modulation of the interhemispheric network dynamics depended on the deviation of the tACS-induced phase-lag from the intrinsic phase asymmetry. Our characterization of the oscillatory network trends is giving rise to the importance of phase-specific gamma-band coupling during ambiguous auditory perception, and emphasizes the necessity to address the inter-individual variability of phase asymmetries in future studies by tailored stimulation protocols. [ABSTRACT FROM AUTHOR]

Introduction: Adult patients who have suffered acute cardiac or pulmonary failure are increasingly being treated using extracorporeal membrane oxygenation (ECMO), a cardiopulmonary bypass technique. While ECMO has improved the long-term outcomes of these patients, neurological injuries can occur from underlying illness or ECMO itself. Cerebral autoregulation (CA) allows the brain to maintain steady perfusion during changes in systemic blood pressure. Dysfunctional CA is a marker of acute brain injury and can worsen neurologic damage. Monitoring CA using invasive modalities can be risky in ECMO patients due to the necessity of anticoagulation therapy. Diffuse correlation spectroscopy (DCS) measures cerebral blood flow continuously, noninvasively, at the bedside, and can monitor CA. In this study, we compare DCS-based markers of CA in veno-arterial ECMO patients with and without acute brain injury. Methods: Adults undergoing ECMO were prospectively enrolled at a single tertiary hospital and underwent DCS and arterial blood pressure monitoring during ECMO. Neurologic injuries were identified using brain computerized tomography (CT) scans obtained in all patients. CA was calculated over a twenty-minute window via wavelet coherence analysis (WCA) over 0.05 Hz to 0.1 Hz and a Pearson correlation (DCSx) between cerebral blood flow measured by DCS and mean arterial pressure. Results: Eleven ECMO patients who received CT neuroimaging were recruited. 5 (45%) patients were found to have neurologic injury. CA indices WCOH, the area under the curve of the WCA, were significantly higher for patients with neurological injuries compared to those without neurological injuries (right hemisphere p = 0.041, left hemisphere p = 0.041). %DCSx, percentage of time DCSx was above a threshold 0.4, were not significantly higher (right hemisphere p = 0.268, left hemisphere p = 0.073). Conclusion: DCS can be used to detect differences in CA for ECMO patients with neurological injuries compared to uninjured patients using WCA. [ABSTRACT FROM AUTHOR]

Gap phase dynamics are the dominant mode of forest turnover in tropical forests. However, gap processes are infrequently studied at the landscape scale. Airborne lidar data offer detailed information on three-dimensional forest structure, providing a means to characterize fine-scale (1 m) processes in tropical forests over large areas. Lidar-based estimates of forest structure (top down) differ from traditional field measurements (bottom up), and necessitate clear-cut definitions unencumbered by the wisdom of a field observer. We offer a new definition of a forest gap that is driven by forest dynamics and consistent with precise ranging measurements from airborne lidar data and tall, multi-layered tropical forest structure. We used 1000 ha of multi-temporal lidar data (2008, 2012) at two sites, the Tapajos National Forest and Ducke Reserve, to study gap dynamics in the Brazilian Amazon. Here, we identified dynamic gaps as contiguous areas of significant growth, that correspond to areas > 10 m2, with height <10 m. Applying the dynamic definition at both sites, we found over twice as much area in gap at Tapajos National Forest (4.8 %) as compared to Ducke Reserve (2.0 %). On average, gaps were smaller at Ducke Reserve and closed slightly more rapidly, with estimated height gains of 1.2 m y-1 versus 1.1 m y-1 at Tapajos. At the Tapajos site, height growth in gap centers was greater than the average height gain in gaps (1.3 m y-1 versus 1.1 m y-1). Rates of height growth between lidar acquisitions reflect the interplay between gap edge mortality, horizontal ingrowth and gap size at the two sites. We estimated that approximately 10 % of gap area closed via horizontal ingrowth at Ducke Reserve as opposed to 6 % at Tapajos National Forest. Height loss (interpreted as repeat damage and/or mortality) and horizontal ingrowth accounted for similar proportions of gap area at Ducke Reserve (13 % and 10 %, respectively). At Tapajos, height loss had a much stronger signal (23 % versus 6 %) within gaps. Both sites demonstrate limited gap contagiousness defined by an increase in the likelihood of mortality in the immediate vicinity (~6 m) of existing gaps. [ABSTRACT FROM AUTHOR]

Background: We aimed to determine whether serum levels of proteins related to changes in cardiac extracellular matrix (ECM) were associated with ischemic injury assessed by cardiac magnetic resonance (CMR) and mortality in patients with ST-elevation myocardial infarction (STEMI). Methods: The concentrations of six ECM-related proteins (periostin, osteopontin, syndecan-1, syndecan-4, bone morphogenetic protein 7, and growth differentiation factor (GDF)-15) were measured in serum samples from patients on Day 1 and Month 4 after STEMI (n = 239). Ischemic injury was assessed by myocardial salvage index, microvascular obstruction, infarct size, and left ventricular function measured by CMR conducted during the initial admission (median 2 days after admission) and after 4 months. All-cause mortality was recorded after a median follow-up time of 70 months. Results: Levels of periostin increased from Day 1 to Month 4 after hospitalization, while the levels of GDF-15, osteopontin, syndecan-1, and syndecan-4 declined. At both time points, high levels of syndecan-1 were associated with microvascular obstruction, large infarct size, and reduced left ventricular ejection fraction, whereas high levels of syndecan-4 at Month 4 were associated with a higher myocardial salvage index and less dilatation of the left ventricle. Higher mortality rates were associated with periostin levels at both time points, low syndecan-4 levels at Month 4, or high GDF-15 levels at Month 4. Conclusions: In patients with STEMI, we found an association between serum levels of ECM biomarkers and ischemic injury and mortality. The results provide new insight into the role ECM components play in ischemic injury following STEMI and suggests a potential for these biomarkers in prognostication after STEMI. [ABSTRACT FROM AUTHOR]

The ability to suddenly stop a planned movement or a movement being performed and restart it after a short interval is an important mechanism that allows appropriate behavior in response to contextual or environmental changes. However, performing such stop-and-restart movements smoothly is difficult at times. We investigated performance (response time) of stop-and-restart movements using a go/stop/re-go task and found consistent stop-and-restart difficulties after short (∼100 ms) stop-to-restart intervals (SRSI), and an increased probability of difficulties after longer (>200 ms) SRSIs, suggesting that two different mechanisms underlie stop-and-restart difficulties. Next, we investigated motor evoked potentials (MEPs) in a moving muscle induced by transcranial magnetic stimulation during a go/stop/re-go task. In re-go trials with a short SRSI (100 ms), the MEP amplitude continued to decrease after the re-go-signal onset, indicating that stop-and-restart difficulties with short SRSIs might be associated with a neural mechanism in the human motor system, namely, stop-related suppression of corticomotor (CM) excitability. Finally, we recorded electroencephalogram (EEG) activity during a go/stop/re-go task and performed a single-trial-based EEG power and phase time-frequency analysis. Alpha-band EEG phase locking to re-go-signal, which was only observed in re-go trials with long SRSI (250 ms), weakened in the delayed re-go response trials. These EEG phase dynamics indicate an association between stop-and-restart difficulties with long SRSIs and a neural mechanism in the human perception system, namely, decreased probability of EEG phase locking to visual stimuli. In contrast, smooth stop-and-restart human movement can be achieved in re-go trials with sufficient SRSI (150–200 ms), because release of stop-related suppression and simultaneous counter-activation of CM excitability may occur as a single task without second re-go-signal perception. These results suggest that skilled motor behavior is subject to various constraints in not only motor, but also perceptual (and attentional), systems. [ABSTRACT FROM AUTHOR]

The view that clot time-based assays do not provide a sufficient assessment of an individual's hemostatic competence, especially in the context of anticoagulant therapy, has provoked a search for new metrics, with significant focus directed at techniques that define the propagation phase of thrombin generation. Here we use our deterministic mathematical model of tissue-factor initiated thrombin generation in combination with reconstructions using purified protein components to characterize how the interplay between anticoagulant mechanisms and variable composition of the coagulation proteome result in differential regulation of the propagation phase of thrombin generation. Thrombin parameters were extracted from computationally derived thrombin generation profiles generated using coagulation proteome factor data from warfarintreated individuals (N = 54) and matching groups of control individuals (N = 37). A computational clot time prolongation value (cINR) was devised that correlated with their actual International Normalized Ratio (INR) values, with differences between individual INR and cINR values shown to derive from the insensitivity of the INR to tissue factor pathway inhibitor (TFPI). The analysis suggests that normal range variation in TFPI levels could be an important contributor to the failure of the INR to adequately reflect the anticoagulated state in some individuals. Warfarin-induced changes in thrombin propagation phase parameters were then compared to those induced by unfractionated heparin, fondaparinux, rivaroxaban, and a reversible thrombin inhibitor. Anticoagulants were assessed at concentrations yielding equivalent cINR values, with each anticoagulant evaluated using 32 unique coagulation proteome compositions. The analyses showed that no anticoagulant recapitulated all features of warfarin propagation phase dynamics; differences in propagation phase effects suggest that anticoagulants that selectively target fXa or thrombin may provoke fewer bleeding episodes. More generally, the study shows that computational modeling of the response of core elements of the coagulation proteome to a physiologically relevant tissue factor stimulus may improve the monitoring of a broad range of anticoagulants. [ABSTRACT FROM AUTHOR]

The aging effects on circadian rhythms have diverse implications including changes in the pattern of rhythmic expressions, such as a wide fragmentation of the rhythm of rest-activity and decrease in amplitude of activity regulated by the suprachiasmatic nucleus (SCN). The study of blue light on biological aspects has received great current interest due, among some aspects, to its positive effects on psychiatric disorders in humans. This study aims to evaluate the effect of blue light therapy on the SCN functional aspects, through the evaluation of the rest-activity rhythm, in aging rats. For this, 33 sixteen-months-old male Wistar rats underwent continuous records of locomotor activity and were exposed to periods of 6 hours of blue light during the first half of the light phase (Zeitgeber times 0–6) for 14 days. After this, the rats were maintained at 12h:12h light:dark cycle to check the long-term effect of blue light for 14 days. Blue light repeated exposure showed positive effects on the rhythmic variables of locomotor activity in aged rats, particularly the increase in amplitude, elevation of rhythmic robustness, phase advance in acrophase, and greater consolidation of the resting phase. This effect depends on the presence of daily blue light exposure. In conclusion, our results indicate that blue light is a reliable therapy to reduce circadian dysfunctions in aged rats, but other studies assessing how blue light modulates the neural components to modulate this response are still needed. [ABSTRACT FROM AUTHOR]

In this work we show how global self-organized patterns can come out of a disordered ensemble of point oscillators, as a result of a deterministic, and not of a random, cooperative process. The resulting system dynamics has many characteristics of classical thermodynamics. To this end, a modified Kuramoto model is introduced, by including Euclidean degrees of freedom and particle polarity. The standard deviation of the frequency distribution is the disorder parameter, diversity, acting as temperature, which is both a source of motion and of disorder. For zero and low diversity, robust static phase-synchronized patterns (crystals) appear, and the problem reverts to a generic dissipative many-body problem. From small to moderate diversity crystals display vibrations followed by structure disintegration in a competition of smaller dynamic patterns, internally synchronized, each of which is capable to manage its internal diversity. In this process a huge variety of self-organized dynamic shapes is formed. Such patterns can be seen again as (more complex) oscillators, where the same description can be applied in turn, renormalizing the problem to a bigger scale, opening the possibility of pattern evolution. The interaction functions are kept local because our idea is to build a system able to produce global patterns when its constituents only interact at the bond scale. By further increasing the oscillator diversity, the dynamics becomes erratic, dynamic patterns show short lifetime, and finally disappear for high diversity. Results are neither qualitatively dependent on the specific choice of the interaction functions nor on the shape of the probability function assumed for the frequencies. The system shows a phase transition and a critical behaviour for a specific value of diversity. [ABSTRACT FROM AUTHOR]

Background: Variable fibrinogen content within cryoprecipitate makes accurate dosing challenging in patients with coagulopathic bleeding, in addition to pathogen transmission risks associated with its administration. Purified and standardized human fibrinogen concentrates (HFCs) represent reliable alternatives. Full cryoprecipitate characterization is required to inform selection of an appropriate fibrinogen source for supplementation therapy. Methods: Extended biochemical comparison of pooled cryoprecipitate and HFC (Fibryga, Octapharma) was performed using commercially available assays to determine levels of variability in cryoprecipitate and HFC. In addition to standard procoagulant factors, measurements included activities of platelet-derived microparticles (PMPs) and plasminogen, and levels of fibrin degradation products. Results: Cryoprecipitate contains lower fibrinogen levels than HFC (4.83 vs.19.73 g/L; p<0.001), translating to approximately half the amount of fibrinogen per standard cryoprecipitate dose (two pools, pre-pooled from five donations each) vs. HFC (2.14 vs. 3.95 g; p<0.001). Factor XIII (FXIII) levels were also lower in cryoprecipitate vs. HFC (192.17 vs. 328.33 IU/dL; p = 0.002). Levels of procoagulants in cryoprecipitate, such as von Willebrand Factor (VWF) and factor VIII (FVIII), were highly variable, as was PMP activity. A standard cryoprecipitate dose contains significantly higher levels of measured plasminogen and D-dimer fragments than a standard HFC dose. Conclusion: The tested HFC is a more reliable fibrinogen and FXIII source for accurate dosing compared with cryoprecipitate. Cryoprecipitate appears considerably less predictable for bleeding management due to wide variation in pro- and anticoagulation factors, the presence of PMPs, and the potential to elevate VWF and FVIII to prothrombotic levels. [ABSTRACT FROM AUTHOR]

We propose a model for the structure formation of jellyfish swimming based on active Brownian particles. We address the phenomena of counter-current swimming, avoidance of turbulent flow regions and foraging. We motivate corresponding mechanisms from observations of jellyfish swarming reported in the literature and incorporate them into the generic modelling framework. The model characteristics is tested in three paradigmatic flow environments. [ABSTRACT FROM AUTHOR]

Perception-action coordination (also known as sensorimotor synchronization, SMS) is often studied by analyzing motor coordination with auditory rhythms. The current study assesses phasing—a compositional technique in which two people tap the same rhythm at varying phases by adjusting tempi—to explore how SMS is impacted by individual and situational factors. After practice trials, participants engaged in the experimental phasing task with a metronome at tempi ranging from 80–140 beats per minute (bpm). Multidimensional recurrence quantification analysis (MdRQA) was used to compare nonlinear dynamics of phasing performance. Varying coupling patterns emerged and were significantly predicted by tempo and linguistic experience. Participants who successfully phased replicated findings from an original case study, demonstrating stable tapping patterns near in-phase and antiphase, while those unsuccessful at phasing showed weaker attraction to in-phase and antiphase. [ABSTRACT FROM AUTHOR]

Despite current advancement in the field of biomedical image processing, propelled by the deep learning revolution, multimodal image registration, due to its several challenges, is still often performed manually by specialists. The recent success of image-to-image (I2I) translation in computer vision applications and its growing use in biomedical areas provide a tempting possibility of transforming the multimodal registration problem into a, potentially easier, monomodal one. We conduct an empirical study of the applicability of modern I2I translation methods for the task of rigid registration of multimodal biomedical and medical 2D and 3D images. We compare the performance of four Generative Adversarial Network (GAN)-based I2I translation methods and one contrastive representation learning method, subsequently combined with two representative monomodal registration methods, to judge the effectiveness of modality translation for multimodal image registration. We evaluate these method combinations on four publicly available multimodal (2D and 3D) datasets and compare with the performance of registration achieved by several well-known approaches acting directly on multimodal image data. Our results suggest that, although I2I translation may be helpful when the modalities to register are clearly correlated, registration of modalities which express distinctly different properties of the sample are not well handled by the I2I translation approach. The evaluated representation learning method, which aims to find abstract image-like representations of the information shared between the modalities, manages better, and so does the Mutual Information maximisation approach, acting directly on the original multimodal images. We share our complete experimental setup as open-source (https://github.com/MIDA-group/MultiRegEval), including method implementations, evaluation code, and all datasets, for further reproducing and benchmarking. [ABSTRACT FROM AUTHOR]

Full-field laser speckle microscopy provides real-time imaging of superficial blood flow rate. Here we apply continuous wavelet transform to time series of speckle-estimated blood flow from each pixel of the images to map synchronous patterns in instantaneous frequency and phase on the surface of rat kidneys. The regulatory mechanism in the renal microcirculation generates oscillations in arterial blood flow at several characteristic frequencies. Our approach to laser speckle image processing allows detection of frequency and phase entrainments, visualization of their patterns, and estimation of the extent of synchronization in renal cortex dynamics. [ABSTRACT FROM AUTHOR]

We investigated modality differences in the N2 and P3 components of event-related potentials (ERPs) between somatosensory and auditory Go/No-go paradigms in eighteen healthy prepubescent children (mean age: 125.9±4.2 months). We also evaluated the relationship between behavioral responses (reaction time, reaction time variability, and omission and commission error rates) and amplitudes and latencies of N2 and P3 during somatosensory and auditory Go/No-go paradigms. The peak latency of No-go-N2 was significantly shorter than that of Go-N2 during somatosensory paradigms, but not during auditory paradigms. The peak amplitude of P3 was significantly larger during somatosensory than auditory paradigms, and the peak latency of P3 was significantly shorter during somatosensory than auditory paradigms. Correlations between behavioral responses and the P3 component were not found during somatosensory paradigms. On the other hand, in auditory paradigms, correlations were detected between the reaction time and peak amplitude of No-go-P3, and between the reaction time variability and peak latency of No-go-P3. A correlation was noted between commission error and the peak latency of No-go-N2 during somatosensory paradigms. Compared with previous adult studies using both somatosensory and auditory Go/No-go paradigms, the relationships between behavioral responses and ERP components would be weak in prepubescent children. Our data provide findings to advance understanding of the neural development of motor execution and inhibition processing, that is dependent on or independent of the stimulus modality. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, governments globally had to impose severe contact restriction measures and social mobility limitations in order to limit the exposure of the population to COVID-19. These public health policy decisions were informed by statistical models for infection rates in national populations. In this work, we are interested in modelling the temporal evolution of national-level infection counts for the United Kingdom (UK—Wales, England, Scotland), Germany (GM), Italy (IT), Spain (SP), Japan (JP), Australia (AU) and the United States (US). We model the national-level infection counts for the period January 2020 to January 2021, thus covering both the pre- and post-vaccine roll-out periods, in order to better understand the most reliable model structure for the COVID-19 epidemic growth curve. We achieve this by exploring a variety of stochastic population growth models and comparing their calibration, with respect to in-sample fitting and out-of-sample forecasting, both with and without exposure adjustment, to the most widely used and reported growth model, the Gompertz population model, often referred to in the public health policy discourse during the COVID-19 pandemic. Model risk as we explore it in this work manifests in the inability to adequately capture the behaviour of the disease progression growth rate curve. Therefore, our concept of model risk is formed relative to the standard reference Gompertz model used by decision-makers, and then we can characterise model risk mathematically as having two components: the dispersion of the observation distribution, and the structure of the intensity function over time for cumulative counts of new infections daily (i.e. the force of infection) attributed directly to the COVID-19 pandemic. We also explore how to incorporate in these population models the effect that governmental interventions have had on the number of infected cases. This is achieved through the development of an exposure adjustment to the force of infection comprised of a purpose-built sentiment index, which we construct from various authoritative public health news reporting. The news reporting media we employed were the New York Times, the Guardian, the Telegraph, Reuters global blog, as well as national and international health authorities: the European Centre for Disease Prevention and Control, the United Nations Economic Commission for Europe, the United States Centres for Disease Control and Prevention, and the World Health Organisation. We find that exposure adjustments that incorporate sentiment are better able to calibrate to early stages of infection spread in all countries under study. [ABSTRACT FROM AUTHOR]

The circadian rhythm, called Process C, regulates a wide range of biological processes in humans including sleep, metabolism, body temperature, and hormone secretion. Light is the dominant synchronizer of the circadian rhythm—it has been used to regulate the circadian phase to cope with jet-lag, shift work, and sleep disorder. The homeostatic oscillation of the sleep drive is called Process S. Process C and Process S together determine the sleep-wake cycle in what is known as the two-process model. This paper addresses the regulation of both Process C and Process S by scheduling light exposure and sleep based on numerical simulations of circadian rhythm and sleep mathematical models. This is a significant step beyond the existing literature that only considers the entrainment of Process C. Regulation of the two-process model poses several unique features and challenges: 1. Process S is non-smooth, i.e., the homeostatic dynamics are different in the sleep and wake regimes; 2. Light only indirectly affects Process S through Process C; 3. Light does not affect Process C during sleep. We consider two scenarios: optimizing light intensity as the control input with spontaneous (i.e., unscheduled) sleep/wake times and jointly optimizing the light intensity and the sleep/wake times, which allows limited delayed sleep and early waking as part of the decision variables. We solve the time-optimal entrainment problem for the two-process model for both scenarios using an extension of the gradient descent algorithm to non-smooth systems. To illustrate the efficacy of our time-optimal entrainment strategies, we consider two common use cases: transmeridian travelers and shift workers. For transmeridian travelers, joint optimization of the two-process model avoids the unrealistic long wake duration when only Process C is considered. The entrainment time also decreases when both the light input and the sleep schedule are optimized compared to when only the light input is optimized. For shift workers, we show that the entrainment time is significantly shortened by optimizing the night shift working light. [ABSTRACT FROM AUTHOR]

Multivalent polymers are a key structural component of many biocondensates. When interacting with their cognate binding proteins, multivalent polymers such as RNA and modular proteins have been shown to influence the liquid-liquid phase separation (LLPS) boundary to both control condensate formation and to influence condensate dynamics after phase separation. Much is still unknown about the function and formation of these condensed droplets, but changes in their dynamics or phase separation are associated with neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and Alzheimer’s Disease. Therefore, investigation into how the structure of multivalent polymers relates to changes in biocondensate formation and maturation is essential to understanding and treating these diseases. Here, we use a coarse-grain, Brownian Dynamics simulation with reactive binding that mimics specific interactions in order to investigate the difference between non-specific and specific multivalent binding polymers. We show that non-specific binding interactions can lead to much larger changes in droplet formation at lower protein-polymer interaction energies than their specific, valence-limited counterparts. We also demonstrate the effects of solvent conditions and polymer length on phase separation, and we present how modulating binding energy to the polymer can change the organization of a droplet in a three component system of polymer, binding protein, and solvent. Finally, we compare the effects of surface tension and polymer binding on the condensed phase dynamics, and show that both lower protein solubilities and higher attraction/affinity of the protein to the polymer result in slower droplet dynamics. This research will help to better understand experimental systems and provides additional insight into how multivalent polymers can control LLPS.

Virtual reality (VR) technology is commonly used in balance research due to its ability to simulate real world experiences under controlled experimental conditions. However, several studies reported considerable differences in balance behavior in real world environments as compared to virtual environments presented in a head mounted display. Most of these studies were conducted more than a decade ago, at a time when VR was still struggling with major technical limitations (delays, limited field-of-view, etc.). In the meantime, VR technology has progressed considerably, enhancing its capacity to induce the feeling of presence and behavioural realism. In this study, we addressed two questions: Has VR technology now reached a point where balance is similar in real and virtual environments? And does the integration of visual cues for balance depend on the subjective experience of presence? We used a state-of-the-art head mounted VR system and a custom-made balance platform to compare balance when viewing (1) a real-world environment, (2) a photo-realistic virtual copy of the real-world environment, (3) an abstract virtual environment consisting of only spheres and bars ('low presence' VR condition), and, as reference, (4) a condition with eyes closed. Body sway of ten participants was measured in three different support surface conditions: (A) quiet stance, (B) stance on a sway referenced surface, and (C) surface tilting following a pseudo-random sequence. A 2-level repeated measures ANOVA and PostHoc analyses revealed no significant differences in body sway between viewing the real world environment and the photo-realistic virtual copy. In contrast, body sway was increased in the 'low presence' abstract scene and further increased with eyes closed. Results were consistent across platform conditions. Our results support the hypothesis that state of the art VR reached a point of behavioural realism in which balance in photo-realistic VR is similar to balance in a real environment. Presence was lower in the abstract virtual condition as compared to the photo-realistic condition as measured by the IPQ presence questionnaire. Thus, our results indicate that spatial presence may be a moderating factor, but further research is required to confirm this notion. We conceive that virtual reality is a valid tool for balance research, but that the properties of the virtual environment affects results. [ABSTRACT FROM AUTHOR]

The circadian rhythm functions as a master clock that regulates many physiological processes in humans including sleep, metabolism, hormone secretion, and neurobehavioral processes. Disruption of the circadian rhythm is known to have negative impacts on health. Light is the strongest circadian stimulus that can be used to regulate the circadian phase. In this paper, we consider the mathematical problem of time-optimal circadian (re)entrainment, i.e., computing the lighting schedule to drive a misaligned circadian phase to a reference circadian phase as quickly as possible. We represent the dynamics of the circadian rhythm using the Jewett-Forger-Kronauer (JFK) model, which is a third-order nonlinear differential equation. The time-optimal circadian entrainment problem has been previously solved in settings that involve either a reduced-order JFK model or open-loop optimal solutions. In this paper, we present (1) a general solution for the time-optimal control problem of fastest entrainment that can be applied to the full order JFK model (2) an evaluation of the impacts of model reduction on the solutions of the time-optimal control problem, and (3) optimal feedback control laws for fastest entrainment for the full order Kronauer model and evaluate their robustness under some modeling errors. [ABSTRACT FROM AUTHOR]

We report the phenomenon of frequency clustering in a network of Hodgkin-Huxley neurons with spike timing-dependent plasticity. The clustering leads to a splitting of a neural population into a few groups synchronized at different frequencies. In this regime, the amplitude of the mean field undergoes low-frequency modulations, which may contribute to the mechanism of the emergence of slow oscillations of neural activity observed in spectral power of local field potentials or electroencephalographic signals at high frequencies. In addition to numerical simulations of such multi-clusters, we investigate the mechanisms of the observed phenomena using the simplest case of two clusters. In particular, we propose a phenomenological model which describes the dynamics of two clusters taking into account the adaptation of coupling weights. We also determine the set of plasticity functions (update rules), which lead to multi-clustering. [ABSTRACT FROM AUTHOR]

Numerous technologies exist to detect circulating tumor cells (CTCs), although reports on cytological detection of CTCs remain limited. We recently developed a cytology-based CTC detection device using glass slides and light microscopy. In this study, we automated this previously manual device to improve its efficiency and cost effectiveness for clinical applications. We conducted a pilot study using this device to compare CTCs in peripheral blood (PB) and draining venous blood (DVB) from patients with colorectal cancer (CRC). The cytology-based automated CTC detection platform consisted of a disposable filtration device with a three-dimensional (3D) metal filter and multichannel automated CTC enrichment device. This platform allowed rapid and gentle filtration of CTCs and their efficient transfer from the filter to glass slides for subsequent Papanicolaou (Pap) and immunocytochemical (ICC) staining. Cytological diagnosis of CTCs was performed by observing permanent glass slide specimens by light microscopy. The current pilot clinical study enrolled CRC patients (n = 26) with stage I–IV tumors, who underwent surgery. PB was collected before surgery, and DVB was obtained from the mesenteric vein immediately after resection. Based on the CTC morphology obtained from PB and DVB samples, we proposed the following cytological criteria for the diagnosis of CTCs: pan-cytokeratin-positive, atypical cells with malignant morphological features identified by Pap staining. The numbers of CTCs defined by these criteria were significantly higher in DVB than PB from CRC patients (p<0.01), and the number of CTCs in DVB was increased significantly with stage progression (p<0.05). These results suggest that DVB may be another potential source of CTCs other than PB for liquid biopsies including downstream analysis. This automated cytology-based CTC detection device therefore provides a unique and powerful tool to investigate the significance of CTCs in CRC patients in a clinical setting. [ABSTRACT FROM AUTHOR]

We report a study on twenty-two healthy human subjects of the dynamic relationship between cerebral hemoglobin concentration ([HbT]), measured with near-infrared spectroscopy (NIRS) in the prefrontal cortex, and systemic arterial blood pressure (ABP), measured with finger plethysmography. [HbT] is a measure of local cerebral blood volume (CBV). We induced hemodynamic oscillations at discrete frequencies in the range 0.04–0.20 Hz with cyclic inflation and deflation of pneumatic cuffs wrapped around the subject’s thighs. We modeled the transfer function of ABP and [HbT] in terms of effective arterial (K( a )) and venous (K( v )) compliances, and a cerebral autoregulation time constant (τ(AR)). The mean values (± standard errors) of these parameters across the twenty-two subjects were K( a ) = 0.01 ± 0.01 μM/mmHg, K( v ) = 0.09 ± 0.05 μM/mmHg, and τ(AR) = 2.2 ± 1.3 s. Spatially resolved measurements in a subset of eight subjects reveal a spatial variability of these parameters that may exceed the inter-subject variability at a set location. This study sheds some light onto the role that ABP and cerebral blood flow (CBF) play in the dynamics of [HbT] measured with NIRS, and paves the way for new non-invasive optical studies of cerebral blood flow and cerebral autoregulation. [ABSTRACT FROM AUTHOR]

In aging, structural and/or functional brain changes may precede changes in cognitive performance. We previously showed that despite having hippocampal volumes similar to those of younger adults, older adults showed oscillatory changes during the encoding phase of a short-delay visuospatial memory task that required spatial relations among objects to be bound across time (Rondina et al., 2016). The present work provides a complementary set of analyses to examine age-related changes in oscillatory activity during maintenance and retrieval of those spatial relations in order to provide a comprehensive examination of the neural dynamics that support memory function in aging. Participants were presented with three study objects sequentially. Following a delay (maintenance phase), the objects were re-presented simultaneously and participants had to determine whether the relative spatial relations among the objects had been maintained (retrieval phase). Older adults had similar task accuracy, but slower response times, compared to younger adults. Both groups showed a decrease in theta (2-7Hz), alpha (9-14Hz), and beta (15-30Hz) power during the maintenance phase. During the retrieval phase, younger adults showed theta and beta power increases that predicted greater task accuracy, whereas older adults showed a widespread decrease in each of the three frequency ranges that predicted longer response latencies. Older adults also showed distinct patterns of behaviour-related activity depending on whether the analysis was time-locked to the onset of the stimulus or to the onset of the response during the test phase. These findings suggest that older adults may experience declines in relational binding and/or comparison processes that are reflected in oscillatory changes prior to structural decline. [ABSTRACT FROM AUTHOR]

We actively maintain postural equilibrium in everyday life, and, although we are unaware of the underlying processing, there is increasing evidence for cortical involvement in this postural control. Converging evidence shows that we make appropriate use of ‘postural anchors’, for example static objects in the environment, to stabilise our posture. Visually evoked postural responses (VEPR) that are caused when we counteract the illusory perception of self-motion in space (vection) are modulated in the presence of postural anchors and therefore provide a convenient behavioural measure. The aim of this study is to evaluate the factors influencing visual appraisal of the suitability of postural anchors. We are specifically interested in the effect of perceived ‘reality’ in VR the expected ‘stability’ of visual anchors. To explore the effect of ‘reality’ we introduced an accommodation-vergence conflict. We show that VEPR are appropriately modulated only when virtual visual ‘anchors’ are rendered such that vergence and accommodation cues are consistent. In a second experiment we directly test whether cognitive assessment of the likely stability of real perceptual anchors (we contrast a ‘teapot on a stand’ and a ‘helium balloon’) affects VEPR. We show that the perceived positional stability of environmental anchors modulate postural responses. Our results confirm previous findings showing that postural sway is modulated by the configuration of the environment and further show that an assessment of the stability and reality of the environment plays an important role in this process. On this basis we propose design guidelines for VR systems, in particular we argue that accommodation-vergence conflicts should be minimised and that high quality motion tracking and rendering are essential for high fidelity VR. [ABSTRACT FROM AUTHOR]

This study investigated the utility of the pupillary light reflex as a method of differentiating DSPD patients with delayed melatonin timing relative to desired/required sleep time (circadian type) and those with non-delayed melatonin timing (non-circadian type). All participants were young adults, with a total of 14 circadian DSPD patients (M = 28.14, SD = 5.26), 12 non-circadian DSPD patients (M = 29.42, SD = 11.51) and 51 healthy controls (M = 21.47 SD = 3.16) completing the protocol. All participants were free of central nervous system acting medications and abstained from caffeine and alcohol on the day of the assessment. Two pupillary light reflex measurements were completed by each participant, one with a 1s dim (~10 lux) light exposure, and one with a 1s bright (~1500 lux) light exposure. Circadian DSPD patients showed a significantly faster pupillary light reflex than both non-circadian DSPD patients and healthy controls. Non-circadian patients and healthy controls did not differ significantly. Receiver operating characteristic curves were generated to determine the utility of mean and maximum constriction velocity in differentiating the two DSPD phenotypes, and these demonstrated high levels of sensitivity (69.23–-100%) and specificity (66.67–91.67%) at their optimal cut offs. The strongest predictor of DSPD phenotype was the mean constriction velocity to bright light (AUC = 0.87). These results support the potential for the pupillary light reflex to clinically differentiate between DSPD patients with normal vs. delayed circadian timing relative to desired bedtime, without the need for costly and time-consuming circadian assessments. [ABSTRACT FROM AUTHOR]

Game theory has been widely applied to many research areas including economics, biology and social sciences. However, it is still challenging to quantify the global stability and global dynamics of the game theory. We developed a landscape and flux framework to quantify the global stability and global dynamics of the game theory. As an example, we investigated a model of three-strategy game: a special replicator mutator game termed as the repeated Prison Dilemma model. In this model, one stable state, two stable states and limit cycle can emerge under different parameters. The repeated Prisoner’s Dilemma system has Hopf bifurcation from one stable state to limit cycle state, and then to another one stable state or two stable states, and vice versa. We quantified the global stability of the repeated Prisoner’s Dilemma system and identified optimal kinetic paths between the basins of attractor. The optimal paths are irreversible due to the non-zero flux. We also quantified the interplay between Peace and War. [ABSTRACT FROM AUTHOR]

Recent studies showed that induced microRNA-449a (miR-449a) enhances a G2/M cell cycle checkpoint arrest in prostate cancer (LNCaP) and lung adenocarcinoma cell lines. In the case of LNCaP cells, upregulated miR-449a directly downregulates c-Myc that is required to induce the cell cycle regulators Cdc25A and Cdc2/CyclinB whose inactivation blocks G2 to M phase transition. However, the molecular mechanisms involved are yet unclear, although in other prostate cancer cells the interactions among p53, miR-449a and Sirt-1 can affect the induction of the G2/M arrest. In order to clarify these molecular mechanisms, in this work we propose a boolean model of the G2/M checkpoint arrest regulation contemplating the influence of miR-449a. The model shows that the cell fate determination between two cellular phenotypes: G2/M-Arrest for DNA repair and G2/M-induced apoptosis is stochastic and influenced by miR-449a state of activation. The results were compared with experimental data available presenting agreement. We also found that several feedback loops are involved in this cell fate regulation and we indicate, through in silico gain or loss of function perturbations of genes, which of these feedback loops are more efficient to favor a specific phenotype. [ABSTRACT FROM AUTHOR]

It is still unclear under which conditions temporary combined antiretroviral therapy (cART) results in a prolonged remission after interruption. Clinical trials have contradicting reposts about the effect of cART during primary HIV infection on the disease progression. Here we propose that the apparent contradiction is due the presence of a window of opportunity for cART treatment observed in the in silico studies. We study non-linear correlations in the HIV dynamics over time using information theory. This approach requires a large dataset of CD4+ T lymphocytes and viral load concentrations over time. Since it is unfeasible to collect the required amount of data in clinical trials we use C-ImmSim, a clinically validated in silico model of the HIV infection, to simulate the HIV infection and temporary cART in 500 virtual patients for a period of 6 years post infection in time steps of 8 hours. We validate the results of our model with two published clinical trials of temporary cART in acute infection and analyse the impact of cART on the immune response. Our quantitative analysis predicts a “window of opportunity” of about ten months after the acute phase during which a temporary cART has significantly longer-lasting beneficial effects on the immune system as compared to treatment during the chronic phase. This window may help to explain the controversial outcomes of clinical trials that differ by the starting time and duration of the short-term course cART and provides a critical insight to develop appropriate protocols for future clinical trials. [ABSTRACT FROM AUTHOR]

This work focuses on the experimental data analysis of electroencephalography (EEG) data, in which multiple sensors are recording oscillatory voltage time series. The EEG data analyzed in this manuscript has been acquired using a low-cost commercial headset, the Emotiv EPOC+. Our goal is to compare different techniques for the optimal estimation of collective rhythms from EEG data. To this end, a traditional method such as the principal component analysis (PCA) is compared to more recent approaches to extract a collective rhythm from phase-synchronized data. Here, we extend the work by Schwabedal and Kantz (PRL 116, 104101 (2016)) evaluating the performance of the Kosambi-Hilbert torsion (KHT) method to extract a collective rhythm from multivariate oscillatory time series and compare it to results obtained from PCA. The KHT method takes advantage of the singular value decomposition algorithm and accounts for possible phase lags among different time series and allows to focus the analysis on a specific spectral band, optimally amplifying the signal-to-noise ratio of a common rhythm. We evaluate the performance of these methods for two particular sets of data: EEG data recorded with closed eyes and EEG data recorded while observing a screen flickering at 15 Hz. We found an improvement in the signal-to-noise ratio of the collective signal for the KHT over the PCA, particularly when random temporal shifts are added to the channels. [ABSTRACT FROM AUTHOR]

Urbanization has been driven by various social, economic, and political factors around the world for centuries. Because urbanization continues unabated in many places, it is crucial to understand patterns of urbanization and their potential ecological and environmental impacts. Given this need, the objectives of our study were to quantify urban growth rates, growth modes, and resultant changes in the landscape pattern of urbanization in Hanoi, Vietnam from 1993 to 2010 and to evaluate the extent to which the process of urban growth in Hanoi conformed to the diffusion-coalescence theory. We analyzed the spatiotemporal patterns and dynamics of the built-up land in Hanoi using landscape expansion modes, spatial metrics, and a gradient approach. Urbanization was most pronounced in the periods of 2001–2006 and 2006–2010 at a distance of 10 to 35 km around the urban center. Over the 17 year period urban expansion in Hanoi was dominated by infilling and edge expansion growth modes. Our findings support the diffusion-coalescence theory of urbanization. The shift of the urban growth areas over time and the dynamic nature of the spatial metrics revealed important information about our understanding of the urban growth process and cycle. Furthermore, our findings can be used to evaluate urban planning policies and aid in urbanization issues in rapidly urbanizing countries. [ABSTRACT FROM AUTHOR]

Cerebral autoregulation (CA) is the complex homeostatic regulatory relationship between blood pressure (BP) and cerebral blood flow (CBF). This study aimed to analyze the frequency-specific coupling function between cerebral oxyhemoglobin concentrations (delta [HbO2]) and mean arterial pressure (MAP) signals based on a model of coupled phase oscillators and dynamical Bayesian inference. Delta [HbO2] was measured by 24-channel near-infrared spectroscopy (NIRS) and arterial BP signals were obtained by simultaneous resting-state measurements in patients with stroke, that is, 9 with left hemiparesis (L–H group), 8 with right hemiparesis (R–H group), and 17 age-matched healthy individuals as control (healthy group). The coupling functions from MAP to delta [HbO2] oscillators were identified and analyzed in four frequency intervals (I, 0.6–2 Hz; II, 0.145–0.6 Hz; III, 0.052–0.145 Hz; and IV, 0.021–0.052 Hz). In L–H group, the CS from MAP to delta [HbO2] in interval III in channel 8 was significantly higher than that in healthy group (p = 0.003). Compared with the healthy controls, the coupling in MAP→delta [HbO2] showed higher amplitude in interval I and IV in patients with stroke. The increased CS and coupling amplitude may be an evidence of impairment in CA, thereby confirming the presence of impaired CA in patients with stroke. In interval III, the CS in L–H group from MAP to delta [HbO2] in channel 16 (p = 0.001) was significantly lower than that in healthy controls, which might indicate the compensatory mechanism in CA of the unaffected side in patients with stroke. No significant difference in region-wise CS between affected and unaffected sides was observed in stroke groups, indicating an evidence of globally impaired CA. These findings provide a method for the assessment of CA and will contribute to the development of therapeutic interventions in stroke patients. [ABSTRACT FROM AUTHOR]

Insects have various gaits with specific characteristics and can change their gaits smoothly in accordance with their speed. These gaits emerge from the embodied sensorimotor interactions that occur between the insect’s neural control and body dynamic systems through sensory feedback. Sensory feedback plays a critical role in coordinated movements such as locomotion, particularly in stick insects. While many previously developed insect models can generate different insect gaits, the functional role of embodied sensorimotor interactions in the interlimb coordination of insects remains unclear because of their complexity. In this study, we propose a simple physical model that is amenable to mathematical analysis to explain the functional role of these interactions clearly. We focus on a foot contact sensory feedback called phase resetting, which regulates leg retraction timing based on touchdown information. First, we used a hexapod robot to determine whether the distributed decoupled oscillators used for legs with the sensory feedback generate insect-like gaits through embodied sensorimotor interactions. The robot generated two different gaits and one had similar characteristics to insect gaits. Next, we proposed the simple model as a minimal model that allowed us to analyze and explain the gait mechanism through the embodied sensorimotor interactions. The simple model consists of a rigid body with massless springs acting as legs, where the legs are controlled using oscillator phases with phase resetting, and the governed equations are reduced such that they can be explained using only the oscillator phases with some approximations. This simplicity leads to analytical solutions for the hexapod gaits via perturbation analysis, despite the complexity of the embodied sensorimotor interactions. This is the first study to provide an analytical model for insect gaits under these interaction conditions. Our results clarified how this specific foot contact sensory feedback contributes to generation of insect-like ipsilateral interlimb coordination during hexapod locomotion. [ABSTRACT FROM AUTHOR]

In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities. [ABSTRACT FROM AUTHOR]

Planar intra-cortical electrode (Utah) arrays provide a unique window into the spatial organization of cortical activity. Reconstruction of the current source density (CSD) underlying such recordings, however, requires “inverting” Poisson’s equation. For inter-laminar recordings, this is commonly done by the CSD method, which consists in taking the second-order spatial derivative of the recorded local field potentials (LFPs). Although the CSD method has been tremendously successful in mapping the current generators underlying inter-laminar LFPs, its application to planar recordings is more challenging. While for inter-laminar recordings the CSD method seems reasonably robust against violations of its assumptions, is it unclear as to what extent this holds for planar recordings. One of the objectives of this study is to characterize the conditions under which the CSD method can be successfully applied to Utah array data. Using forward modeling, we find that for spatially coherent CSDs, the CSD method yields inaccurate reconstructions due to volume-conducted contamination from currents in deeper cortical layers. An alternative approach is to “invert” a constructed forward model. The advantage of this approach is that any a priori knowledge about the geometrical and electrical properties of the tissue can be taken into account. Although several inverse methods have been proposed for LFP data, the applicability of existing electroencephalographic (EEG) and magnetoencephalographic (MEG) inverse methods to LFP data is largely unexplored. Another objective of our study therefore, is to assess the applicability of the most commonly used EEG/MEG inverse methods to Utah array data. Our main conclusion is that these inverse methods provide more accurate CSD reconstructions than the CSD method. We illustrate the inverse methods using event-related potentials recorded from primary visual cortex of a macaque monkey during a motion discrimination task. [ABSTRACT FROM AUTHOR]

Improved walking comfort has been linked with better bio-mimicking of the prosthetic ankle. This study investigated if a hydraulic ankle/foot can provide enough motion in both the sagittal and frontal planes during level and camber walking and if the hydraulic ankle/foot better mimics the biological ankle moment pattern compared with a fixed ankle/foot device. Five active male unilateral trans-femoral amputees performed level ground walking at normal and fast speeds and 2.5° camber walking in both directions using their own prostheses fitted with an “Echelon” hydraulic ankle/foot and an “Esprit” fixed ankle/foot. Ankle angles and the Trend Symmetry Index of the ankle moments were compared between prostheses and walking conditions. Significant differences between prostheses were found in the stance plantarflexion and dorsiflexion peaks with a greater range of motion being reached with the Echelon foot. The Echelon foot also showed significantly improved bio-mimicry of the ankle resistance moment in all walking conditions, either compared with the intact side of the same subject or with the “normal” mean curve from non-amputees. During camber walking, both types of ankle/foot devices showed similar changes in the frontal plane ankle angles. Results from a questionnaire showed the subjects were more satisfied with Echelon foot. [ABSTRACT FROM AUTHOR]

This paper proposes a mathematical framework for understanding how the structural changes in the COPD lung reflect in model parameters. The core of the analysis is a correlation between the heterogeneity in the lung as COPD degree changes (GOLD II, III and IV) and the nonlinearity index evaluated using the forced oscillation technique. A low frequency evaluation of respiratory impedance models and nonlinearity degree is performed since changes in tissue mechanics are related to viscoelastic properties. Simulation analysis of our model indicates a good correlation to expected changes in heterogeneity and nonlinear effects. A total of 43 COPD diagnosed patients are evaluated, distributed as GOLD II (18), GOLD III (15) and GOLD IV (10). Experimental data supports the claims and indicate that the proposed model and index for nonlinearity is well-suited to capture COPD structural changes. [ABSTRACT FROM AUTHOR]

Processes shaping the African Guineo-Congolian rain forest, especially in the West African part, are not well understood. Recent molecular studies, based mainly on forest tree species, confirmed the previously proposed division of the western African Guineo-Congolian rain forest into Upper Guinea (UG) and Lower Guinea (LG) separated by the Dahomey Gap (DG). Here we studied nine populations in the area of the DG and the borders of LG and UG of the widespread liana species, Chasmanthera dependens (Menispermaceae) by amplified fragment length polymorphism (AFLP), a chloroplast DNA sequence marker, and modelled the distribution based on current as well as paleoclimatic data (Holocene Climate Optimum, ca. 6 kyr BP and Last Glacial Maximum, ca. 22 kyr BP). Current population genetic structure and geographical pattern of cpDNA was related to present as well as historical modelled distributions. Results from this study show that past historical factors played an important role in shaping the distribution of C. dependens across West Africa. The Cameroon Volcanic Line seems to represent a barrier for gene flow in the present as well as in the past. Distribution modelling proposed refugia in the Dahomey Gap, supported also by higher genetic diversity. This is in contrast with the phylogeographic patterns observed in several rainforest tree species and could be explained by either diverging or more relaxed ecological requirements of this liana species. [ABSTRACT FROM AUTHOR]

Insulin is secreted in a pulsatile manner from multiple micro-organs called the islets of Langerhans. The amplitude and phase (shape) of insulin secretion are modulated by numerous factors including glucose. The role of phase modulation in glucose homeostasis is not well understood compared to the obvious contribution of amplitude modulation. In the present study, we measured Ca2+ oscillations in islets as a proxy for insulin pulses, and we observed their frequency and shape changes under constant/alternating glucose stimuli. Here we asked how the phase modulation of insulin pulses contributes to glucose regulation. To directly answer this question, we developed a phenomenological oscillator model that drastically simplifies insulin secretion, but precisely incorporates the observed phase modulation of insulin pulses in response to glucose stimuli. Then, we mathematically modeled how insulin pulses regulate the glucose concentration in the body. The model of insulin oscillation and glucose regulation describes the glucose-insulin feedback loop. The data-based model demonstrates that the existence of phase modulation narrows the range within which the glucose concentration is maintained through the suppression/enhancement of insulin secretion in conjunction with the amplitude modulation of this secretion. The phase modulation is the response of islets to glucose perturbations. When multiple islets are exposed to the same glucose stimuli, they can be entrained to generate synchronous insulin pulses. Thus, we conclude that the phase modulation of insulin pulses is essential for glucose regulation and inter-islet synchronization. [ABSTRACT FROM AUTHOR]

Entrainment of neural oscillations on multiple time scales is important for the perception of speech. Musical rhythms, and in particular the perception of a regular beat in musical rhythms, is also likely to rely on entrainment of neural oscillations. One recently proposed approach to studying beat perception in the context of neural entrainment and resonance (the “frequency-tagging” approach) has received an enthusiastic response from the scientific community. A specific version of the approach involves comparing frequency-domain representations of acoustic rhythm stimuli to the frequency-domain representations of neural responses to those rhythms (measured by electroencephalography, EEG). The relative amplitudes at specific EEG frequencies are compared to the relative amplitudes at the same stimulus frequencies, and enhancements at beat-related frequencies in the EEG signal are interpreted as reflecting an internal representation of the beat. Here, we show that frequency-domain representations of rhythms are sensitive to the acoustic features of the tones making up the rhythms (tone duration, onset/offset ramp duration); in fact, relative amplitudes at beat-related frequencies can be completely reversed by manipulating tone acoustics. Crucially, we show that changes to these acoustic tone features, and in turn changes to the frequency-domain representations of rhythms, do not affect beat perception. Instead, beat perception depends on the pattern of onsets (i.e., whether a rhythm has a simple or complex metrical structure). Moreover, we show that beat perception can differ for rhythms that have numerically identical frequency-domain representations. Thus, frequency-domain representations of rhythms are dissociable from beat perception. For this reason, we suggest caution in interpreting direct comparisons of rhythms and brain signals in the frequency domain. Instead, we suggest that combining EEG measurements of neural signals with creative behavioral paradigms is of more benefit to our understanding of beat perception. [ABSTRACT FROM AUTHOR]

The features of the asynchronous correlation between accident indices and the factors that influence accidents can provide an effective reference for warnings of coal mining accidents. However, what are the features of this correlation? To answer this question, data from the China coal price index and the number of deaths from coal mining accidents were selected as the sample data. The fluctuation modes of the asynchronous correlation between the two data sets were defined according to the asynchronous correlation coefficients, symbolization, and sliding windows. We then built several directed and weighted network models, within which the fluctuation modes and the transformations between modes were represented by nodes and edges. Then, the features of the asynchronous correlation between these two variables could be studied from a perspective of network topology. We found that the correlation between the price index and the accidental deaths was asynchronous and fluctuating. Certain aspects, such as the key fluctuation modes, the subgroups characteristics, the transmission medium, the periodicity and transmission path length in the network, were analyzed by using complex network theory, analytical methods and spectral analysis method. These results provide a scientific reference for generating warnings for coal mining accidents based on economic indices. [ABSTRACT FROM AUTHOR]

Complex nonlinear phenomena are investigated in a basic power system model of the single-machine-infinite-bus (SMIB) with a synchronous generator modeled by a classical third-order differential equation including both angle dynamics and voltage dynamics, the so-called flux decay equation. In contrast, for the second-order differential equation considering the angle dynamics only, it is the classical swing equation. Similarities and differences of the dynamics generated between the third-order model and the second-order one are studied. We mainly find that, for positive damping, these two models show quite similar behavior, namely, stable fixed point, stable limit cycle, and their coexistence for different parameters. However, for negative damping, the second-order system can only collapse, whereas for the third-order model, more complicated behavior may happen, such as stable fixed point, limit cycle, quasi-periodicity, and chaos. Interesting partial collapse phenomena for angle instability only and not for voltage instability are also found here, including collapse from quasi-periodicity and from chaos etc. These findings not only provide a basic physical picture for power system dynamics in the third-order model incorporating voltage dynamics, but also enable us a deeper understanding of the complex dynamical behavior and even leading to a design of oscillation damping in electric power systems. [ABSTRACT FROM AUTHOR]

Motion synchrony correlates with effective and well-rated human interaction. However, people do not remain locked in synchrony; Instead, they repeatedly enter and exit synchrony. In many important interactions, such as therapy, marriage and parent-infant communication, it is the ability to exit and then re-enter synchrony that is thought to build strong relationship. The phenomenon of entry into zero-phase synchrony is well-studied experimentally and in terms of mathematical modeling. In contrast, exit-from-synchrony is under-studied. Here, we focus on human motion coordination, and examine the exit-from-synchrony phenomenon using experimental data from the mirror game paradigm, in which people perform joint improvised motion, and from human tracking of computer-generated stimuli. We present a mathematical mechanism that captures aspects of exit-from-synchrony in human motion. The mechanism adds a random motion component when the accumulated velocity error between the players is small. We introduce this mechanism to several models for human coordinated motion, including the widely studied HKB model, and the predictor-corrector model of Noy, Dekel and Alon. In all models, the new mechanism produces realistic simulated behavior when compared to experimental data from the mirror game and from tracking of computer generated stimuli, including repeated entry and exit from zero-phase synchrony that generates a complexity of motion similar to that of human players. We hope that these results can inform future research on exit-from-synchrony, to better understand the dynamics of coordinated action of people and to enhance human-computer and human-robot interaction. [ABSTRACT FROM AUTHOR]

The frequency, magnitude, and size of forest disturbances are increasing globally. Much recent research has focused on how the occurrence of one disturbance may affect susceptibility to subsequent disturbances. While much has been learned about such linked disturbances, the strength of the interactions is likely to be contingent on the severity of disturbances as well as climatic conditions, both of which can affect disturbance intensity and tree resistance to disturbances. Subalpine forests in western Colorado were affected by extensive and severe wildfires in the late 19th century and an extensive and severe outbreak of spruce beetle (Dendroctonus rufipennis) in the 1940s. Previous research found that most, but not all, of the stands that burned and established following the late 19th century fires were not susceptible to the 1940s outbreak as beetles preferentially attack larger trees and stands in advanced stages of development. However, previous research also left open the possibility that some stands that burned and established following the 19th century fires may have been attacked during the 1940s outbreak. Understanding how strongly stand structure, as shaped by disturbances of varying severity, affected susceptibility to past outbreaks is important to provide a baseline for assessing the degree to which recent climate change may be relaxing the preferences of beetles for larger trees and for stands in latter stages of structural development and thereby changing the nature of linked disturbances. Here, dendroecological methods were used to study disturbance history and tree age of stands in the White River National Forest in Western Colorado that were identified in historical documents or remotely-sensed images as having burned in the 19th century and having been attacked by spruce beetle in the 1940s. Dendroecological reconstructions indicate that in young post-fire stands only old remnant trees that survived the otherwise stand-replacing fires were killed in the 1940s outbreak. No young post-fire trees (< ca. 128 years) were susceptible to the 1940s outbreak, implying that under the relatively cool and wet conditions of the mid-20th century, susceptibility to and spatial patterns of spruce beetle outbreak were most likely controlled by variations in severity of prior disturbance by fire. This study provides a baseline for comparing linked disturbances under the relatively warmer and drier conditions of recent (e.g. post-1990) outbreaks in order to assess how climate mitigates the degree to which pre-disturbance history and structure affect susceptibility to disturbances. [ABSTRACT FROM AUTHOR]

Background The mouse is the most commonly used animal model in biomedical research because of recent advances in molecular genetic techniques. Studies related to eye movement in mice are common in fields such as ophthalmology relating to vision, neuro-otology relating to the vestibulo-ocular reflex (VOR), neurology relating to the cerebellum's role in movement, and psychology relating to attention. Recording eye movements in mice, however, is technically difficult. Methods We developed a new algorithm for analyzing the three-dimensional (3D) rotation vector of eye movement in mice using high-speed video-oculography (VOG). The algorithm made it possible to analyze the gain and phase of VOR using the eye's angular velocity around the axis of eye rotation. Results When mice were rotated at 0.5 Hz and 2.5 Hz around the earth's vertical axis with their heads in a 30° nose-down position, the vertical components of their left eye movements were in phase with the horizontal components. The VOR gain was 0.42 at 0.5 Hz and 0.74 at 2.5 Hz, and the phase lead of the eye movement against the turntable was 16.1° at 0.5 Hz and 4.88° at 2.5 Hz. Conclusions To the best of our knowledge, this is the first report of this algorithm being used to calculate a 3D rotation vector of eye movement in mice using high-speed VOG. We developed a technique for analyzing the 3D rotation vector of eye movements in mice with a high-speed infrared CCD camera. We concluded that the technique is suitable for analyzing eye movements in mice. We also include a C++ source code that can calculate the 3D rotation vectors of the eye position from two-dimensional coordinates of the pupil and the iris freckle in the image to this article. [ABSTRACT FROM AUTHOR]

While perceptual learning increases objective sensitivity, the effects on the constant interaction of the process of perception and its metacognitive evaluation have been rarely investigated. Visual perception has been described as a process of probabilistic inference featuring metacognitive evaluations of choice certainty. For visual motion perception in healthy, naive human subjects here we show that perceptual sensitivity and confidence in it increased with training. The metacognitive sensitivity–estimated from certainty ratings by a bias-free signal detection theoretic approach–in contrast, did not. Concomitant 3Hz transcranial alternating current stimulation (tACS) was applied in compliance with previous findings on effective high-low cross-frequency coupling subserving signal detection. While perceptual accuracy and confidence in it improved with training, there were no statistically significant tACS effects. Neither metacognitive sensitivity in distinguishing between their own correct and incorrect stimulus classifications, nor decision confidence itself determined the subjects’ visual perceptual learning. Improvements of objective performance and the metacognitive confidence in it were rather determined by the perceptual sensitivity at the outset of the experiment. Post-decision certainty in visual perceptual learning was neither independent of objective performance, nor requisite for changes in sensitivity, but rather covaried with objective performance. The exact functional role of metacognitive confidence in human visual perception has yet to be determined. [ABSTRACT FROM AUTHOR]