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The brain is understood as an intricate biological system composed of numerous elements. It is susceptible to various physical and chemical influences, including temperature. The literature extensively explores the conditions that influence synapses in the context of cellular communication. However, the understanding of how the brain's global physical conditions can modulate ephaptic communication remains limited due to the poorly understood nature of ephapticity. This study proposes an adaptation of the Hodgkin and Huxley (HH) model to investigate the effects of ephaptic entrainment in response to thermal changes (HH-E). The analysis focuses on two distinct neuronal regimes: subthreshold and suprathreshold. In the subthreshold regime, circular statistics are used to demonstrate the dependence of phase differences with temperature. In the suprathreshold regime, the Inter-Spike Interval are employed to estimate phase preferences and changes in the spiking pattern. Temperature influences the model's ephaptic interactions and can modify its preferences for spiking frequency, with the direction of this change depending on specific model conditions and the temperature range under consideration. Furthermore, temperature enhance the anti-phase differences relationship between spikes and the external ephaptic signal. In the suprathreshold regime, ephaptic entrainment is also influenced by temperature, especially at low frequencies. This study reveals the susceptibility of ephaptic entrainment to temperature variations in both subthreshold and suprathreshold regimes and discusses the importance of ephaptic communication in the contexts where temperature may plays a significant role in neural physiology, such as inflammatory processes, fever, and epileptic seizures. [ABSTRACT FROM AUTHOR]

We show how the maximum of recurrence-microstates entropy configures a new way to properly compute appropriate recurrence vicinity parameter and time sampling to perform recurrence analysis of continuous data. For experimental data, we show the same procedure may be used to find the optimum sampling or to perform down-sampling of the data, preserving recurrence meaning and adjusting the ideal sampling. The new method retrieves results obtained using traditional methods with the advantage of being independent of any free parameter, since all parameter dependencies are automatically set. Our results are also less sensitive to noise when experimental data are used. Due to the automatized way to capture suitable recurrence parameters, the method is adequate for using in autonomous numerical algorithms, allowing the recovery of relevant recurrence information embedded in time series (including over-sampled data), rationalizing the process of data acquisition and allowing only relevant data to be collected. [ABSTRACT FROM AUTHOR]

The brain is commonly understood as a complex network system with a particular organization and topology that can result in specific electrophysiological patterns. Among all the dynamic elements resulting from the circuits of the brain's network, ephapticity is a cellular communication mechanism that has received little attention. To understand the network's properties of ephaptic entrainment, we start investigating the ephaptic effect on a single neuron. In this study, we used numerical simulations to examine the relationship between alterations in ephaptic neuronal entrainment and impaired electrophysiological properties of the neuronal membrane, which can occur via spike field coherence (SFC). This change in frequency band amplitude is observed in some neurodegenerative diseases, such as Parkinson's or Alzheimer's. To further investigate these phenomena, we proposed a damaged model based on the impairment of both the resistance of the ion channels and the capacitance of the lipid membrane. Therefore, we simulated ephaptic entrainment with the hybrid neural model quadratic integrate-and-fire ephaptic (QIF-E), which mimics an ephaptic entrainment generated by an LFP (simulate a neuronal group). Our results indicate a link between peak entrainment (ephapticity) preference and a shift in frequency band when damage occurs mainly in ion channels. Finally, we discuss possible relationships between ephaptic entrainment and neurodegenerative diseases associated with aging factors. [ABSTRACT FROM AUTHOR]

Inverse problems are challenging in several ways, and we cite the non-linearity and the presence of non-Gaussian noise. Least squared is the standard method to construct a equivalent functional for optimization, which is equivalent to the L2 norm of the misfit. Alternative norms in the optimization process are an useful strategy in the inverse problem solution. Generalized statistics can be present at two sides of the inverse problem: in the noise that pollutes the data and in the norm used in the optimization algorithm. With help of a seismic problem, we polluted the signal with a q-exponential noise (using an exponent q noise ) and subsequently inverted the problem using a norm associated to a q-exponential (with an exponent q inv ). The same procedure was also applied to the simpler problem of a linear fitting. We tested the hypothesis of a relation between the exponents q noise and q inv . The overall pattern observed is the following: inversion error are smaller for low q noise and high q inv . In contrast, the worst inversion is found for high polluting noise (far from Gaussian noise) and for inversion with low q inv (close to the Gaussian case). [ABSTRACT FROM AUTHOR]

In recent decades, there has been a growing interest in the impact of electric fields generated in the brain. Transmembrane ionic currents originate electric fields in the extracellular space and are capable of affecting nearby neurons, a phenomenon called ephaptic neuronal communication. In the present work, the Quadratic Integrated-and-Fire model (QIF-E) underwent an adjustment/improvement to include the ephaptic entrainment behavior between neurons and electric fields. Indeed, the aim of our study is to validate the QIF-E model, which is a model to estimate the influence of electric fields on neurons. For this purpose, we evaluated whether the main properties observed in an experiment by Anastassiou et al. (Nat Neurosci 14:217–223, 2011), which analyzed the effect of an electric field on cortical pyramidal neurons, are reproduced with the QIF-E model. In this way, the analysis tools are employed according to the neuronal activity regime: (i) for the subthreshold regime, the circular statistic is used to describe the phase differences between the input stimulus signal (electrode) and the modeled membrane response; (ii) in the suprathreshold regime, the Population Vector and the Spike Field Coherence are used to estimate phase preferences and the entrainment intensity between the input stimulus and Action Potentials. The results observed are (i) in the subthreshold regime the values of the phase differences change with distinct frequencies of the input stimulus; (ii) in the supra-threshold regime the preferential phase of Action Potentials changes for different frequencies. In addition, we explore other parameters of the model, such as noise and membrane characteristic-time, in order to understand different types of neurons and extracellular environment related to ephaptic communication. Such results are consistent with results observed in empirical experiments based on ephaptic phenomenon. In addition, the QIF-E model allows further studies on the physiological importance of ephaptic communication in the brain, and its simplicity may open a door to simulate the ephaptic response in neuronal networks and assess the impact of ephaptic communication in such scenarios. [ABSTRACT FROM AUTHOR]

Ants use chemical, visual, magnetic and/or solar cues during foraging activity. Orientation is important, since foragers need to return to the nest. In this study, we analyze the maze performance of the Dinoponera quadriceps using chemical and visual cues to study spatial orientation. We used a white maze with seventeen chambers and we allowed the ants to explore for ten minutes in each session. Six treatments performed by manipulating presence or absence of chemical and visual cues. Two treatments occurred in the presence and absence of odor, but without visual cues. In four treatments, we introduced visual cues, in two upper visual cues and in two frontal visual cues, both with and without odor. Our results showed that both chemical and visual cues improve maze performance during ant movement to the food source and to the nest. We suggest bimodal navigation in D. quadriceps. The association of multiple cues (chemical and visual) improves workers navigation performance, which probably enhances foraging rate and individual fitness. [ABSTRACT FROM AUTHOR]

Population abundance data are often used to define species' conservation status. Abundance of marine turtles is typically estimated using nesting beach monitoring data such as nest counts and clutch frequency (CF, i.e., the number of nests female turtles lay within a nesting season). However, studies have shown that CF determined solely from nesting beach monitoring data can be underestimated, leading to inaccurate abundance estimates. To obtain reliable estimates of CF for hawksbill turtles in northeastern Brazil (6.273356° S, 35.036271° W), the region with the highest nesting density in the South Atlantic, data from beach monitoring and satellite telemetry were combined from 2014 to 2019. Beach monitoring data indicated the date of first nesting event, while state-space modeling of satellite telemetry data indicated the departure date of turtles, allowing calculations of residence length at breeding site and CF estimates based on internesting intervals. Females were estimated to nest up to six times within the nesting season with CF estimates between 4.5 and 4.8 clutches per female. CF estimates were used to determine the number of nesting females at the study site based in two approaches: considering and not considering transient turtles. Our approach and findings highlight that transients heavily influence CF estimates and need for reconsideration of how this key parameter is commonly determined for marine turtle populations and the use of beach monitoring data and satellite telemetry for estimations of CF. [ABSTRACT FROM AUTHOR]

Full-waveform inversion (FWI) is a powerful methodology employed in estimating subsurface physical parameters. FWI is classically formulated as a data-fitting problem based on minimizing the squared l 2 -norm of the difference between the observed data and modeled data (i.e., the data residuals or errors). The FWI based on l 2 -norm (hereafter classical FWI) stems from the assumption that the errors follow a Gaussian probability distribution. However, since, in most cases the error is non-Gaussian for non-linear problems and therefore, the classical FWI tends to fail. In this work, we consider the Tsallis q-deformation of the exponential function, which is widely used in the field of statistical physics, to derive an alternative misfit function to mitigate the FWI sensitivity to spurious measurements (outliers). In this regard, we formulated the FWI from a q-generalization of the Laplace probability distribution (or q-Laplace distribution). Application on a typical Brazilian pre-salt velocity model with an acoustic synthetic noisy-data is presented, in which we compare the performance of our proposal against the classical FWI. In addition, we compare also our methodology with the robust misfit function based on l 1 -norm, which is based on the Laplace distribution. The results show that our proposal outperforms classical FWI, and also the robust FWI based on l 1 -norm. The results also reveal that our proposal accelerates the data inversion process when the data is polluted by outliers. [ABSTRACT FROM AUTHOR]

The inference of physical parameters from measured data is essential for describing and analysing several complex systems. In this regard, the inverse problem theory has been applied to solve this task based on the Boltzmann–Gibbs statistical mechanics by considering that the errors are Gaussian-like. However, in the non-Gaussian noise case, the classical inverse-problem approach estimates model parameters which may be inaccurate and grossly biased. In the case of extreme outliers in the data set, for example, the most common approach used is based on the l 1 -norm of the difference between modelled and observed data. This approach is famous for being robust because it is based on a long-tailed probability function: the Laplace distribution. However, l 1 -norm-based inverse problems equally weight noise and information, which limits its robustness to a large number of outliers in the data set. To mitigate the limitations of the l 1 -norm approach, we introduce in this work the inverse problem theory in the context of Tsallis and Kaniadakis generalised statistical mechanics, by generalising the Laplace distribution. Applications to a classical geophysical data-inversion problem demonstrate that inverse problems based on Tsallis q- and Kaniadakis κ -statistics outperform the classical and l 1 -norm-based frameworks. They also reveal that the best results are associated with the limit in which both generalised distributions are equivalent. [ABSTRACT FROM AUTHOR]

The problem of inferencing parameters of complex systems from measured data has been extensively studied based on the inverse problem theory. Classically, an inverse problem is formulated as an optimisation task in which the objective function is based on the maximisation of Boltzmann–Gibbs entropy under appropriate constraints. In this classical framework, errors are assumed to follow a Gaussian-behaviour. However, in many situations, the errors are non-Gaussian and therefore the classical approach is predestined to failure. To mitigate the inverse-problem sensitivity to non-Gaussian errors, we have considered in this study a q-generalised objective function within the context of nonextensive statistical mechanics. In this regard, the errors are assumed to follow the q-Gaussian distribution, which arises from the maximisation of the nonadditive Tsallis entropy. We study the robustness properties of the q-objective function, which is a generalisation of the classical objective function, through the so-called influence function. In this work, we analyse and discuss from an analytical and numerical perspective, the role of the entropic index (q) of Tsallis entropy on the effectiveness and robustness in the inference of physical parameters from with strongly noisy-data. In this perspective, we show that exists an optimum value for the entropic index at the limit q → 3 , which implies in δ q = 3 - q ≈ 0 in the q-objective function. To validate our proposal, we consider a classic geophysical inverse problem by employing a realistic geological model and a data set contaminated by spikes. [ABSTRACT FROM AUTHOR]

The physical analysis of earthquakes is essential for the exploration of the interior structure of a region. Nowadays, the statistics of earthquakes' occurrence are dominated by the Gutenberg–Richter (GR) law. Here, we report evidence of the similarity between earthquakes and marsquakes by using the generalized GR law in the context of Tsallis nonextensive statistical mechanics. We analyze the Martian quakes that were recorded by the InSight's seismometer in the Elysium Planitia region, Mars, from January 2019 to December 2019, which corresponds to the first year of geophysical observations by Nasa's InSight mission. The results show evidence for the similarity between the triggering mechanism of earthquakes and marsquakes. They also reveal the fractal nature of the Martian geological faults. [ABSTRACT FROM AUTHOR]

Many complex systems, from earthquakes and financial markets to Barkhausen effect in ferromagnetic materials, respond with a noise consisting of discrete avalanche-like events with broad range of sizes and durations, separated by waiting times. Here we focus on the waiting-time statistics in magnetic systems. By investigating the Barkhausen noise in amorphous and polycrystalline ferromagnetic films having different thicknesses, we uncover the form of the waiting-time distribution in time series recorded from the irregular and irreversible motion of magnetic domain walls. Further, we address the question of if the waiting-time distribution evolves with the threshold level, as well as with the film thickness and structural character of the materials. Our results, besides informing on the temporal avalanche correlations, disclose the waiting-time statistics in magnetic systems also bring fingerprints of the universality classes of Barkhausen avalanches and a dimensional crossover in the domain wall dynamics. [ABSTRACT FROM AUTHOR]

The behavior of sea turtle species can be influenced by the lunar cycle, possibly due to moonlight variability. We analyzed the relationship between nesting behavior and moon phase using nesting hawksbill turtle records for beaches in Northeast Brazil for the 2006–2007 to 2015–2016 seasons. The total number of records was 4807, while the total number with time point registration was 1031. The Eretmochelys imbricata inter-nesting period was approximately half the lunar cycle; we therefore expected nesting phase synchronization with lunar phases within each season. We computed the lunar angle for the hawksbill records, and the Kuiper test for uniformity indicated that the species shows some lunar phase preferences. We observed that oviposition at the first and last quarters of the moon is more frequent than at full moon or new moon phases. We also computed the lunar angle throughout several seasons for remigrant turtles and found an absence of preferential lunar phase across different seasons. This indicates that the hawksbill does not choose a lunar phase previously chosen in other nesting seasons. We analyzed the relationship between the presence of the moon in the sky and nesting turtles, and, in sequence, compared the records of false crawls and nest crawls; no relation was found between these variables. [ABSTRACT FROM AUTHOR]

The Small-World Network on a Sphere SWNS is a non-crossing network that has no hubs and presents the small-world property diam ~ log N with diam being the maximal distance between any two vertices and N being the number of vertices. The SWNS is constructed using a partition of the sphere and the parallels are regular sections of the sphere with constant latitude. The number of cells on the parallels, however, increases exponentially from the pole to the equator of the sphere. We analytically compute the distribution of connectivity, the clustering coefficient and the SWNS distances. The resilience of the model against selective attacks is also discussed. [ABSTRACT FROM AUTHOR]

Classical models of phytoplankton–zooplankton interaction show that with nutrient enrichment such systems may abruptly shift from limit cycles to stable phytoplankton domination due to zooplankton predation by planktivorous fish. Such models assume that planktivorous fish eat only zooplankton, but there are various species of filter-feeding fish that may also feed on phytoplankton. Here, we extend these classical models to systematically explore the effects of omnivory by planktivorous fish. Our analysis indicates that if fish forage on phytoplankton in addition to zooplankton, the alternative attractors predicted by the classical models disappear for all realistic parameter settings, even if omnivorous fish have a strong preference for zooplankton. Our model also shows that the level of fish biomass above which zooplankton collapse should be higher when fish are omnivorous than when fish are zooplanktivorous. We also used the model to explore the potential effects of the now increasingly common practice of stocking lakes with filter-feeding fish to control cyanobacteria. Because omnivorous filter-feeding fish forage on phytoplankton as well as on the main grazers of phytoplankton, the net effect of such fish on the phytoplankton biomass is not obvious. Our model suggests that there may be a unimodal relationship between the biomass of omnivorous filter-feeding fish and the biomass of phytoplankton. This implies that to manage for reductions in phytoplankton biomass, heavy stocking or strong reduction of such fish is best. [ABSTRACT FROM AUTHOR]