Lessons from being challenged by COVID-19.

We present results of different approaches to model the evolution of the COVID-19 epidemic in Argentina, with a special focus on the megacity conformed by the city of Buenos Aires and its metropolitan area, including a total of 41 districts with over 13 million inhabitants. We first highlight the relevance of interpreting the early stage of the epidemic in light of incoming infectious travelers from abroad. Next, we critically evaluate certain proposed solutions to contain the epidemic based on instantaneous modifications of the reproductive number. Finally, we build increasingly complex and realistic models, ranging from simple homogeneous models used to estimate local reproduction numbers, to fully coupled inhomogeneous (deterministic or stochastic) models incorporating mobility estimates from cell phone location data. The models are capable of producing forecasts highly consistent with the official number of cases with minimal parameter fitting and fine-tuning. We discuss the strengths and limitations of the proposed models, focusing on the validity of different necessary first approximations, and caution future modeling efforts to exercise great care in the interpretation of long-term forecasts, and in the adoption of non-pharmaceutical interventions backed by numerical simulations.

The Physics of Birdsong Production.

Human babies need to learn how to talk. The need of a tutor to achieve acceptable vocalizations is a feature that we share with a few species in the animal kingdom. Among those are Songbirds, which account for nearly half of the known bird species. For that reason, Songbirds have become an ideal animal model to study how a brain reconfigures itself during the process of learning a complex task. In the last years, neuroscientists have invested important resources in order to unveil the neural architecture involved in birdsong production and learning. Yet, behavior emerges from the interaction between a nervous system, a peripheral biomechanical architecture and environment, and therefore its study should be just as integrated. In particular, the physical study of the avian vocal organ can help to elucidate which features found in the song of birds are under direct control of specific neural instructions and which emerge from the biomechanics involved in its generation. This work describes recent advances in the study of the physics of birdsong production.

New perspectives on the physics of birdsong.

In this work, we revisit the path that has been travelled during the last few years towards the modelling of the avian vocal organ, the syrinx, using numerical and theoretical techniques from bifurcation theory as analysing tools and present experimental support for the models. This fruitful perspective allowed the retracing of many acoustic features of syllables to intrinsic properties of the syrinx, thereby relocating the bird phonatory organ from the role of a mere vocal instrument of the nervous system to a central source of complex acoustical behaviour.

Dynamical origin of spectrally rich vocalizations in birdsong.

Birdsong is a model system for learned vocal behavior with remarkable parallels to human vocal development and sound production mechanisms. Upper vocal tract filtering plays an important role in human speech, and its importance has recently also been recognized in birdsong. However, the mechanisms of how the avian sound source might contribute to spectral richness are largely unknown. Here we show in the most widely studied songbird, the zebra finch (Taeniopygia guttata), that the broad range of upper harmonic content in different low-frequency song elements is the fingerprint of the dynamics displayed by its vocal apparatus, which can be captured by a two-dimensional dynamical model. As in human speech and singing, the varying harmonic content of birdsong is not only the result of vocal tract filtering but of a varying degree of tonality emerging from the sound source. The spectral content carries a strong signature of the intrinsic dynamics of the sound source.

Lateralization as a symmetry breaking process in bird song.

The singing by songbirds is a most convincing example in the animal kingdom of functional lateralization of the brain, a feature usually associated with human language. Lateralization is expressed as one or both of the bird's sound sources being active during the vocalization. Normal songs require high coordination between the vocal organ and respiratory activity, which is bilaterally symmetric. Moreover, the physical and neural substrate used to produce the song lack obvious asymmetries. In this work we show that complex spatiotemporal patterns of motor activity controlling airflow through the sound sources can be explained in terms of spontaneous symmetry breaking bifurcations. This analysis also provides a framework from which to study the effects of imperfections in the system's symmetries. A physical model of the avian vocal organ is used to generate synthetic sounds, which allows us to predict acoustical signatures of the song and compare the predictions of the model with experimental data.

Dynamical systems techniques reveal the sexual dimorphic nature of motor patterns in birdsong.

In this work we analyze the pressure motor patterns used by canaries (Serinus canaria) during song, both in the cases of males and testosterone treated females. We found a qualitative difference between them which was not obvious from the acoustical features of the uttered songs. We also show the diversity of patterns, both for males and females, to be consistent with a recently proposed model for the dynamics of the oscine respiratory system. The model not only allows us to reproduce qualitative features of the different pressure patterns, but also to account for all the diversity of pressure patterns found in females.

Respiratory patterns in oscine birds during normal respiration and song production.

In this work we study the generation of respiratory patterns by oscine birds. We present a model capable of generating realistic respiratory patterns, during normal respiration and song production. The model accounts for the interaction between neural nuclei and air sac dynamics. We performed experiments in vivo in order to test the predictions of the model, measuring air sac pressure during song and normal respiration in canaries (Serinus canaria).

Synthesizing bird song.

In this work we present an electronic syrinx: an analogical integrator of the equations describing a model for sound production by oscine birds. The model depends on time varying parameters with clear biological interpretation: the air sac pressure and the tension of ventral syringeal muscles. We test the hypothesis that these physiological parameters can be reconstructed from the song. In order to do so, we built two transducers. The input for these transducers is an acoustic signal. The first transducer generates an electric signal that we use to reconstruct the bronchial pressure. The second transducer allows us to reconstruct the syringeal tension (in both cases, for the time intervals where phonation takes place). By driving the electronic syrinx with the output of the transducers we generate synthetic song. Important qualitative features of the acoustic input signal are reproduced by the synthetic song. These devices are especially useful to carry out altered feedback experiences, and applications as biomimetic resources are discussed.

Simple neural substrate predicts complex rhythmic structure in duetting birds.

Horneros (Furnarius Rufus) are South American birds well known for their oven-looking nests and their ability to sing in couples. Previous work has analyzed the rhythmic organization of the duets, unveiling a mathematical structure behind the songs. In this work we analyze in detail an extended database of duets. The rhythms of the songs are compatible with the dynamics presented by a wide class of dynamical systems: forced excitable systems. Compatible with this nonlinear rule, we build a biologically inspired model for how the neural and the anatomical elements may interact to produce the observed rhythmic patterns. This model allows us to synthesize songs presenting the acoustic and rhythmic features observed in real songs. We also make testable predictions in order to support our hypothesis.

Dynamics of learning in coupled oscillators tutored with delayed reinforcements.

In this work we analyze the solutions of a simple system of coupled phase oscillators in which the connectivity is learned dynamically. The model is inspired by the process of learning of birdsongs by oscine birds. An oscillator acts as the generator of a basic rhythm and drives slave oscillators which are responsible for different motor actions. The driving signal arrives at each driven oscillator through two different pathways. One of them is a direct pathway. The other one is a reinforcement pathway, through which the signal arrives delayed. The coupling coefficients between the driving oscillator and the slave ones evolve in time following a Hebbian-like rule. We discuss the conditions under which a driven oscillator is capable of learning to lock to the driver. The resulting phase difference and connectivity are a function of the delay of the reinforcement. Around some specific delays, the system is capable of generating dramatic changes in the phase difference between the driver and the driven systems. We discuss the dynamical mechanism responsible for this effect and possible applications of this learning scheme.

Limits on the excitable behavior of a semiconductor laser with optical feedback.

Recently, it was proposed that semiconductor lasers with optical feedback present a complex behavior that can be described as noise driven excitable. In this work we investigate in which region of parameter space this description is adequate. We conclude that the region of the parameter space in which the system displays noise driven excitable behavior is a subset of the region in which presents low frequency fluctuations.

Experimental support for a model of birdsong production.

In this work we present an experimental validation of a recently proposed model for the production of birdsongs. We have previously observed that driving the model with simple functions of time, which represent tensions in vocal muscles, produces a wide variety of sounds resembling birdsongs. In this work we drive the model with functions whose time dependence comes from recordings of muscle activities and air sac pressure. We simultaneously recorded the birds' songs and compared them with the synthetic songs. The model produces recognizable songs. Beyond finding a qualitative agreement, we also test some predictions of the model concerning the relative levels of activity in the gating muscles at the beginning and end of a syllable.

Electronic neuron within a ganglion of a leech (Hirudo medicinalis).

We report the construction of an electronic device that models and replaces a neuron in a midbody ganglion of the leech Hirudo medicinalis. In order to test the behavior of our device, we used a well-characterized synaptic interaction between the mechanosensory, sensitive to pressure, (P) cell and the anteropagoda (because of the action potential shape) (AP) neuron. We alternatively stimulated a P neuron and our device connected to the AP neuron, and studied the response of the latter. The number and timing of the AP spikes were the same when the electronic parameters were properly adjusted. Moreover, after changes in the depolarization of the AP cell, the responses under the stimulation of both the biological neuron and the electronic device vary in a similar manner.

Topologically inequivalent orbits induced by noise.

In this Letter we extend the concept of stochastic resonance. We show that in forced excitable systems noise can be responsible for the appearance of recurrences presenting a robust topological organization inequivalent to the periodic orbits of the deterministic system. As in stochastic resonance, these new structures are most pronounced at an optimal noise intensity.

Biorthogonal decomposition techniques unveil the nature of the irregularities observed in the solar cycle.

We present a biorthogonal decomposition of the temporal and latitudinal distribution of sunspots recorded since 1874. We show that the butterfly diagrams can be interpreted as the result of approximately constant amplitudes and phases of two oscillations with periods close to 22 years. Our analysis reveals clear evidence of the absence of low-dimensional chaos, at least for the time scales that can be analyzed with this database. This result suggests that the spatiotemporal irregularities observed in the solar cycle are due to the superposition of regular structures with a stochastic background.

Generic two-variable model of excitability.

We present a simple model that displays all classes of two-dimensional excitable regimes. One of the variables of the model displays the usual spikes observed in excitable systems. Since the model is written in terms of a "standard" vector field, it is always possible to fit it to experimental data displaying spikes in an algorithmic way. In fact, we use it to fit a series of membrane potential recordings obtained in the medicinal leech and time series generated with the FitzHugh-Nagumo equations and the excitability model of Eguía et al. [Phys. Rev. E 58, 2636 (1998)]. In each case, we determine the excitability class of the corresponding system.

Computing with excitable systems in a noisy environment.

In this work we show that excitable units with biologically inspired couplings are capable of performing any logic operation in a noisy environment without synchronization.

Continuous model for vocal fold oscillations to study the effect of feedback.

In this work we study the effects of delayed feedback on vocal fold dynamics. To perform this study, we work with a vocal fold model that is made as simple as possible while retaining the spectral content characteristic of human vocal production. Our results indicate that, even with the simplest explanation for vocal fold oscillation, delayed feedback due to reflected sound in the vocal tract can lead to extremely rich dynamics.

Simple motor gestures for birdsongs.

We present a model of sound production in a songbird's vocal organ and find that much of the complexity of the song of the canary (Serinus canaria) can be produced from simple time variations in forcing functions. The starts, stops, and pauses between syllables, as well as variation in pitch and timbre are inherent in the mechanics and can often be expressed through smooth and simple variations in the frequency and relative phase of two driving parameters

Unveiling the topological structure of chaotic flows from data.

We report the analysis of branched manifolds through homologies, in order to extend the range of applicability of the topological approach to the analysis of chaotic data. Analytic and numerical cases are discussed.