Lattice Model for Influenza Spreading with Spontaneous Behavioral Changes

Individual behavioral response to the spreading of an epidemic plays a crucial role in the progression of the epidemic itself. The risk perception induces individuals to adopt a protective behavior, as for instance reducing their social contacts, adopting more restrictive hygienic measures or undergoing prophylaxis procedures. In this paper, starting with a previously developed lattice-gas SIR model, we construct a coupled behavior-disease model for influenza spreading with spontaneous behavioral changes. The focus is on self-initiated behavioral changes that alter the susceptibility to the disease, without altering the contact patterns among individuals. Three different mechanisms of awareness spreading are analyzed: the local spreading due to the presence in the neighborhood of infective individuals; the global spreading due to the news published by the mass media and to educational campaigns implemented at institutional level; the local spreading occurring through the “thought contagion” among aware and unaware individuals. The peculiarity of the present approach is that the awareness spreading model is calibrated on available data on awareness and concern of the population about the risk of contagion. In particular, the model is validated against the A(H1N1) epidemic outbreak in Italy during the season, by making use of the awareness data gathered by the behavioral risk factor surveillance system (PASSI). We find that, increasing the accordance between the simulated awareness spreading and the PASSI data on risk perception, the agreement between simulated and experimental epidemiological data improves as well. Furthermore, we show that, within our model, the primary mechanism to reproduce a realistic evolution of the awareness during an epidemic, is the one due to globally available information. This result highlights how crucial is the role of mass media and educational campaigns in influencing the epidemic spreading of infectious diseases.     

Emerging model systems in evo-devo: cavefish and microevolution of development

SUMMARY Cavefish and their conspecific surface-dwelling ancestors ( Astyanax mexicanus ) are emerging as a model system to study the microevolution of development. Here we describe attributes that make this system highly promising for such studies. We review how the Astyanax system is being used to understand evolutionary forces underlying loss of eyes and pigmentation in cavefish. Pigment regression is probably explained by neutral mutations, whereas natural selection is a likely mechanism for loss of eyes. Finally, we discuss several research frontiers in which Astyanax is poised to make significant contributions in the future: evolution of constructive traits, the craniofacial skeleton, the central nervous system, and behavior.     

Feather evolution exemplifies sexually selected bridges across the adaptive landscape

Over the last two decades, paleontologists have pieced together the early evolutionary history of feathers. Simple hair‐like feathers served as insulating pelage, but the first feathers with complex branching structures and a plainer form evolved for the purpose of sexual display. The evolution of these complex display feathers was essential to the later evolution of flight. Feathers illustrate how sexual selection can generate complex novel phenotypes, which are then available for natural selection to modify and direct toward novel functions. In the longstanding metaphor of the adaptive landscape, sexual selection is a means by which lineages resting on one adaptive peak may gradually bridge a gap to another peak, without the landscape itself being first altered by environmental changes.     

Patterning the protochordate neural tube

The complex vertebrate nervous system has evolved from a simpler nervous system such as that seen in present-day protochordates. Through a recent accumulation of gene-expression data, together with fine anatomical studies, we are now able to identify both how the neural tube was patterned when it first evolved and what is truly novel in the vertebrate neural tube. We are entering a new era in the understanding of how the evolution of novel vertebrate structures is linked to genetic evolution.     

Modelling the spread of European buckthorn in the Region of Waterloo

Established invasive species, such as European buckthorn (Rhamnus cathartica), pose a challenging problem for land managers who must decide when and how to control them. In order to make an informed decision land managers need to be able to predict the spread of these invasive species at local scales and without the need for excessive sampling. Our approach uses a hybrid model, combining habitat suitability and the presence of the invasive in neighbouring cells to predict the probability of a cell being invaded over time. A generalized linear mixed-effects model was used to create a habitat suitability model and a spread model. The habitat suitability model predicts the presence of buckthorn based on environmental characteristics and the results are used in the spread model. The spread model indicates that the invasion of buckthorn is influenced by the suitability of habitat and the presence of buckthorn in neighbouring cells. The success of the spread model suggests that this approach can be used to create a spatiotemporally explicit model with limited sampling effort.     

Rules of retinotectal mapmaking

The selective connections that nerve cells make to each other and to effector and receptor cells outside the nervous system are essential to organized behavior. The retinotectal projection has been used frequently in the experimental investigation of how such patterned sets of connections are formed. This article traces the evolution of some of the dominant experimental paradigms and concepts that have resulted in the currently accepted rules underlying the retinotectal map.     

The remapping of space in motor learning and human–machine interfaces

Studies of motor adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. One of the most fundamental elements of our environment is space itself. This article focuses on the notion of Euclidean space as it applies to common sensory motor experiences. Starting from the assumption that we interact with the world through a system of neural signals, we observe that these signals are not inherently endowed with metric properties of the ordinary Euclidean space. The ability of the nervous system to represent these properties depends on adaptive mechanisms that reconstruct the Euclidean metric from signals that are not Euclidean. Gaining access to these mechanisms will reveal the process by which the nervous system handles novel sophisticated coordinate transformation tasks, thus highlighting possible avenues to create functional human–machine interfaces that can make that task much easier. A set of experiments is presented that demonstrate the ability of the sensory-motor system to reorganize coordination in novel geometrical environments. In these environments multiple degrees of freedom of body motions are used to control the coordinates of a point in a two-dimensional Euclidean space. We discuss how practice leads to the acquisition of the metric properties of the controlled space. Methods of machine learning based on the reduction of reaching errors are tested as a means to facilitate learning by adaptively changing he map from body motions to controlled device. We discuss the relevance of the results to the development of adaptive human–machine interfaces and optimal control.     

Making connections in the inner ear: Recent insights into the development of spiral ganglion neurons and their connectivity with sensory hair cells

In mammals, auditory information is processed by the hair cells (HCs) located in the cochlea and then rapidly transmitted to the CNS via a specialized cluster of bipolar afferent connections known as the spiral ganglion neurons (SGNs). Although many anatomical aspects of SGNs are well described, the molecular and cellular mechanisms underlying their genesis, how they are precisely arranged along the cochlear duct, and the guidance mechanisms that promote the innervation of their hair cell targets are only now being understood. Building upon foundational studies of neurogenesis and neurotrophins, we review here new concepts and technologies that are helping to enrich our understanding of the development of the nervous system within the inner ear.     

Decisions,decisions, decisions: choosing a biological science of choice

Behavioral ecologists argue that evolution drives animal behavior to efficiently solve the problems animals face in their environmental niches. The ultimate evolutionary causes of decision making, they contend, can be found in economic analyses of organisms and their environments. Neurobiologists interested in how animals make decisions have, in contrast, focused their efforts on understanding the neurobiological hardware that serves as a more proximal cause of that same behavior. Describing the flow of information within the nervous system without regard to these larger goals has been their focus. Recent work in a number of laboratories has begun to suggest that these two approaches are beginning to fuse. It may soon be possible to view the nervous system as a representational process that solves the mathematically defined economic problems animals face by making efficient decisions. These developments in the neurobiological theory of choice, and the new schema they imply, form the subject of this article.     

Within-host parasite dynamics,emerging trade-off,and evolution of virulence with immune system

Abstract.— Virulence is an evolutionary paradox because parasites never benefit from their host's death. The adaptive explanation of virulence is classically based upon the existence of physiological constraints that create a trade-off between parasites' epidemiological traits (virulence, transmissibility, and clearance). Here we develop an epidemiological model where infections are dynamic processes and we demonstrate how these dynamics generate a trade-off between emerging epidemiological parameters. We then study how host's immune strength modifies this trade-off and hence influences virulence evolution. We found that in acute infections, where parasites are engaged in a race with immune cells, immunity restrains more the duration of the infection than its intensity. As a consequence parasites evolve to provoke more virulent but shorter infections in strongly immunized hosts.     

Neurotrophins in inflammatory lung diseases: modulators of cell differentiation and neuroimmune interactions

Chronic inflammatory lung diseases represent a group of severe diseases with increasing prevalence as well as epidemiological importance. Inflammatory lung diseases could result from allergic or infectious genesis. There is growing evidence that the immune and nervous system are closely related not only in physiological but also in pathological reactions in the lung. Extensive communications between neurons and immune cells are responsible for the magnitude of airway inflammation and the development of airway hyperreactivity, a consequence of neuronal dysregulation. Neurotrophins are molecules regulating and controlling this crosstalk between the immune and peripheral nervous system (PNS) during inflammatory lung diseases. They are constitutively expressed by resident lung cells and produced in increasing quantities by immune cells invading the airways under inflammatory conditions. They act as activation, differentiation and survival factors for cells of both the immune and nervous system. This article will review the most recent data of neurotrophin signaling in the normal and inflamed lung and as yet unexplored, roles of neurotrophins in the complex communication within the neuroimmune network.     

Evolution of evolvability via adaptation of mutation rates

We examine a simple form of the evolution of evolvability-the evolution of mutation rates-in a simple model system. The system is composed of many agents moving, reproducing, and dying in a two-dimensional resource-limited world. We first examine various macroscopic quantities (three types of genetic diversity, a measure of population fitness, and a measure of evolutionary activity) as a function of fixed mutation rates. The results suggest that (i) mutation rate is a control parameter that governs a transition between two qualitatively different phases of evolution, an ordered phase characterized by punctuated equilibria of diversity, and a disordered phase of characterized by noisy fluctuations around an equilibrium diversity, and (ii) the ability of evolution to create adaptive structure is maximized when the mutation rate is just below the transition between these two phases of evolution. We hypothesize that this transition occurs when the demands for evolutionary memory and evolutionary novelty are typically balanced. We next allow the mutation rate itself to evolve, and we observe that evolving mutation rates adapt to values at this transition. Furthermore, the mutation rates adapt up (or down) as the evolutionary demands for novelty (or memory) increase, thus supporting the balance hypothesis.     

High strength-of-ties and low mobility enable the evolution of third-party punishment

As punishment can be essential to cooperation and norm maintenance but costly to the punisher, many evolutionary game-theoretic studies have explored how direct punishment can evolve in populations. Compared to direct punishment, in which an agent acts to punish another for an interaction in which both parties were involved, the evolution of third-party punishment (3PP) is even more puzzling, because the punishing agent itself was not involved in the original interaction. Despite significant empirical studies of 3PP, little is known about the conditions under which it can evolve. We find that punishment reputation is not, by itself, sufficient for the evolution of 3PP. Drawing on research streams in sociology and psychology, we implement a structured population model and show that high strength-of-ties and low mobility are critical for the evolution of responsible 3PP. Only in such settings of high social-structural constraint are punishers able to induce self-interested agents toward cooperation, making responsible 3PP ultimately beneficial to individuals as well as the collective. Our results illuminate the conditions under which 3PP is evolutionarily adaptive in populations. Responsible 3PP can evolve and induce cooperation in cases where other mechanisms alone fail to do so.     

Asymmetric localization and function of cell-fate determinants: a fly's view

One mechanism to generate daughter cells with distinct fates is the asymmetric inheritance of regulatory proteins, leading to differential gene regulation in the daughter cells. This mode of cell division is termed 'asymmetric cell division.' The nervous system of the fly employs asymmetric cell division, both in the central nervous system, to generate neural precursors, neurons and glial cells; and in the peripheral nervous system, to create sensory organs that are composed of multiple cell types. These cell lineages are excellent models to examine the gene expression program that leads to fate acquisition, the cell-fate determinants that control these programs and how these determinants, in turn, are distributed through cell polarity machinery.     

How group size affects vigilance dynamics and time allocation patterns: the key role of imitation and tempo

In the context of social foraging, predator detection has been the subject of numerous studies, which acknowledge the adaptive response of the individual to the trade-off between feeding and vigilance. Typically, animals gain energy by increasing their feeding time and decreasing their vigilance effort with increasing group size, without increasing their risk of predation ('group size effect'). Research on the biological utility of vigilance has prevailed over considerations of the mechanistic rules that link individual decisions to group behavior. With sheep as a model species, we identified how the behaviors of conspecifics affect the individual decisions to switch activity. We highlight a simple mechanism whereby the group size effect on collective vigilance dynamics is shaped by two key features: the magnitude of social amplification and intrinsic differences between foraging and scanning bout durations. Our results highlight a positive correlation between the duration of scanning and foraging bouts at the level of the group. This finding reveals the existence of groups with high and low rates of transition between activities, suggesting individual variations in the transition rate, or 'tempo'. We present a mathematical model based on behavioral rules derived from experiments. Our theoretical predictions show that the system is robust in respect to variations in the propensity to imitate scanning and foraging, yet flexible in respect to differences in the duration of activity bouts. The model shows how individual decisions contribute to collective behavior patterns and how the group, in turn, facilitates individual-level adaptive responses.     

ADAPTATION AND PLASTICITY OF ANIMAL COMMUNICATION IN FLUCTUATING ENVIRONMENTS

Adaptations that facilitate the reception of long‐range signals under challenging conditions are expected to generate signal diversity when species communicate in different habitats. Although we have a general understanding of how individual communicating animals cope with conditions influencing signal detection, the extent to which plasticity and evolutionary changes in signal characteristics contribute to interspecific differences in signaling behavior is unclear. We quantified the visual displays of free‐living lizards and environmental variables known to influence display detection for multiple species from two separate island radiations. We found evidence of both adaptive evolution and adaptive plasticity in display characteristics as a function of environmental conditions, but plasticity accounted for most of the observed differences in display behavior across species. At the same time, prominent differences between the two island radiations existed in aspects of signaling behavior, unrelated to the environment. Past evolutionary events have therefore played an important role in shaping the way lizards adjust their signals to challenges in present‐day environments. In addition to showing how plasticity contributes to interspecific differences in communication signals, our findings suggest the vagaries of evolution can in itself lead to signal variation between species.     

Predicting adaptive behavior in the environment from central nervous system dynamics

To generate adaptive behavior, the nervous system is coupled to the environment. The coupling constrains the dynamical properties that the nervous system and the environment must have relative to each other if adaptive behavior is to be produced. In previous computational studies, such constraints have been used to evolve controllers or artificial agents to perform a behavioral task in a given environment. Often, however, we already know the controller, the real nervous system, and its dynamics. Here we propose that the constraints can also be used to solve the inverse problem--to predict from the dynamics of the nervous system the environment to which they are adapted, and so reconstruct the production of the adaptive behavior by the entire coupled system. We illustrate how this can be done in the feeding system of the sea slug Aplysia. At the core of this system is a central pattern generator (CPG) that, with dynamics on both fast and slow time scales, integrates incoming sensory stimuli to produce ingestive and egestive motor programs. We run models embodying these CPG dynamics--in effect, autonomous Aplysia agents--in various feeding environments and analyze the performance of the entire system in a realistic feeding task. We find that the dynamics of the system are tuned for optimal performance in a narrow range of environments that correspond well to those that Aplysia encounter in the wild. In these environments, the slow CPG dynamics implement efficient ingestion of edible seaweed strips with minimal sensory information about them. The fast dynamics then implement a switch to a different behavioral mode in which the system ignores the sensory information completely and follows an internal "goal," emergent from the dynamics, to egest again a strip that proves to be inedible. Key predictions of this reconstruction are confirmed in real feeding animals.     

Analysis of theta-rhythms recorded in an isolated strip of rabbit sensomotor cortex

To test the possibility that the theta-rhythm may spread passively from the hippocampus into the neocortex in rabbits and to analyze the properties of these rhythms recorded from the surface of the neocortex, an investigation was made of activity recorded simultaneously from the hippocampus and various points of the neocortex, including from a strip of the sensomotor cortex isolated completely with respect to its nervous connections. The use of special correlation methods showed that an appreciable contribution to the potentials recorded from the isolated strip can be made by the passive conduction of hippocampal activity (provided that it generates a regular high-amplitude theta-rhythm). At the same time, potentials in a theta-rhythm may be generated in the isolated strip itself. The theta-rhythm recorded in the intact rabbit cortex may thus be of combined genesis: generated in the neocortex itself and spreading passively from the hippocampus through the brain tissues as through a volume conductor.