337,430 research outputs found
“An ethnographic seduction”: how qualitative research and Agent-based models can benefit each other
We provide a general analytical framework for empirically informed agent-based simulations. This methodology provides present-day agent-based models with a sound and proper insight as to the behavior of social agents — an insight that statistical data often fall short of providing at least at a micro level and for hidden and sensitive populations. In the other direction, simulations can provide qualitative researchers in sociology, anthropology and other fields with valuable tools for: (a) testing the consistency and pushing the boundaries, of specific theoretical frameworks; (b) replicating and generalizing results; (c) providing a platform for cross-disciplinary validation of results
Analytical models for well-mixed populations of cooperators and defectors under limiting resources
In the study of the evolution of cooperation, resource limitations are
usually assumed just to provide a finite population size. Recently, however,
agent-based models have pointed out that resource limitation may modify the
original structure of the interactions and allow for the survival of
unconditional cooperators in well-mixed populations. Here, we present
analytical simplified versions of two types of agent-based models recently
published: one in which the limiting resource constrains the ability of
reproduction of individuals but not their survival, and a second one where the
limiting resource is necessary for both reproduction and survival. One finds
that the analytical models display, with a few differences, the same
qualitative behavior of the more complex agent-based models. In addition, the
analytical models allow us to expand the study and identify the dimensionless
parameters governing the final fate of the system, such as coexistence of
cooperators and defectors, or dominance of defectors or of cooperators. We
provide a detailed analysis of the occurring phase transitions as these
parameters are varied.Comment: 7 pages, 8 figure
Fission-fusion dynamics and group-size dependent composition in heterogeneous populations
Many animal groups are heterogeneous and may even consist of individuals of
different species, called mixed-species flocks. Mathematical and computational
models of collective animal movement behaviour, however, typically assume that
groups and populations consist of identical individuals. In this paper, using
the mathematical framework of the coagulation-fragmentation process, we develop
and analyse a model of merge and split group dynamics, also called
fission-fusion dynamics, for heterogeneous populations that contain two types
(or species) of individuals. We assume that more heterogeneous groups
experience higher split rates than homogeneous groups, forming two daughter
groups whose compositions are drawn uniformly from all possible partitions. We
analytically derive a master equation for group size and compositions and find
mean-field steady-state solutions. We predict that there is a critical group
size below which groups are more likely to be homogeneous and contain the
abundant type/species. Despite the propensity of heterogeneous groups to split
at higher rates, we find that groups are more likely to be heterogeneous but
only above the critical group size. Monte-Carlo simulation of the model show
excellent agreement with these analytical model results. Thus, our model makes
a testable prediction that composition of flocks are group-size dependent and
do not merely reflect the population level heterogeneity. We discuss the
implications of our results to empirical studies on flocking systems.Comment: 19 pages, 8 figure
The evolution of genetic architectures underlying quantitative traits
In the classic view introduced by R. A. Fisher, a quantitative trait is
encoded by many loci with small, additive effects. Recent advances in QTL
mapping have begun to elucidate the genetic architectures underlying vast
numbers of phenotypes across diverse taxa, producing observations that
sometimes contrast with Fisher's blueprint. Despite these considerable
empirical efforts to map the genetic determinants of traits, it remains poorly
understood how the genetic architecture of a trait should evolve, or how it
depends on the selection pressures on the trait. Here we develop a simple,
population-genetic model for the evolution of genetic architectures. Our model
predicts that traits under moderate selection should be encoded by many loci
with highly variable effects, whereas traits under either weak or strong
selection should be encoded by relatively few loci. We compare these
theoretical predictions to qualitative trends in the genetics of human traits,
and to systematic data on the genetics of gene expression levels in yeast. Our
analysis provides an evolutionary explanation for broad empirical patterns in
the genetic basis of traits, and it introduces a single framework that unifies
the diversity of observed genetic architectures, ranging from Mendelian to
Fisherian.Comment: Minor changes in the text; Added supplementary materia
Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model
Several firing patterns experimentally observed in neural populations have
been successfully correlated to animal behavior. Population bursting, hereby
regarded as a period of high firing rate followed by a period of quiescence, is
typically observed in groups of neurons during behavior. Biophysical
membrane-potential models of single cell bursting involve at least three
equations. Extending such models to study the collective behavior of neural
populations involves thousands of equations and can be very expensive
computationally. For this reason, low dimensional population models that
capture biophysical aspects of networks are needed.
\noindent The present paper uses a firing-rate model to study mechanisms that
trigger and stop transitions between tonic and phasic population firing. These
mechanisms are captured through a two-dimensional system, which can potentially
be extended to include interactions between different areas of the nervous
system with a small number of equations. The typical behavior of midbrain
dopaminergic neurons in the rodent is used as an example to illustrate and
interpret our results.
\noindent The model presented here can be used as a building block to study
interactions between networks of neurons. This theoretical approach may help
contextualize and understand the factors involved in regulating burst firing in
populations and how it may modulate distinct aspects of behavior.Comment: 25 pages (including references and appendices); 12 figures uploaded
as separate file
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