RESUMEN
Understanding the relationship between large-scale structural and functional brain networks remains a crucial issue in modern neuroscience. Recently, there has been growing interest in investigating the role of homeostatic plasticity mechanisms, across different spatiotemporal scales, in regulating network activity and brain functioning against a wide range of environmental conditions and brain states (e.g., during learning, development, ageing, neurological diseases). In the present study, we investigate how the inclusion of homeostatic plasticity in a stochastic whole-brain model, implemented as a normalization of the incoming node's excitatory input, affects the macroscopic activity during rest and the formation of functional networks. Importantly, we address the structure-function relationship both at the group and individual-based levels. In this work, we show that normalization of the node's excitatory input improves the correspondence between simulated neural patterns of the model and various brain functional data. Indeed, we find that the best match is achieved when the model control parameter is in its critical value and that normalization minimizes both the variability of the critical points and neuronal activity patterns among subjects. Therefore, our results suggest that the inclusion of homeostatic principles lead to more realistic brain activity consistent with the hallmarks of criticality. Our theoretical framework open new perspectives in personalized brain modeling with potential applications to investigate the deviation from criticality due to structural lesions (e.g. stroke) or brain disorders.
Asunto(s)
Encéfalo/fisiología , Homeostasis/fisiología , Modelos Neurológicos , Red Nerviosa/fisiología , Plasticidad Neuronal/fisiología , Mapeo Encefálico , Simulación por Computador , Humanos , Imagen por Resonancia Magnética , Redes Neurales de la Computación , Neuronas/fisiología , Descanso/fisiología , Accidente Cerebrovascular/fisiopatologíaRESUMEN
In this work we study the likelihood of survival of single-species in the context of hostile and disordered environments. Population dynamics in this environment, as modeled by the Fisher equation, is characterized by negative average growth rate, except in some random spatially distributed patches that may support life. In particular, we are interested in the phase diagram of the survival probability and in the critical size problem, i.e., the minimum patch size required for surviving in the long-time dynamics. We propose a measure for the critical patch size as being proportional to the participation ratio of the eigenvector corresponding to the largest eigenvalue of the linearized Fisher dynamics. We obtain the (extinction-survival) phase diagram and the probability distribution function (PDF) of the critical patch sizes for two topologies, namely, the one-dimensional system and the fractal Peano basin. We show that both topologies share the same qualitative features, but the fractal topology requires higher spatial fluctuations to guarantee species survival. We perform a finite-size scaling and we obtain the associated scaling exponents. In addition, we show that the PDF of the critical patch sizes has an universal shape for the 1D case in terms of the model parameters (diffusion, growth rate, etc.). In contrast, the diffusion coefficient has a drastic effect on the PDF of the critical patch sizes of the fractal Peano basin, and it does not obey the same scaling law of the 1D case.
Asunto(s)
Ambiente , Modelos Biológicos , Animales , Dinámica Poblacional , Probabilidad , Análisis de SupervivenciaRESUMEN
We present 2 distinct and independent approaches to deduce the effective interaction strengths between species and apply it to the 20 most abundant species in the long-term 50-ha plot on Barro Colorado Island, Panama. The first approach employs the principle of maximum entropy, and the second uses a stochastic birth-death model. Both approaches yield very similar answers and show that the collective effects of the pairwise interspecific interaction strengths are weak compared with the intraspecific interactions. Our approaches can be applied to other ecological communities in steady state to evaluate the extent to which interactions need to be incorporated into theoretical explanations for their structure and dynamics.
Asunto(s)
Árboles , Clima Tropical , Biodiversidad , Conservación de los Recursos Naturales , Ecología , Ecosistema , Entropía , Extinción Biológica , Modelos Estadísticos , Modelos Teóricos , Análisis Multivariante , Panamá , Dinámica Poblacional , Procesos EstocásticosRESUMEN
The recurrent patterns in the commonness and rarity of species in ecological communities--the relative species abundance--have puzzled ecologists for more than half a century. Here we show that the framework of the current neutral theory in ecology can easily be generalized to incorporate symmetric density dependence. We can calculate precisely the strength of the rare-species advantage that is needed to explain a given RSA distribution. Previously, we demonstrated that a mechanism of dispersal limitation also fits RSA data well. Here we compare fits of the dispersal and density-dependence mechanisms for empirical RSA data on tree species in six New and Old World tropical forests and show that both mechanisms offer sufficient and independent explanations. We suggest that RSA data cannot by themselves be used to discriminate among these explanations of RSA patterns--empirical studies will be required to determine whether RSA patterns are due to one or the other mechanism, or to some combination of both.