69 research outputs found
An ANOVA approach for statistical comparisons of brain networks
The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.Fil: Fraiman Borrazás, Daniel Edmundo. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina. Universidad de San AndrĂ©s. Departamento de Matemáticas y Ciencias; ArgentinaFil: Fraiman, Jacob Ricardo. Universidad de la RepĂşblica; Uruguay. Instituto Pasteur de Montevideo; Urugua
Bak-Sneppen model: Local equilibrium and critical value
The Bak-Sneppen (BS) model is a very simple model that exhibits all the richness of self-organized criticality theory. At the thermodynamic limit, the BS model converges to a situation where all particles have a fitness that is uniformly distributed between a critical value pc and 1. The pc value is unknown, as are the variables that influence and determine this value. Here we study the BS model in the case in which the lowest fitness particle interacts with an arbitrary even number of m nearest neighbors. We show that pc verifies a simple local equilibrium relation. Based on this relation, we can determine bounds for pc of the BS model and exact results for some BS-like models. Finally, we show how transformations of the original BS model can be done without altering the model's complex dynamics.Fil: Fraiman Borrazás, Daniel Edmundo. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentin
The brain: What is critical about it?
We review the recent proposal that the most fascinating brain properties are
related to the fact that it always stays close to a second order phase
transition. In such conditions, the collective of neuronal groups can reliably
generate robust and flexible behavior, because it is known that at the critical
point there is the largest abundance of metastable states to choose from. Here
we review the motivation, arguments and recent results, as well as further
implications of this view of the functioning brain.Comment: Proceedings of BIOCOMP2007 - Collective Dynamics: Topics on
Competition and Cooperation in the Biosciences. Vietri sul Mare, Italy (2007
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