Paulo Freire e a pedagogia do oprimido: afinidades pós-coloniais

The main objective of the present research is to reflect on the affinities between post-colonial theories - analytical perspectives directed toward the discussion of colonialism and its effects on the contemporary social fabric - and Brazilian educator, Paulo Freire‟s (1921-1997) Pedagogy of the Oppressed, written at the end of the 1960‟s. The study aims to make the argument that the present reflections on the featured work is an example of a post-colonial theoretical framework, delineating a critical modus operandi of colonialism, particularly in its cultural and epistemic dimensions, delineating a problematization of the processes of cognitive domination set, above all, by the European colonization of the Latin American continent, with the formation of the modern-world-system (WALLERSTEIN, 2007), dated from the 16TH Century forward. From this stand point, and especially supported by the contributions of Boaventura de Sousa Santos on the sociology of absence, the present work accentuates Pedagogy of the Oppressed as a set of reflections that bring the possibility of a pedagogy of absence (SANTOS, 1996), having in mind that, this book deals with, the presuppositions of an educational action, which considers the plurality of knowledge and social practices by way of the establishment of a pedagogical practice of collective construction, emancipator and dialogic that arises from the encounter to the indolent reason (SANTOS, 2009) in which the silencing of the voices of the oppressed, construct their conditions of invisibility, promoting also the absence of the social questions inherent to the processes of teaching and learning. It is with this perspective, however, that post colonialism is considered a theoretical site for the affirmation and the reinvention of the Pedagogy of the Oppressed, an obligatory reference in the construction of a prudent knowledge for a decent life (SANTOS, 2006)

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.