Compilado AZyNE 28-12

To Group or Not to Group?, Science

Summary: The phenomenon of cooperation between potentially competing individuals raises an interesting question related to evolution: Why should a competitor favor someone else's fitness at the expense of its own? One way to approach this question is through insights on how cooperation and population structure coevolve.

• Source: To Group or Not to Group?, Eörs Szathmáry, DOI: 10.1126/science.1209548, Science Vol. 334 no. 6063 pp. 1648-1649, 2011/12/23

Antonio Damasio: The quest to understand consciousness, TED.com

About this talk: Every morning we wake up and regain consciousness -- that is a marvelous fact -- but what exactly is it that we regain? Neuroscientist Antonio Damasio uses this simple question to give us a glimpse into how our brains create our sense of self.

• Source: Antonio Damasio: The quest to understand consciousness, TED.com, 2011/12
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Evolution and development of Brain Networks: From Caenorhabditis elegans to Homo sapiens, arXiv

Abstract: Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes involving a limited amount of tasks and modalities to complex functional and behavioral processing integrating different kinds of information from highly specialized tissue. However, studies in a range of species suggest that fundamental similarities, in spatial and topological features as well as in developmental mechanisms for network formation, are retained across evolution. 'Small-world' topology and highly connected regions (hubs) are prevalent across the evolutionary scale, ensuring efficient processing and resilience to internal (e.g. lesions) and external (e.g. environment) changes. Furthermore, in most species, even the establishment of hubs, long-range connections linking distant components, and a modular organization, relies on similar mechanisms. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints.

• Source: Evolution and development of Brain Networks: From Caenorhabditis elegans to Homo sapiens, Marcus Kaiser and Sreedevi Varier, arXiv:1112.5449, 2011/12/22

The Diversity Paradox: How Nature Resolves an Evolutionary Dilemma, arXiv

Excerpt: Adaptation to changing environments is a hallmark of biological systems. Diversity in traits is necessary for adaptation and can influence the survival of a population faced with novelty. In habitats that remain stable over many generations, stabilizing selection reduces trait differences within populations, thereby appearing to remove the diversity needed for heritable adaptive responses in new environments. Paradoxically, field studies have documented numerous populations under long periods of stabilizing selection and evolutionary stasis that have rapidly evolved under changed environmental conditions. In this article, we review how cryptic genetic variation (CGV) resolves this diversity paradox by allowing populations in a stable environment to gradually accumulate hidden genetic diversity that is revealed as trait differences when environments change. (…)

• Source: The Diversity Paradox: How Nature Resolves an Evolutionary Dilemma, James M. Whitacre and Sergei P. Atamas, arXiv:1112.3115, 2011/12/14

Facing Complexity: Prediction vs. Adaptation, arXiv

Abstract: One of the presuppositions of science since the times of Galileo, Newton, Laplace, and Descartes has been the predictability of the world. This idea has strongly influenced scientific and technological models. However, in recent decades, chaos and complexity have shown that not every phenomenon is predictable, even if it is deterministic. If a problem space is predictable, in theory we can find a solution via optimization. Nevertheless, if a problem space is not predictable, or it changes too fast, very probably optimization will offer obsolete solutions. This occurs often when the immediate solution affects the problem itself. An alternative is found in adaptation. An adaptive system will be able to find by itself new solutions for unforeseen situations.

• Source: Facing Complexity: Prediction vs. Adaptation, Carlos Gershenson, arXiv:1112.3843, 2011/12/16