Center for Insect Science, University of Arizona

An evolutionary biologist learns how to be remembered: cheat someone.

What makes someone unforgettable? Is it their charm? Their looks? Or is it that they once stiffed you on the bill?

Like many others, I have trouble remembering people's names, even as I am being introduced to them, but certain names remain etched in my mind forever. Few, for example, will forget Bernard Madoff, the New York financier convicted of defrauding people out of billions of dollars in a giant Ponzi scheme.

Raoul Bell and Axel Buchner at the Institute of Experimental Psychology in Düsseldorf, Germany, have explored this bias in memory (R. Bell and A. Buchner. Evol. Psychol. 7, 317–330; 2009). They reveal that humans have a greater propensity to remember the names of individuals associated with cheating than names associated with trustworthiness or other unrelated behaviours.

Cooperation is immensely beneficial to humans, but with cooperation looms the ever-present risk of exploitation. Researchers have proposed that humans have a specialized brain module dedicated to detecting and remembering cheaters, to help them to steer clear of future interactions with such individuals. It has previously been suggested that the cheater memory module is tied only to facial stimuli. But using the same behaviours associated with facial stimuli in previous studies, Bell and Buchner were able to replicate these findings using only names, which suggests a more general module for remembering cheaters.

Associating reputations with names is crucial to maintaining social norms through verbal mechanisms such as gossip. Thus memory bias for the names as well as the faces of cheaters could expand the ability of groups of individuals to avoid exploitation.

Madoff probably won't have much luck if he tries to scam people again.

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CRP-Santé, Luxembourg

A bioinformatician considers the general applicability of host-pathogen computer simulations

Computer simulations can help explain evolutionary phenomena such as co-evolution and the emergence of robustness. Unlike traditional methods of analysis, such simulations can incorporate detailed representations of environmental antagonisms — such as the pressure that parasites exert on the evolution of their hosts.

This is what Marcel Salathé of ETH Zurich in Switzerland and Orkun Soyer of the University of Trento, Italy, recently analysed at the molecular level. By using computer simulations based on mathematical models, they showed how robust signalling networks may evolve in parasite-infested cells (M. Salathé and O. S. Soyer Mol. Syst. Biol. 4, 202; 2008). In their simulations, signalling networks exhibited increasing redundancy in response to parasites, to the point that a node could be entirely removed without affecting network function. It seems that network redundancy may be a signature of parasitism present or past.

The paper is an exciting invitation to take a computational approach to evolutionary questions, by including more detailed mathematical representations. One could, for example, extend the host-parasite model to incorporate not just protein sequences, but also the ways in which genomic variation is generated, and see how everything plays out.

The approach could be generalized. National security studies, for example, might examine when and how attempts to infiltrate terrorist networks might actually make them more robust. And perhaps Salathé and Soyer's approach could be used to find ways of using environmental interference to reduce the robustness of disease networks, such as cancer signalling pathways, by examining their antagonistic interactions with therapeutic agents.

Posted by Anna Petherick at 12:13 PM | Permalink | Comments (0) | TrackBacks (0)