You are currently browsing the tag archive for the ‘Natural Selection’ tag.

Image – The frontispiece of William King Gregory’s two-volume Evolution Emerging. Gregory, 1951, Evolution Emerging: A Survey of Changing Patterns from Primeval Life to Man, vol. 2, p. 757; fig. 20.33; [courtesy of Mary DeJong, Mai Qaraman, and the American Museum of Natural History].

Video – TED lecture: Empathy, cooperation, fairness and reciprocity – caring about the well-being of others seems like a very human trait. But Frans de Waal shares some surprising videos of behavioural tests, on primates and other mammals, that show how many of these moral traits all of us share. (TED, Nov. 2011, link).

Evolutionary explanations are built around the principle that all that natural selection can work with are the effects of behaviour – not the motivation behind it. This means there is only one logical starting point for evolutionary accounts, as explained by Trivers (2002, p. 6): “You begin with the effect of behaviour on actors and recipients; you deal with the problem of internal motivation, which is a secondary problem, afterwards. . . . [I]f you start with motivation, you have given up the evolutionary analysis at the outset.” ~ Frans B.M. de Waal, 2008.

Do animals have morals? And above all, did morality evolved? The question is pertinent in a broad range of quite different areas, as in as well Computer Sciences and Norm Generation (e.g. link for an MSc thesis) in bio-inspired Computation and Artificial Life, but here new fresh answers come directly from Biology. Besides the striking video lecture above, what follows are 2 different excerpts (abstract and conclusions) from a 2008 paper by Frans B.M. de Waal (Living Links Center lab., Emory University, link): de Waal, F.B.M. (2008). Putting the altruism back in altruism: The evolution of empathy. Ann. Rev. Psychol. 59: 279-300 (full PDF link):

(…) Abstract: Evolutionary theory postulates that altruistic behaviour evolved for the return-benefits it bears the performer. For return-benefits to play a motivational role, however, they need to be experienced by the organism. Motivational analyses should restrict themselves, therefore, to the altruistic impulse and its knowable consequences. Empathy is an ideal candidate mechanism to underlie so-called directed altruism, i.e., altruism in response to another’s pain, need, or distress. Evidence is accumulating that this mechanism is phylogenetically ancient, probably as old as mammals and birds. Perception of the emotional state of another automatically activates shared representations causing a matching emotional state in the observer.With increasing cognition, state-matching evolved into more complex forms, including concern for the other and perspective-taking. Empathy-induced altruism derives its strength from the emotional stake it offers the self in the other’s welfare. The dynamics of the empathy mechanism agree with predictions from kin selection and reciprocal altruism theory. (…)

(…) Conclusion: More than three decades ago, biologists deliberately removed the altruism from altruism.There is now increasing evidence that the brain is hardwired for social connection, and that the same empathy mechanism proposed to underlie human altruism (Batson 1991) may underlie the directed altruism of other animals. Empathy could well provide the main motivation making individuals who have exchanged benefits in the past to continue doing so in the future. Instead of assuming learned expectations or calculations about future benefits, this approach emphasizes a spontaneous altruistic impulse and a mediating role of the emotions. It is summarized in the five conclusions below: 1. An evolutionarily parsimonious account (cf. de Waal 1999) of directed altruism assumes similar motivational processes in humans and other animals. 2. Empathy, broadly defined, is a phylogenetically ancient capacity. 3. Without the emotional engagement brought about by empathy, it is unclear what could motivate the extremely costly helping behavior occasionally observed in social animals. 4. Consistent with kin selection and reciprocal altruism theory, empathy favours familiar individuals and previous cooperators, and is biased against previous defectors. 5. Combined with perspective-taking abilities, empathy’s motivational autonomy opens the door to intentionally altruistic altruism in a few large-brained species.(…) in, de Waal, F.B.M. (2008). Putting the altruism back in altruism: The evolution of empathy. Ann. Rev. Psychol. 59: 279-300 (full PDF link).

Frans de Waal research work does not end up here, of course. He is a ubiquitous influence and writer on many related areas such as: Cognition, Communication, Crowding/Conflict Resolution, Empathy and Altruism, Social Learning and Culture, Sharing and Cooperation and last but not least, Behavioural Economics. All of his papers are free on-line, in a web page I do vividly recommend a long visit.

Figure – Understanding the Brain as a Computational Network: significant neuronal motifs of size 3.  Most over-represented colored motifs of size 3 in the C. elegans complex neuronal network. Green: sensory neuron; blue: motor neuron; red: interneuron. Arrows represent direction that the signal travels between the two cells. (from Adami et al. 2011 [Ref. below])

Abstract: […] Complex networks can often be decomposed into less complex sub-networks whose structures can give hints about the functional organization of the network as a whole. However, these structural motifs can only tell one part of the functional story because in this analysis each node and edge is treated on an equal footing. In real networks, two motifs that are topologically identical but whose nodes perform very different functions will play very different roles in the network. Here, we combine structural information derived from the topology of the neuronal network of the nematode C. elegans with information about the biological function of these nodes, thus coloring nodes by function. We discover that particular colorations of motifs are significantly more abundant in the worm brain than expected by chance, and have particular computational functions that emphasize the feed-forward structure of information processing in the network, while evading feedback loops. Interneurons are strongly over-represented among the common motifs, supporting the notion that these motifs process and transduce the information from the sensor neurons towards the muscles. Some of the most common motifs identified in the search for significant colored motifs play a crucial role in the system of neurons controlling the worm’s locomotion. The analysis of complex networks in terms of colored motifs combines two independent data sets to generate insight about these networks that cannot be obtained with either data set alone. The method is general and should allow a decomposition of any complex networks into its functional (rather than topological) motifs as long as both wiring and functional information is available. […] from Qian J, Hintze A, Adami C (2011) Colored Motifs Reveal Computational Building Blocks in the C. elegans Brain, PLoS ONE 6(3): e17013. doi:10.1371/journal.pone.0017013

[…] The role of evolution in producing these patterns is clear, said Adami. “Selection favors those motifs that impart high fitness to the organism, and suppresses those that work against the task at hand.” In this way, the efficient and highly functional motifs (such as the sensory neuron-interneuron-motor neuron motif) are very common in the nervous system, while those that would waste energy and give no benefit to, or even harm, the animal are not found in the network. “Adami and his team have used evolutionary computation to develop hypotheses about the evolution of neural circuits and find, for these nematode worms, that simplicity is the rule,” says George Gilchrist, program director in NSF’s Division of Environmental Biology (in the Directorate for Biological Sciences), which funds BEACON. “By including functional information about each node in the circuit, they have begun decoding the role of natural selection in shaping the architecture of neural circuits.” […] from Danielle J. Whittaker “Understanding the Brain as a Computational Network“, NSF, April 2011.

EVOL-ution Stencil Art work by KrieBeL (source on flickr)

It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptable to change“. Charles Darwin (On the Origin of Species, Nov. 1859)

At his final chapter Charles Darwin (On the Origin of Species, Nov. 1859) reviews points from earlier chapters, and he concludes by hoping that his theory might produce revolutionary changes in many fields of natural history. Although he avoids the controversial topic of human origins in the rest of the book so as not to prejudice readers against his theory, here he ventures a cautious hint that psychology would be put on a new foundation and that “Light will be thrown on the origin of man“. Darwin ends with a passage that became well known and much quoted:

[…] It is interesting to contemplate an entangled bank, clothed with many plants of many kinds, with birds singing on the bushes, with various insects flitting about, and with worms crawling through the damp earth, and to reflect that these elaborately constructed forms, so different from each other, and dependent on each other in so complex a manner, have all been produced by laws acting around us … Thus, from the war of nature, from famine and death, the most exalted object which we are capable of conceiving, namely, the production of the higher animals, directly follows. There is grandeur in this view of life, with its several powers, having been originally breathed into a few forms or into one; and that, whilst this planet has gone cycling on according to the fixed law of gravity, from so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved […]. Charles Darwin, On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life, Nov. 1859. [passage from ]

[...] People should learn how to play Lego with their minds. Concepts are building bricks [...] V. Ramos, 2002.

@ViRAms on Twitter

Error: Twitter did not respond. Please wait a few minutes and refresh this page.


Blog Stats

  • 244,363 hits