Categories
MURC

The 5min MURC Panel Intro v1.0

I started sketching out what to say in our 5min panel intro talk (either by Scott and/or myself); would like your input! Please let me know ASAP if I mangled your topic/you have suggestions about presentation order/ the intro itself, etc.!

0:00 Intro to evol theory
– Power of evolutionary theory: can explain order, complexity (appearance of ‘design’) in neutral terms; “Through [Darwin’s] strange inversion of reasoning, the unintelligent forces can create intelligent design” (this guy qtd in Dennet 2009 PNAS; badly paraphrased, will look up when I get back to Vancouver…)
– Evolution has a unifying and integrating power — eg, ties together the diverse fields of biology. “Nothing makes sense in biology except in the light of evolution” –Theodosius Dobzhansky
– The bridge between arts and sciences? The way to embody the mind (cite Slingerland?) and explain the “human realm” through natural means?
– We will explore, albeit very briefly, some potential applications of evolutionary theory outside biology.

1:30 Topics Overview
– We will examine the following topics in the following order:
1. Ashley — Animal Culture
– Not all inheritance in biol happens via genes; nor is cultural inheritance unique to humans?
2. Charlene — Memetics
– Critically exploring the possibility of a replicator in non-biological, namely cultural, evolution — are memes feasible?
3. Yana — Neutral Evolution
– Not everything is adaptive: Importance and application of selectively neutral and pluralistic models within biology and beyond. Would linguistic and cultural evolution lend better to less-adaptationistic explanations?
4. Scott — Genetic Algorithms
– The use of evolutionary algorithms in computer science and engineering has been growing over the years; is it truly an efficient design strategy to employ evolution for design considering its >99% fail rate?
(~3:00)
5. Peter — Autopsy of Thorn
– Old English contained a unique letter to encode the /th/ sound, the Thorn, which mysteriously disappeared; what were its origins, history and how has its demise come to be?
6. Lisi — Revolutions
[[I need your proposal please! =D]]
Tentative: Can evolutionary modeling be applied to revolutions of ideas [and politics?] in culture?
7. Ruth — Evolution of Religion
– Religion is often considered an anathema to evolution; however, can the development and changes of religion itself be explained with evolutionary theory?
4:30
– Afterwards, the panel will be wrapped up with a 15min discussion in the end. [We can carry on the discussion after at Location X]
-5:00-

[note to self]We need to find out if we can take the discussion outside/prolong it somehow if people would like to! This needs to be planned[/note to self]

What do you guys think?[[

Categories
language Week 5

Linguistics Overview

Okay, so I was thinking– we really did gloss over just about everything when we ran through linguistics this week. So here’s a brief glossary of particularly important terms:

Allomorphs: Two phonetically similar and semantically identical morphemes that never appear in the same context.
Allophones: Two sounds that are phonetically similar and never appear in the same context.
Cognate: Two words in related languages that are recognizably similar in both sound and in meaning.
Content words: Words that have specific, definable meanings; basically any word in a sentence that’s not a function word is a content word.
Function words: Words that only exist to serve the grammar of the language; they are often difficult to specifically define and short in length. Examples in English include “and”, “but”, “the”, etc.
Morpheme: The smallest linguistic unit that still has meaning.
Phoneme: A sound that is used by a language to distinguish between words.

That’s everything I can explain for now. Comment if you want more info, want additional terms defined/explained, whatever.

Categories
MURC proposals

MURC proposal

Here’s mine – I tried to submit about four times and got ‘error updating database’ each time so…I’m not really sure what to do about that. Also yes, I know, needs more refs.

A Map Out of Eden: How evolutionary theory can be used to trace change in religious ideologies

I am interested in examining whether evolutionary theory can be applied to document the changes in religious institutions and ideals over time. While some work has been done relating evolution and religion, much of it has been in the field of evolutionary psychology, in trying to discern the adaptive role of religion in terms of biology and psychology, rather than examining religions themselves (Sosis and Alcora 2003). A small amount has also been done in the newer field of memetics, treating religious beliefs as a type of meme (Rachlin, 2007), but evolutionary theory hasn’t been directly to religion without the somewhat undefined intermediary of the meme. For example, does the geographic split between the Eastern and Western Orthodox churches represent a form of selection? Can we apply the concept of lateral gene transfer – the idea that genetic information can be transmitted to peers rather than to descendants – to ideas? Given these things, is it then possible to construct phylogenies of religious sects based on when a given theory was accepted or rejected by the sects? To answer these questions, I plan on examining major theological schisms in Christianity and the historical events that lead to them, to see if a historical map of the branchings can be constructed. I am particularly interested in dealing with Christianity as a model, because it’s large, with a long history, and has had a large number of idealogical schisms over that history, resulting in a a multitude of sects which share some central ideals but are otherwise very diverse, to the point of seeming like entirely different religions to outsiders.

Rachlin, Howard. ‘Cui bono? A Review of ‘Breaking the Spell: Religion as a Natural Phenomenon’ by Daniel C. Dennett’. Journal of the Experimental Analysis of Behaviour. 87 (2007): 143–149

Sosis, Richard and Candace Alcora. ‘Signaling, solidarity, and the sacred: The evolution of religious behavior’ Evolutionary anthropology. 12.6 (2003)

Categories
Extra readings language

Classic language evolution paper: Pinker & Bloom 1990

This is mostly just for fun (it’s 50 pages long), and out of historical interest as well: This was the paper where Pinker and Bloom were like “uhhh…guys…yes the royal society(or some other academic society?) did place a ban on the subject of evolutionary linguistics…BUT THAT WAS OVER A CENTURY AGO, AND THINGS HAVE CHANGED! Hello???” and the response ranged between “STFU, you’re nuts” and “OMG I’VE BEEN THINKING THAT ALL ALONG, THANK YOU! =D”. tl;dr — this paper was quite important to the development of the field.

See, when you strip academic discourse of its flowery language, the whole thing degrades to little more than your usual internet flamewar…

Natural Language and Natural Selection — Pinker & Bloom 1990 Behav Sci

PS: Also, I’ve met Pinker =P   Turns out he exudes pure charisma, and his hair is real. Yeah, that’s right, do be jealous.

Categories
MURC proposals

Not everything is an adaptation: applications of neutral evolutionary models outside biology

(my submitted MURC proposal)

Academic disciplines tend to focus on elite groups of particularly charismatic topics. Evolutionary biology traditionally favoured animals – a particularly bizarre offshoot in the world vastly dominated by unicellular lifeforms, thereby not particularly representative of the general mechanisms of evolution. The integration of microbial and molecular evolution has brought some paradigm shifts to biology, such as the neutral theory of evolution (Ohta 1992 Annu Rev Ecol Syst). However, the popularized version used outside biology remains predominantly zoocentric.

Much of ‘traditional’ evolutionary theory, as applied outside biology, tends to focus on heavily selectionist explanations, especially for instances of increased complexity. In evolutionary biology, it is becoming evident that not all increased complexity is adaptive (eg. Stoltzfus 1999 J Mol Evol; Lynch 2007 PNAS), and it would be interesting to extend this paradigm shift to areas of applied evolutionary theory, such as linguistic and cultural evolution.

For example, it has been known in biology that the effective population size impacts the selective ‘tolerance’ in a system, placing heavier pressure on efficiency when these populations are larger, as in prokaryotes, and exhibiting greater lenience in smaller populations, promoting the evolution of cumbersome lifeforms such as mammals (Lynch 2007 PNAS). A recent study (Lupyan & Dale 2010 PLoS ONE) found a tendency for small isolated (esoteric) languages to exhibit higher morphological complexity than their exoteric counterparts. I would like to explore this phenomenon using effective population size, in conjunction with or as a replacement of some explanations offered in the paper, such as simplification by bilingual speakers.

I intend to examine these and other case studies in attempt to examine whether the application of neutral evolutionary models can aid our understanding of non-biological evolution. It is evident that strictly selectionist explanations are insufficient to explain non-biological evolutionary phenomena, which may benefic greatly from a more pluralistic approach.

***

Exam tomorrow morning, so this is all I’m gonna care about. But do leave comments and criticise the hell out of it — will try to get around to this after the break.

Btw, let’s make these drafts suffice for this week’s weekly blog post. Also, would you guys like to make an extra ‘bonus post’ during the reading break to make up for a missing one either from the past or in the future? Would that be fair?

PS: ahhh the fallbacks of being an admin: ALMOST accidentally posted this as a ‘page’ rather than a ‘post’… >_>

Categories
Uncategorized

Animal Cultural and Genetic Evolution

Okay, wordpress is acting insane for me now…

To what extent does cultural evolution influence genetic evolution?

Cultural evolution is well established in humans, and support for its occurrence in other vertebrates continues to grow (1). In humans, cultural evolution has been occasionally known to effect genetic evolution, such as in the retention of lactase activity into adulthood in dairy using cultures (2). Little attention has been paid to the possibilities of cultural influences on animal evolution, however there a several examples in which culture may play a roll in population genetics. In one case, a pair of species of Darwin’s finches which have the ability to hybridize appear to maintain relative genetic isolation due to the learning of song in mate choice (3). In another, beneficial cultural traits which are passed on matrilineally may explain low genetic diversity in several whale species (4).
Cases such as these might be better equipped to answer questions on how culture effects evolution than circumstances involving humans, as animal culture tends to be less complex, and in some cases very well studied (5). To this end, I plan to examine supposed instances of animal cultural evolution effecting genetic evolution, and look for trends. I suspect culture will most strongly effect genetic evolution when it is either passed on from parent to offspring, such as in the finches and whales, or allows the species to exploit a new ecological niche such as lactase in humans.

1. Laland, K., Odling-Smee, J., Myles, S. 2010. How culture shaped the human genome: bringing genetics and the human sciences together. Nature Reviews Genetics. 11: 137-148.

2. Laland, K., Janik, V. 2006. The animal cultures debate. TREE. 21(10) 541 – 546.

3. Grant, R., Grant, P. 1996. Cultural Inheritance of Song and Its Role in the Evolution of Darwin’s Finches. Evolution. 50(6): 2471-2487.

4. Whiehead, Hal. 1998. Cultural Selection and Genetic Diversity in Matrilineal Whales. Science. 282 (5394): 1708 – 1711.

5. Podos, J., Huber, S., Taft, B. 2004. Bird Song: The interface of evolution and mechanism. Annu. Rev. Ecol. Evol. Syst. 2004. 35: 55 – 87.

Categories
language MURC MURC proposals

Peter’s MURC Proposal Draft

AN AUTOPSY OF THORN

Although much scholarly ink has been spilled on the topic of changes in spoken English over the centuries, precious little has been put to paper on the topic of mutations in the orthography, and even less about the phasing in and out of particular characters. In particular, the letter thorn, which started out as a representation of the sound in modern English modeled by the “th”, has had little or no attention paid to it. The question is, why would English adopt this letter into the otherwise Roman alphabet, only to lose it a couple centuries later?
The first step toward answering this question will be to look at the dates during which thorn was used. These can be established fairly easily by examining texts, so as to find its first appearances and its final appearances in the English language. Once these are known, examining the culture and language of the time should be indicative of the rough context in which the thorn was preserved; once these have been established, I would only need to find a set of factors that were lost at roughly the same as the thorn in order to come to a conclusion as to its cause of death, as it were.

Sources:
Nevalainen, Terttu, and Helena Raumolin-Brunberg. Historical Sociolinguistics, Hong Kong: Pearson Education Limited, 2003.

Smith, Jeremy J. An Historical Study of English: Function, Form, and Change. New York: Routledge, 1996.

Categories
MURC MURC proposals

Scott’s MURC proposal – draft

To what extent does imitating biological evolution benefit genetic programming?

Genetic algorithms are a set of search algorithms that have been inspired by biological evolution [holland]. They have been used in applications from *** to creative logo design[blprnt], by using variations of biological mutation, fitness-based selection, and populations.

Over the years, the benefits provided by copying biology have been debated. For example, the inclusion of sexual recombination, which is a part of nearly all plant and animal reproduction, drastically degrades the performance of genetic algorithms [nordin] something which evolutionary biologists still don’t have a computationally sound explanation for in biology (R. Redfield, personal communication, February 4, 2010). On the other hand, biological evolution has produced solutions to many different environmental conditions – from the darkest sea-floors, to the driest deserts – which could be used to inform computer science.

There is already a selection of literature on genetic algorithms which would allow a review to explore which aspects of biological evolution are worth emulating, and which have been unhelpful to the field of computer science.

By summarizing the state of the art of genetic algorithms, and comparing that with an introductory understanding of biology, I hope to describe several mechanisms of biological evolution, how they transfer to genetic algorithms, and present a base comparison of whether they are useful in computer science. Due to the situational nature of the search problems to which genetic algorithms are applied, I would expect categorical classification of benefit of these mechanisms to be difficult.

[holland]
Holland, John H. Adaptation in Natural and
Artificial Systems. Ann Arbor, MI: University
of Michigan Press 1975.

[nordin]
Peter Nordin, Frank Francone, and Wolfgang Banzhaf, 1996, Explicitly defined introns and destructive
crossover in genetic programming, Advances in Genetic Programming 2, chapter 6, pp. 111–134, MIT
Press, Cambridge,MA, USA.

[blprnt] www.blprnt.com/variance/

Categories
Week 5

Crossover in biology and computer science

Last week, Rosie was talking about how biologists are uncertain about the benefits provided by sexual recombination. Particularly, she said something about how ‘the numbers’ don’t show any benefit to the organism for sexual recombination. If I recall correctly, sexual recombination is crossover (that’s how I’m going to treat it for this post and someone needs to correct me if I’m wrong).

Then, in my computer science class today, we were talking about Stochastic Local Search algorithms, of which Genetic Algorithms are a subset, and the lecture presented the introduction of crossover as the defining factor of GAs. The impression that I got was that, in computer science, crossover was assumed to be beneficial. And since computer scientists are generally good at calculating the generalized efficiency of algorithms, I assumed that there must be some fairly definite benefit provided by crossover, which contradicts what Rosie said about the mathematic benefits of biological crossover not adding up.

If GAs in computer science benefit from crossover and biological evolution doesn’t, then I see three possible outcomes. 1) The analogy between GAs and biology break down in this case – which is the default assumption. 2) The computer scientists haven’t done strict tests of crossover, and it will turn out to be unhelpful, as in biology. Or 3) GAs and biology both benefit from crossover, meaning that there will be mathematical models of the benefit of crossover from computer science which might be able to inform biology.

I have some discussion on these three possibilities. But I’m going to have to hold off for now.

Categories
Uncategorized

Mutation and Recombination

Rosie’s lecture got me thinking about my interest in the evolution of imagination, and whether it is useful to postulate ideas or memes as independent of the minds of thier hosts. Bascially, I want to test how far this metaphor can stretch, while remaining critical it might burst.

In genetics, mutations are changes within an individual, like typos in base pairs when DNA polymerase and other repair enzymes fail to spot and fix them. The rate of mutation tends to be very low, a balance between perfect copying and the physiological cost of preventing them.

Recombination of genes happens between (sexual) individuals and no one has yet been able to come up with a good theory of why it occurs when this process does more harm than good in mathematical modelling.

One of the main criticisms of the meme concept is that culture cannot be examined in bits or composed of independent units. But like religion, culture must be made up of something. Even genes do not “work” in isolation, so we should not expect memes to either. Genes used to be fuzzy and invisible too, before we could observe DNA and chromosomes; they are useful theoretical artifacts because when a sequence gets knocked out, it has some observable effect. But can a meme be knocked out and shed light on culture? Not likely.

So what would a meme be, physically? A sequence of neural connections or pattern of activity?

How would a meme mutate or recombine? Does it have fidelity, fecundity, and stability (longetivity)?

In Conceptural Integration Theory (CIT, also known as mental space theory), developed by Gilles Fauconnier and Mark Turner, a set of activated neuronal assemblies are momentarily marked off in a so called “mental space” (imagine a circle with a realistic painting of a woman as the neural pattern, composed of various parts such as head, neck, torso, color, shape, light, etc. and another circle with an African mask as the pattern, also composed of various parts such as head, shape, light, etc.), and the patterns in each space are run together in a simulated new “blended space” (imagine a new circle with Picasso’s famous painting Ladies of Avignon. This is a very crude example, but you get the idea.) Basically, the this theory looks vaguely like a venn diagram using concept maps. It has been critiqued for being fairly empirically untestable so far.

The mental spaces are short term, constructed via information stored in longer term memory networks and associations. In the example of the expression “digging one’s own financial grave,” there is the creation of two maps or “mental spaces” for the domains Grave Digging and Financial Failure, respectively. In each space, there are association networks such as Gravedigger, corpse, and death for “Grave Digging” and the unawareness of consequences, suffering, bad decisions for “Financial Failure” which are blended in a new space to make meaning of the metaphor (Slingerland 2008:178, 186). Blending allows us to conceive of “As if” scenarios, and build upon them, ideas upon ideas, memes spawning more memes.

What I want to ask, is whether this blending is similar to recombination or mutation.

A meme would be a neural pattern that codes for something very simple in a larger association network, such as the shape of a head or an eye, or changes in pitch or the identification and categorization of nouns, verbs, etc. A cluster of memes would code for all kinds of stylistic representations, images of familiar symbols, tunes and story plots. Blending creates new memes, which may be selected for or against depending on the frequency of other memes. For example, if my network of memes related to funerals included links to dark colors, grief, pain, images of dull skies, tears were to suddenly encounter links to funeral jokes, laughter, bright skies, and ritual dancing, there would be competition in terms of the strength of those connections, which links I activate more than others (weak links eventually become extinct), and these depend on the strength of the input signals which I recieve from the larger cultural meme pool. In that way, memes can be said to be independent from their hosts.

There is no blending without input into two or more “mental spaces”. Input must come from past experience and stimuli from other minds, from a memetic environment or community (like a gene pool?). These spaces (chromosomes?) “cross over” in some sense, and elements are thrown away in the process, but it is not reassembled between “two individual hosts” but in the same mind, which then can be communicated to another, etc. New ideas are often intentional, not mistakes in copying, so they don’t really “mutate” in the same sense.

Mutation happens when mistakes are made communicating between minds. It takes a long time to learn how to replicate a letter, to teach a child to write, and reproduce recognizable symbols with stability and fidelity. It takes an even longer time to copy a pattern for a fictional character, which includes all the past experiences, thoughts, feelings, actions, associations, friendships, events, yadda, yadda of that charcter (passed orally or textually, and is prone to mistakes, but there is some stability that there is agreement on someone named Anne of Green Gables or Harry Potter). Sounds may be misheard, but there is enough stability that we can trace those shifts most of the time. Instructions may be lost and the product or technology is left behind for reverse engineering. Nevertheless, there appears to be a certain rate of mutation that makes some memes more fit than others when phemotypically expressed in a cultural artefact, like some tunes that we can’t get rid of, or the ubiquitous smily face.

What does it mean for ideas to mutuate, recombine or blend? Is culture like an organism? Is this a useful metaphor?

Spam prevention powered by Akismet