June 30, 2008
More familiar than we thought
The nearly 10,000 living species of birds are amazingly diverse, and yet we often think of them as being fundamentally different from the more familiar 4000-odd mammalian species. For instance, bird brains are organized very differently from mammals -- birds lack the neocortex that we humans exhibit so prominently, among other things. The tacit presumption derived from this structural difference has long been that birds should not exhibit some of the neurological behaviors that mammals exhibit. And yet, evidence continues to emerge demonstrating that birds are at least functionally very much like mammals, exhibiting tools use, cultural knowledge , long-term planning behavior, and creativity among other things.
A recent study in the Proceedings of the National Academy of Science (USA) adds another trait: sleeping [1,2], at least among song birds. By hooking up some zebra finches to the machinery usually used to measure the brain activity of sleeping mammals, Philip Low and his colleagues discovered that song-bird brains exhibit the same kind of sleeping-brain activity (slow waves, REM, etc.) normally seen in mammals. The authors avoid the simplistic explanation that the cause of this similarity is due to a shared ancestry, i.e., mammalian-style sleep evolved in the common ancestor of birds and mammals, which would be about 340 million years ago (with the origin of the Amniote class of animals). This hypothesis would imply (1) that all birds should sleep this way (but the current evidence suggests that it's only song-birds that do so), and (2) that other amniotes like lizards would have mammalian-like sleep patterns (which they apparently do not).
So, the similarity must therefore be an example of convergent evolution, i.e., birds and mammals evolved this kind of sleep behavior independently. The authors suggest that this convergence is because there are functionally equivalent regions of mammal and bird brains (a familiar idea for long-time readers of this blog)  and that these necessitate the same kind of sleep behavior. That is, song birds and mammals sleep the same way for the same reason. But, without understanding what mammalian-like sleep behavior is actually for, this could be mere speculation, even though it seems like it's on the right track. Given the other similarities of complex behavior seen in birds and mammals, it's possible that this kind of sleep behavior is fundamental to complex learning behaviors, although there could be other explanations too (e.g., see  below). At the very least, this similarity of behavior in evolutionarily very distant species gives us a new handle into understanding why we, and other species, sleep the way we do.
Update 30 June 2008: The New York Times also has an article in its science section about this phenomenon.
 "Mammalian-like features of sleep structure in zebra finches." P. S. Low, S. S. Shank, T. J. Sejnowski and D. Margoliash. PNAS 105, 9081-9086 (2008).
A suite of complex electroencephalographic patterns of sleep occurs in mammals. In sleeping zebra finches, we observed slow wave sleep (SWS), rapid eye movement (REM) sleep, an intermediate sleep (IS) stage commonly occurring in, but not limited to, transitions between other stages, and high amplitude transients reminiscent of K-complexes. SWS density decreased whereas REM density increased throughout the night, with late-night characterized by substantially more REM than SWS, and relatively long bouts of REM. Birds share many features of sleep in common with mammals, but this collective suite of characteristics had not been known in any one species outside of mammals. We hypothesize that shared, ancestral characteristics of sleep in amniotes evolved under selective pressures common to songbirds and mammals, resulting in convergent characteristics of sleep.
 New Scientist has a popular science piece about the PNAS article.
 Mammals and birds have another important convergent similarity: they are both warm-blooded, but their common ancestor was cold-blooded. Thus, warm-bloodedness had to evolve independently for birds and for mammals, a phenomenon known as polyphyly. One interesting hypothesis is that warm-bloodedness and mammalian-like sleep patterns are linked somehow; if so, then presumably sleeping has something fundamental to do with metabolism, rather than learning as is more popularly thought. Of course, the fact that the similarity in sleeping seems to be constrained to song-birds rather than all birds poses some problems for the metabolism idea.
June 23, 2008
Entering orbit around the Googleplex
Attention conservation notice: this is a posting about a workshop at Google's Mountain View complex.
I'll be giving a talk (1:30pm, Building 42, 2nd Floor; not sure if it's open to the public) about complex models of large-scale structure in networks at Google's Mountain View complex tomorrow, as part of a joint SFI workshop entitled "Selection Tinkering and Emergence in Complex Networks." The workshop is part of the Paramaribo Tech Talk series at Google; here's a brief explanation of the event:
This meeting will search for general principles of organization and evolution of natural and artificial systems changing through local rules based on reuse of previously existing substructures. Such a process of "tinkering" makes a big difference (at least in principle) when comparing biological structures and man-made artifacts. As pointed out by the French biologist François Jacob, the engineer is able to foresee the future use of the artifact (i.e. it acts as a designer) whereas evolution does not. The first can ignore previous designs, whereas the second is based on changes taking place by using available structures.
In spite of its apparent drawbacks, tinkering has been able to generate most complex structures observable in the real world (including some in the technological world). Very often, the resulting structures share common principles of organization, suggesting that convergent evolution towards a limited number of basic plans is inevitable. How innovations emerge through evolution is one of the key problems in complexity, and this meeting will focus towards understanding these problems, using several scales of analysis - from cellular networks and tissues to ecosystems - and using network approaches as a quantitative characterization of such complexity.
My contribution, I believe, is to talk about networks and how to extract meaningful information about their large-scale structure.
Update 28 June 2008: The visit to Google went quite well, I think. The Tech Talk was in one of the main buildings, and what seemed like a relatively central place. Throughout the day, Googlers passed by on their way to other places in the complex. During my talk, I noticed a few new faces in the audience, which I can only assume were locals.
What's fascinating about Google is, really its size. My understanding is that the core business -- the one that brings in the majority of the money -- is the AdSense division, which sells keywords to advertisers and places ads on various other sites. The AdSense group itself doesn't require much to run, so there's a tremendous surplus of cash, which Google has apparently been using to grow like crazy and to invest in interesting (but mostly not profitable) projects related to organizing information. In some sense, this makes Google a lot like the old Bell Labs, where massive amounts of extra money were devoted to risky projects, many of which didn't produce anything useful until years or decades later. On the other hand, there's a lot to be said for having a good reputation, and the kind of good PR that Google gets from free but useful products like GoogleEarth, etc. is the kind that you simply can't buy any other way.
Another thing that struck me about the Googleplex was the age demographic. One of my friends from grad school who works there now said that a quarter of everyone he meets has worked there for less time than he has. That's not because there's a high turnover rate, but because Google's just been hiring like crazy. And they've been hiring young people. The vast majority of people I saw were under 40 or so, and a big portion of them were under 30.
So, it's a strange place really -- not like most companies I've interacted with --lots of fringe benefits (free food everywhere, free services like haircuts and shuttles, 20% time to work on your own crazy projects, etc.), lots of freedom, lots of young people, etc. In some sense, the internal corporate philosophy seems to be one of bringing together lots of smart people and giving them the tools, impetus and freedom to do brilliant things. So, it seems like a great place to work, right now. If the cash surplus situation were to change dramatically for some reason (government anti-trust activity a la Microsoft, strong competition from Yahoo! or MSN, a collapse of Internet adversing, etc.), then I'm sure things would change, much as they did for Bell Labs in the 1990s when it was spun out from AT&T.
For researchers, Google seems like a pretty good place to be. The three Googler colleagues of mine that I chatted with while I was there all have PhDs and all seemed to be really happy with their jobs. Of course, none had been there for that long, but one of them, who works on understanding the internal organizational dynamics of the company, mentioned that the retirement / quitting rate is very very low. So, like I said, it seems like a really good place to work, for now.