The unappreciated animals of science

Would you believe it – I actually forgot that I had a blog for a few of weeks. I guess I was busy?

If you don’t work on a particular organism, you tend to forget that each has its own history outside of the laboratory. Catherine Dulac has a great video wild-caught mice: whereas laboratory strains are sedentary, moseying about their cage without a care in the world, wild-caught mice are little ninjas, running around and jumping off the sides. These ain’t the same creatures.

eLife has a good series on the natural history of model organisms. Right now they have C. elegans, zebrafish, and E. coli, though I expect there will be more.

On nasty E. coli:

In 1884, the German microbiologist and pediatrician Theodor Escherich began a study of infant gut microbes and their role in digestion and disease. During this study, he discovered a fast-growing bacterium that he calledBacterium coli commune, but which is now known as the biological rock star that is Escherichia coliE. coli‘s relationship with a host literally begins at birth. Newborns are typically inoculated with maternal E. coli through exposure to her fecal matter during birth and from subsequent handling. Although perhaps disconcerting to ponder, this inoculation seems to be quite important. Indeed, E. coli becomes more abundant in the mother’s microbiome during pregnancy, increasing the chances of her newborn’s inoculation…

The external world was long thought to be so harsh as to preclude E. coli‘s growth outside of its host. While a tiny minority might eventually reach a new host, most cells were expected to eventually die. This is the basal assumption behind using the presence of E. coli as an indicator of fecal contamination. However, recent studies have shown that E. coli can, in fact, establish itself as a member of microbial soil, water, and plant-associated communities

On fishies:

Field observations of zebrafish behavior are few and anecdotal, and so much of what zebrafish do in nature has to be inferred from their behavior in the lab…Interestingly, wild-caught and lab fish (both previously imprinted on the ‘wild type’) have similar preferences for prospective shoaling partners…Lab strains of zebrafish spawn all year round, but breeding in the wild occurs primarily during the summer monsoons, when ephemeral pools appear; these presumably offer plenty to eat and some shelter from currents and predators.

Analyses of wild zebrafish suggest a reason for the discrepancies: these fish have a major sex determinant (WZ/ZZ) on chromosome 4—which has features similar to sex chromosomes in other species—yet this determinant has been lost from lab strains (Wilson et al., 2014). This suggests that founder effects, or domestication itself, led to seemingly ad hoc systems employing multiple sex determinants, probably of small original effect in the wild.

On wormies:

This species was originally isolated in rich soil or compost, where it is mostly found in a non-feeding stage called the dauer. More recently, feeding and reproducing stages of C. elegans have been found in decomposing plant material, such as fruits and thick herbaceous stems. These rotting substrates in their late stages of decomposition provide abundant bacterial food for the nematode…Population demographic surveys at the local scale in orchards and woods indicate that C. elegans has a boom-and-bust lifestyle. C. elegans metapopulations evolve in a fluctuating environment where optimal habitats are randomly distributed in space and time… Over the year, in surveys performed in France and Germany, C. eleganspopulations in rotting fruits typically peak in the fall, with proliferation possible in spring through to early winter…

If not with E. coli, it is noteworthy that C. elegans shares its rotting fruit habitat with two other top model organisms, Drosophila melanogaster and Saccharomyces cerevisiae…A specific association is actually found between another Caenorhabditis species and another Drosophila species: this nematode species, C. drosophilae, feeds on rotting cactus in desert areas and its dauer juveniles use a local Drosophila species as a vector to move between cacti.

Orchid mantis: more interesting than cryptic mimicry

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I know, I know, you read the title and exclaim: what can be more exciting than cryptic mimicry?! Well, listen to this:

On the face of it, this is a classic evolutionary story, and a cut-and-dried case: the mantis has evolved to mimic the flower as a form of crypsis – enabling it to hide among its petals, feeding upon insects that are attracted by the flower…

O’Hanlon and colleagues set about systematically testing the ideas contained within the traditional view of the orchid mantis’ modus operandi. First, they tested whether mantises actually camouflage amongst flowers, or, alternatively, attract insects on their own…

However, when paired alongside the most common flower in their habitat, insects approached mantises more often than flowers, showing that mantises are attractive to insects by themselves, rather than simply camouflaging among the flowers…Surprisingly mantises did not choose to hide among the flowers. They chose leaves just as often. Sitting near flowers did bring benefits, though, because insects were attracted to the general vicinity – the “magnet effect”.

But wait: there’s more!

As an aside, I’ve heard that Preying Mantis’ make great pets. They are social creatures that will creepily watch you everywhere you go, but also kind of ignore you. They’re like insect-cats.

(Photo from)

Science blogs: still kinda there, I guess

I have bemoaned the lack of a neuroscience blogosphere before. Neuroscience blogs exist as independent fiefdoms, rarely responding to one another. And if we were to cut out the cognitive and psychological sides of neuroscience, the field of blogs would be more like a field of half-grown trees cut down and abandoned, with only a rare leaf or two peaking out of the desiccation.

So in the interests of navel-gazing, it is interesting to think about a post from DynamicEcology (Blogs are dying; long live science blogs):

The classic blog is “the unedited voice of an author”, who thinks out loud over an extended period of time and carries on an open-ended conversation with readers who like that author enough to read a significant fraction of his or her posts. That turns out to be a poor way to make money compared to the alternatives, which is a big reason blogs as a whole are dying. Another reason blogs as a whole are dying is that some of things they used to be for are better done via other means (e.g., Twitter for sharing links, various apps for sharing photos and videos). A third reason is that not that many people actually want to blog…

Fortunately, most of the reasons why blogs as a whole are dying don’t apply to science blogs written by academics. Academic scientists have day jobs that often pay pretty well, and tenured ones have as much job security as anyone ever does. Academics don’t need to make money from blogs, they can do it for real but intangible rewards…

So how come there’s no ecology blogosphere? And how come many ecology blogs either have died or post much less often than they used to (e.g., Just Simple Enough*, Jabberwocky Ecology)? And how come new ecology blogs are so scarce, and mostly peter out after only a few posts without ever building much of an audience? Not that you’d expect most ecologists to blog, but so few puzzles me a little. And it’s not just a puzzle for ecology, since there’s no blogosphere worthy of the name for any scholarly field except economics

But Paige Brown Jarreau actually studies this and is writing a dissertation on this. Here is what she has to say:

Many science bloggers I interviewed and surveyed talked about their blogs today as a place for extended thoughts from Twitter and other “faster” social media streams. According to my dissertation data, academics and science writers alike continue to use their blogs…

– as a home for their writing

– as a portfolio

– as a place to be able to write without strict editorial oversight

– as a place to stick extras that don’t fit elsewhere, either in the academic publishing world or in the larger science content ecosystem

– as a place for opinion, interpretation, analysis and curation

– as a place to cover in depth the stories and scientific papers not being covered by the media (what I call Ecosystem Blogging, or covering what’s missing from the existing content ecosystem)

– as a place to add context missing from news and social media

And here is her fantastic network diagram of how blogs are linked (I have a small little dot in between the neuroscience blogs and the ecology blogs, ironically):

BlogsRead_ModularityClass3_InDegreeSize (1)

I only started blogging something like a year or two ago so I certainly couldn’t tell you if blogs are dying or growing or changing or what. Things seem pretty much the same to me. There are a lot of blogs about science and science culture; there are a lot of blogs explaining science to a lay audience; there are a few blogs that discusses the science at a professional level. But I know that there is demand for it; every conference I go to, I meet people who read my blog.

But we can’t pretend that the community isn’t fragmenting in strange ways. Last week, I posted one of my intermittent Monday Open Questions. It got 0 comments on my blog. However! It go comments on Google+ and tons on Twitter. There was a lot of discussion – it just routed around my blog. Blogs aren’t hubs for discussion and interaction they are the start of the conversation.

I always find it a bit of a shame because it is hard to make everything accessible to a large audience. I know there are people who read this blog through my RSS feed, and who read it through G+, and who read it through Twitter, and who just come to it every so often. And they are going to have very different experiences with it.

(As an addendum: it would be quite nice if there was a way to automatically grab responses to specific blog posts on twitter/G+ and embed them in the comments section.)

#Cosyne2015, by the numbers

 

Cosyne2015_posters

Another year, another Cosyne. Sadly, I will be there only in spirit (and not, you know, reality.) But I did manage to get my hands all over the Cosyne abstract authors data…I can now tell you everyone who has had a poster or talk presented there and who it was with. Did you know Steven Pinker was a coauthor on a paper in 2004?!

This year, the winner of the ‘most posters’ award (aka, the Hierarch of Cosyne)  goes to Carlos Brody. Carlos has been developing high-throughput technology to really bang away at the hard problem of decision-making in rodents, and now all that work is coming out at once. Full disclosure notice, his lab sits above me and they are all doing really awesome work.

Here are the Hierarchs, historically:

  • 2004: L. Abbott/M. Meister
  • 2005: A. Zador
  • 2006: P. Dayan
  • 2007: L. Paninski
  • 2008: L. Paninski
  • 2009: J. Victor
  • 2010: A. Zador
  • 2011: L. Paninski
  • 2012: E. Simoncelli
  • 2013: J. Pillow/L. Abbott/L. Paninski
  • 2014: W. Gerstner
  • 2015: C. Brody

CosyneAll_posters

Above is the total number of posters/abstracts by author. There are prolific authors, and there is Liam Paninski. Congratulations Liam, you maintain your iron grip as the Pope of Cosyne.

As a technical note, I took ‘unique’ names by associating first letter of the name with last name. I’m pretty sure X. Wang is at least two or three different people and some names (especially those with an umlaut or, for some reason, Paul Schrater) are especially likely to change spelling from year to year. I tried correcting a bit, but fair warning.

Power law 2004-2015

 

As I mentioned last year, the distribution of posters follows a power law.

But now we have the network data and it is pretty awesome to behold. I was surprised that if we just look at this year’s posters, there is tons of structure (click here for a high-res, low-size PDF version):
ajcCOSYNE_2015_small_image

When you include both 2014 and 2015, things get even more connected (again, PDF version):

ajcCOSYNE_2014-2015_small_image

Beyond this it starts becoming a mess. The community is way too interconnected and lines fly about every which way. If anyone has an idea of a good way to visualize all the data (2004-2015), I am all ears. And as I said, I have the full connectivity diagram so if anyone wants to play around with the data, just shoot me an email at adam.calhoun at gmail.

Any suggestions for further analyses?

 

The not-so frivolous function of play?

We play. Cats play. Dogs play. Horses play. Do fish play? Do cockroaches play? What is the function of play?!

[P]lay is actually at the center of a spectrum of three behavior types: [exploration, play, and stereotypies]. Both exploration and stereotypic behaviors can be easily mistaken for play. Exploration refers to an animal’s reaction to a novel environment or stimuli. For example, if you give a child a new toy, they will generally eagerly take it and examine and manipulate it. However, after thoroughly investigating the new toy, the child may toss it aside and play with their favorite beat-up GI Joe doll…

This doesn’t mean that every species plays, mind you; certainly not every mammal species. Even closely related groups can be vastly different- rats play mountains more than mice do, for example, and some species like aardvarks don’t appear to play at all. Still, almost every major group of mammals has some representatives that show play behavior…

Despite the popular conception that play is practice for later life skills, there is almost zero evidence to back it up. Cats who pounced and batted at objects as kittens were no better at hunting than cats with limited object play;  the same went for coyotes and grasshopper mice. Rats, meerkats, wolves, and many primate species are no better at winning fights based on how often they play fight as youngsters.

Did you know that there is a ‘preeminent play scientist’ and he has five criteria to define play? They are:

  1. The performance of the behavior is not fully functional in the form or context in which it is expressed; that is, it includes elements, or is directed towards stimuli, that do not contribute to current survival.

  2. The behavior is spontaneous, voluntary, intentional, pleasurable, rewarding, reinforcing, or autotelic (done for its own sake).

  3. It differs from the “serious” performance of ethotypic behavior structurally ortemporally in at least one respect: it is incomplete (generally through inhibited or dropped final element), exaggerated, awkward, or precocious; or it involves behavior patterns with modified form, sequencing, or targeting.

  4. The behavior is performed repeatedly in a similar, but not rigidly stereotyped, form during at least a portion of the animal’s ontogeny.

  5. The behavior is initiated when the animal is adequately fed, healthy, relaxed, and free from stress (e. g. predator threat, harsh microclimate, social instability) or intense competing systems (e. g. feeding, mating, predator avoidance).

You have to go read the full article, if for nothing other than all the adorable videos of animals playing.

This is much, much better than that really dumb David Graeber article that science needs to be about play and fun.

Monday Open Question: The unsolved problems of neuroscience?

Over at NeuroSkeptic, there was a post asking “what are the unsolved problems of neuroscience”? For those interested in this type of questions, there are more such questions here and here. This, obviously, is catnip to me.

Modeled on Hilbert’s famous 23 problems in mathematics, the list comes from Ralph Adolphs and has questions such as “how do circuits of neurons compute?” and “how could we cure psychiatric and neurological diseases?” For me, I found the meta-questions most interesting:

Meta-question 1: What counts as understanding the brain?

Meta-question 2: How can a brain be built?

Meta-question 3: What are the different ways of understanding the brain?

But the difference between the lists from Hilbert and Adolphs is very important: Hilbert asked precise questions. The Adolphs questions often verge on extreme ambiguity.

Mathematics has an advantage over biology in its precision. We (often) know what we don’t know. Is neuroscience even at that point? Or would it be more fruitful to propose a systematic research plan?

Me, I would aim my specific questions at something more basic and precise than most of those on the list. For the sake of argument, here are a couple possible questions:

  • Does the brain compute Bayesian probabilities, and if so how? (Pouget says yes, Marcus says no?)
  • How many equations are needed to model any given process in the nervous system?
  • How many distinct forms of long-term potentiation/depression exist?

So open question time:

What (specific) open question do you think is most important?

or What are some particularly fruitful research programs? I am thinking in relation to the Langlands program here.