Study: Men smell and that will stress you out

ferret-specific neurons

A study in Nature Methods has kicked up a bit of a fuss:

In 2007, his lab observed that mice spend less time licking a painful injection—a sign that they’re hurting—when a person is nearby, even if that “person” is a cardboard cutout of Paris Hilton. Other scientists began to wonder if their own data were biased by the same effect. “There were whisperings at meetings that this was confounding research results,” Mogil says.

—–

Male, but not female, experimenters induce intense stress in rodents that can dampen pain responses, according to a paper published today in Nature Methods. Such reactions affect the rodents’ behaviour and potentially confound the results of animal studies, the study suggests.

Yup, the paper says that the stench of men is just plain stressful to rodents. And it’s just human males, but males from many (most?) species.

It is pretty well-established that many animals have neurons that have an innate response to the odor of other animal species. Look at the percent of neurons in the vomeronasal organ (VNO) of the mouse that detect the scent of specific other animals:

Conspecific cells

 

I suppose that means it shouldn’t be surprising that there would be a way to detect males across species. And the data from this paper kinda-sorta points to that: bedding from male guinea pigs, rats, cats, and dogs induced stress-related behaviors but not when the bedding came from castrated males (poor guys). Overall, the affect of the stress was stronger on the female than the male mice.

There are three interesting take-aways from this paper. First, obviously, is that males stress out mice they handle more than females do – and they stress out female mice more than male mice. Second, certain male-specific effects seem to require both an odor and the physical presence of the (male/female) handler. Third, the odor isn’t likely to be a pheromone but rather a complex mix of odors. Three of the stress-inducing odors that they identify are 300 μM (E)-3-methyl-2-hexenoic acid (3M2H), 0.75–3 mM androstenone and 0.75–3 mM androstadienone (4,16-androstadien-3-one), which I’m sure everyone is familiar with! The first is a fatty acid that contributes to “Caucasian male underarm odor” (yum), the second is a steroid found in sweat and urine (and celery), and the third is a metabolite of testosterone.

Also, let’s take a moment to pity the poor grad students who had to take “repeated rectal measurement of core [mouse] body temperature”.

References

Isogai Y, Si S, Pont-Lezica L, Tan T, Kapoor V, Murthy VN, & Dulac C (2011). Molecular organization of vomeronasal chemoreception. Nature, 478 (7368), 241-5 PMID: 21937988

Sorge, R., Martin, L., Isbester, K., Sotocinal, S., Rosen, S., Tuttle, A., Wieskopf, J., Acland, E., Dokova, A., Kadoura, B., Leger, P., Mapplebeck, J., McPhail, M., Delaney, A., Wigerblad, G., Schumann, A., Quinn, T., Frasnelli, J., Svensson, C., Sternberg, W., & Mogil, J. (2014). Olfactory exposure to males, including men, causes stress and related analgesia in rodents Nature Methods DOI: 10.1038/nmeth.2935

Worms, nervous systems, and the beginning of neuroscience

Worms can distinguish between light and dark, and they generally stay underground, safe from predators, during daylight hours. They have no ears, but if they are deaf to aerial vibration, they are exceedingly sensitive to vibrations conducted through the earth, as might be generated by the footsteps of approaching animals. All of these sensations, Darwin noted, are transmitted to collections of nerve cells (he called them “the cerebral ganglia”) in the worm’s head.

“When a worm is suddenly illuminated,” Darwin wrote, it “dashes like a rabbit into its burrow.” He noted that he was “at first led to look at the action as a reflex one,” but then observed that this behavior could be modified—for instance, when a worm was otherwise engaged, it showed no withdrawal with sudden exposure to light.

For Darwin, the ability to modulate responses indicated “the presence of a mind of some kind.” He also wrote of the “mental qualities” of worms in relation to their plugging up their burrows, noting that “if worms are able to judge…having drawn an object close to the mouths of their burrows, how best to drag it in, they must acquire some notion of its general shape.” This moved him to argue that worms “deserve to be called intelligent, for they then act in nearly the same manner as a man under similar circumstances.”

Darwin was discussing the cerebral ganglia of worms in 1881. If you are particularly interested in worms or just plain masochistic, you can find a copy of the book here. It is somehow historically poetic that, by twists and turns, worms have become one of the foundational species of neuroscience research.

Yet it made me realize that I had no idea when the term ‘cerebral ganglia’ first began to be used. When did we realize that we had a ‘nervous system’? I will go into this more in a later post, but the concept began to be used in books around the year 1650 (which is consistent with other sources I have found). On the other hand, we didn’t understand that the neuron was a useful and separate unit until almost 1900!

neuroscience ngram

 

Pyramidal neurons

pyramidal neuronsvia neuroimages, by  Alexandre William Moreau/ Institute of Neurology/ Nikon Small World Competition

 

Nietzsche on science

While searching for the appropriate epigraph for my thesis – y’know, important things – I found a lot of great Nietzsche quotes that vaguely relate to science:

Being deep and appearing deep.–Whoever knows he is deep, strives for clarity; whoever would like to appear deep to the crowd, strives for obscurity. For the crowd considers anything deep if only it cannot see to the bottom: the crowd is so timid and afraid of going into the water.

Profundity of thought belongs to youth, clarity of thought to old age.

There are no facts, only interpretations.

There cannot be a God because if there were one, I could not believe that I was not He.

It is my ambition to say in ten sentences what others say in a whole book.

The man of knowledge must be able not only to love his enemies but also to hate his friends.

Cause and effect: such a duality probably never exists; in truth we are confronted by a continuum out of which we isolate a couple of pieces, just as we perceive motion only as isolated points and then infer it without ever actually seeing it. The suddenness with which many effects stand out misleads us; actually, it is sudden only for us. In this moment of suddenness there are an infinite number of processes which elude us. An intellect that could see cause and effect as a continuum and a flux and not, as we do, in terms of an arbitrary division and dismemberment, would repudiate the concept of cause and effect and deny all conditionality.

Convictions are more dangerous enemies of truth than lies.

What are man’s truths ultimately? Merely his irrefutable errors.

What then is truth? A mobile army of metaphors, metonyms, and anthropomorphisms — in short, a sum of human relations, which have been enhanced, transposed, and embellished poetically and rhetorically, and which after long use seem firm, canonical, and obligatory to a people: truths are illusions about which one has forgotten that is what they are; metaphors which are worn out and without sensuous power; coins which have lost their pictures and now matter only as metal, no longer as coins.
We still do not know where the urge for truth comes from; for as yet we have heard only of the obligation imposed by society that it should exist: to be truthful means using the customary metaphors – in moral terms, the obligation to lie according to fixed convention, to lie herd-like in a style obligatory for all…

Nietzsche loved to pile endless epigrams in his book; he was essentially the greatest Twitter philosopher of all time. Not only was he fairly straightforward in how he presented his ideas, but he was a great stylist. Read, say, Twilight of the Idols and then Dostoevsky’s Notes from Underground and tell me they aren’t both products of similar minds.

Whitespace popout

whitespace

Apologies for all these images that I’m posting, I promise I’m not turning this into my tumblr. I’m just a tad bit busy finishing my thesis with little time to write cogently about science. So enjoy this example of your visual system screwing with you.

Have you tried optogenetics?

optogenetics

It has become pretty common to see someone, after a neuroscience talk, ask, “Interesting – but have you tried doing this with optogenetics?” As if this technique to precisely activate neurons was something that was trivial to implement. It’s not, obviously, it’s quite expensive and hard (for many systems). Otherwise everyone would be doing it already! Who wouldn’t want to turn neurons on and off at will?

Florian Engert, who imaged all the neurons in the zebrafish brain, used this picture at the end of his talk at CSHL Synapses last year when asking for suggestions on experiments.

[via Cian O’Donnell]

‘Primitive’ cardiovascular systems

A 520-million year old cardiovascular system:

It was both modern and unsophisticated. A simple, tubelike heart was buried in the creature’s belly—or thorax—and shot single blood vessels into the 20 or so segments of its primitive body. In contrast, x-ray scans of the specimen revealed profoundly intricate channels in the head and neck. The brain was well supplied with looping blood vessels, which extended branches into the arthropod’s alienlike eyestalks and antennae and rivaled the complexity of today’s crustaceans.

The study of cardiovasculature is actually extremely important to understanding neuroscience. There is a complicated apparatus in the brain designed to interact with the vasculature in order to get ATP (energy), etc. Though a commenter (Ginny Freeman) notes:

The “heart” was NOT buried in the “creature’s belly”. It’s a crustacean, for heaven’s sake! Crustaceans like all arthropods have a DORSAL circulatory system.

Here is the original paper.

Information theory of behavior

Biology can tell us what but theory tells us why. There is a new issue of Current Opinion in Neurobiology that focuses on the theory and computation in neuroscience. There’s tons of great stuff there, from learning and memory to the meaning of a spike to the structure of circuitry. I have an article in this issue and even made the cover illustration! It’s that tiny picture to the left; for some reason I can’t find a larger version but oh well…

Our article is “Information theory of adaptation in neurons, behavior, and mood“. Here’s how it starts:

Recently Stephen Hawking cautioned against efforts to contact aliens [1], such as by beaming songs into space, saying: “We only have to look at ourselves to see how intelligent life might develop into something we wouldn’t want to meet.” Although one might wonder why we should ascribe the characteristics of human behavior to aliens, it is plausible that the rules of behavior are not arbitrary but might be general enough to not depend on the underlying biological substrate. Specifically, recent theories posit that the rules of behavior should follow the same fundamental principle of acquiring information about the state of environment in order to make the best decisions based on partial data

Bam! Aliens. Anyway, it is an opinion piece where we try to push the idea that behavior can be seen as an information-maximization strategy. Many people have quite successfully pushed the idea that sensory neurons are trying to maximize their information about the environment so that they can represent it as well as possible. We suggest that maybe it makes sense to extend that up the hierarchy of biology. After all, people generally hate uncertainty, a low information environment, because it is hard to predict what is going to happen next.

Here is an unblocked copy of the article for those who don’t have access.

References

Sharpee, T., Calhoun, A., & Chalasani, S. (2014). Information theory of adaptation in neurons, behavior, and mood Current Opinion in Neurobiology, 25, 47-53 DOI: 10.1016/j.conb.2013.11.007

Keeping up with the scientific Joneses

It’s really hard to find relevant articles in the morass of papers that are out there. xcorr has an excellent post up detailing recommendations on how to keep up with the scientific literature:

To do good research, you have to be well-informed of the latest scientific developments both in your narrow field of study and in science at large. I recommend the following workflow to make this as painless as possible:

  • Use feedly to keep up-to-date with blogs, journals
  • Use PubChase to get personalized paper recommendations
  • Use Zotero to organize papers you read
  • Use PaperShip to read and comment on papers on your iPad

Here’s a more detailed exposition, along with further resources and alternatives, to help you keep up the scientific literature.

I currently just use feedly, which means every wednesday/thursday I am flooded with articles (I think I subscribe to ~20 different journal feeds?), and every day brings new and relatively useless articles from a few static pubmed rss feeds. It sounds like I need to get started using PubChase!

How should you judge a theoretical model?

When faced with a model of the world (in physics, neuroscience, economics, ecology), how should you judge that theory? Cyrus Samii suggests 5 ways. Here is number 2:

2. If any result can be engineered then results themselves have no special ontological status.

This is another way of asking whether a model has empirical content, which we typically take as falsifiability. Yet Karl Popper suggested:

The empirical content of a statement increases with its degree of falsifiability: the more a statement forbids, the more it says about the world of experience.

And he suggested “two criteria determine the empirical content of a theory are their level of universality (Allgemeinheit) and their degree of precision (Bestimmtheit).”

I also really like the question at the start of number 4:

How complicated can the problems be that we allow our agents to solve in a model? Is a dynamic program ever admissible as a reasonable assumption on the objective function of an agent?

Charles Krebs (or Judy Myers) says:

Recommendation – no paper on models should be published or talked about unless it makes specific, testable predictions of how the model can be tested.

I actually disagree with this rather strenuously. There are several reasons to make models, only one of which is to make predictions. Another is to confirm hypotheses.

Let’s say that you think that honeybees are dying because of the excessive use of mint toothpaste and you collect data to prove it. The problem is that data is simply a collection of facts (or “facts”) with no organizing structure. A model can give those facts that structure: you put what you know together with some of the data, and see if what you know is sufficient to replicate the observations of the world. Of course, you have to interpret these types of models carefully; they are not predictive models in the sense that they tell you anything about the world. Rather, they tell you about whether you have a consistent and complete story. But it’s still just a story.