John Nash, 1928 – 2015

Sad news that John Nash was killed yesterday when his taxi crashed on its way back from the airport. He and his wife were ejected from the taxi when it ran into the lane divider.

Nash is most famous from his biopic A Beautiful Mind though obviously it is his intellectual contributions that you should know about.

His 30 page PhD thesis was what won him the Nobel Prize. His work on game theory was influential not just in economics, but psychology and ecology among other fields.

Recently declassified letters to the NSA show how Nash was foundational to modern cryptography and its reliance on computational complexity. This is the description he included in his letter:


When he was killed, he was returning from Norway where he received the Abel prize for work on nonlinear partial differential equations.

He continued to publish; his final paper (afaik) was “The agencies method for coalition formation in experimental games

He also maintained (?) a delightfully minimalist personal web page.

When did we start using information theory in neuroscience?

This question came up in journal club a little while ago.

The hypothesis that neurons in the brain are attempting to maximize their information about the world is a powerful one. Although usually attributed to Horace Barlow, the idea arose almost immediately after Shannon formalized his theory of information.

Remember, Shannon introduced information theory in 1948. Yet only four years later, MacKay and McCulloch (of the McCulloch-Pitts neuron!) published an article analyzing neural coding from the perspective of information theory. By assuming that a neuron is a communication channel, they wanted to understand what is the best ‘code’ for a neuron to use – a question which was already controversial in the field (it seems as if the dead will never die…). Specifically, they wanted to compare whether the occurrence of a spike was the informative signal or whether it was the time since the previous spike. They found, based on information theory, that it is the interval from the previous spike that can signal the most information.

And for those who want to break into the analog vs digital coding they have this to say:

nor is it our purpose in the following investigation to reopen the “analogical versus digital” question, which we believe to represent an unphysiological antithesis. The statistical nature of nervous activity must preclude anything approaching a realization in practice of the potential information capacity of either mechanism, and in our view the facts available are inadequate to justify detailed theorization at the present time

Around the same time, Von Neumann – of course it would be Von Neumann! – delivered a series of lectures analyzing coding from the perspective of idealized neurons of the McCulloch-Pitts variety. Given that these were lectures around the time of the publication of the work in the preceding paragraph, I am guessing that he knew of their work – but maybe not!

In 1954, Attneave looked at how visual perception is affected by information and the redundancy in the signal. He provides by far the most readable paper of the bunch. Here is the opening:

In this paper I shall indicate some of the ways in which the concepts and techniques of information theory may clarify our understanding of visual perception. When we begin to consider perception as an information-handling process, it quickly becomes clear that much of the information received by any higher organism is redundant. Sensory events are highly interdependent in both space and time: if we know at a given moment the states of a limited number of receptors (i.e., whether they are firing or not firing), we can make better-than-chance inferences with respect to the prior and subsequent states of these receptors, and also with respect to the present, prior, and subsequent states of other receptors.

He also has this charming figure:

Attneave's cat

What Attneave’s Cat demonstrates is that most of the information in the visual image of the cat – the soft curves, the pink of the ears, the flexing of the claws – are totally irrelevant to the detection of the cat. All you need is a few points with straight lines connecting them, and this redundancy is surely what the nervous system is relying on.

Finally, in 1955 there was a summer research school thingamajig hosted by Shannon, Minsky, McCarthy and Rochester with this as one of the research goals:

1. Application of information theory concepts to computing machines and brain models. A basic problem in information theory is that of transmitting information reliably over a noisy channel. An analogous problem in computing machines is that of reliable computing using unreliable elements. This problem has been studies by von Neumann for Sheffer stroke elements and by Shannon and Moore for relays; but there are still many open questions. The problem for several elements, the development of concepts similar to channel capacity, the sharper analysis of upper and lower bounds on the required redundancy, etc. are among the important issues. Another question deals with the theory of information networks where information flows in many closed loops (as contrasted with the simple one-way channel usually considered in communication theory). Questions of delay become very important in the closed loop case, and a whole new approach seems necessary. This would probably involve concepts such as partial entropies when a part of the past history of a message ensemble is known.

Shannon of course tried to have is cake and eat it too by warning of the dangers of misused information theory. If you are interested in more on the topic, Dimitrov, Lazar and Victor have a great review.

So there you go – it is arguably MacKay, McCulloch, Von Neumann, and Attneave who are the progenitors of Information Theory in Neuroscience.


Attneave, F. (1954). Some informational aspects of visual perception. Psychological Review, 61 (3), 183-193 DOI: 10.1037/h0054663

Dimitrov, A., Lazar, A., & Victor, J. (2011). Information theory in neuroscience Journal of Computational Neuroscience, 30 (1), 1-5 DOI: 10.1007/s10827-011-0314-3

MacKay, D., & McCulloch, W. (1952). The limiting information capacity of a neuronal link The Bulletin of Mathematical Biophysics, 14 (2), 127-135 DOI: 10.1007/BF02477711

von Neumann (1956). Probabilistic logics and the synthesis of reliable organisms from unreliable components Automata Studies

Unrelated to all that, 5/15 edition

Is math in economics just sleight of hand?

via Noah Smith/Justin Wolfers

Welcome to the analome

I’ll let you guess what this is an -ome of…

The National Geographic Photo Contest

walks on water bolivia

The Great Pheasant Mating Dance

Birds, people, insects, we are all the same

The importance of penis length (in an insect)

importance of penis length

I’ll just leave this here.

The two scientific cultures: publications or citations?

I would much rather graduate with three papers cited twenty times each than twenty papers cited three times each.*

That fact drives how I do think about publishing my results:

If I wanted to published the maximum number of papers per dataset, I’d be worried about including too much data in any given paper because, once it was published other researchers might take that data and do the same analyses I was planning to do in a followup paper.

If I want my paper to be cited as much as possible though the opposite is true. I WANT my data to be as useful and accessible as possible because it will increase the number of other groups who will use that data, and cite my work when they publish their next paper.

In neuroscience, the “high prestige” positions are three papers cited twenty times; I am not sure if that is good.

Fishes escape from sharks…sometimes

A cover shows fish escape waves from sharks

fish escape waves


But sometimes they’re busy doing other things (mating) –

no fish escape waves

(via Johann Mourier)

DREADD users blog

Lots of good stuff on this blog! Check it out if you even have a passing interest in DREADDs.

The Evolution of Popular Music: USA 1960-2010

musical revolutions

There have been three music revolutions since 1960: in 1963, 1982, and 1991

Logothetis, animal rights extremists, and support

While I was on an accidental blogging sabbatical, Nikos Logothetis stopped his work on non-human primates because of pressure from animal rights groups:

Logothetis’s research on the neural mechanisms of perception and object recognition has used rhesus macaques with electrode probes implanted in their brains. The work was the subject of a broadcast on German national television in September that showed footage filmed by an undercover animal rights activist working at the institute. The video purported to show animals being mistreated.

Logothetis has said the footage is inaccurate, presenting a rare emergency situation following surgery as typical and showing stress behaviors deliberately prompted by the undercover caregiver. (His written rebuttal is here.) The broadcast triggered protests, however, and it prompted several investigations of animal care practices at the institute. Investigations by the Max Planck Society and animal protection authorities in the state of Baden-Württemberg found no serious violations of animal care rules. A third investigation by local Tübingen authorities that led to a police raid at the institute in late January is still ongoing.

Although this has been covered well elsewhere, I figured it was worth posting because it has seemed to disappear into the ether of conversation. It’s just last week’s news! But the effects of are long-lasting. The Center for Integrative Neuroscience, where Logothetis works, has a motion for solidarity which you should take a moment to sign.

His most-cited paper used monkeys to compare local field potentials (neural electrical activity) and fMRI BOLD signals. Here are two relevant figures comparing the two:


He has many good papers studying vision. He also tried studying consciousness using vision once upon a time. So there’s that.

Karl Deisseroth’s New Yorker profile

The New Yorker has profiled Karl Deisseroth. I liked this paragraph which is an excellent description of his personality:

The Stanford neuroscientist Rob Malenka, who oversaw Deisseroth’s postdoctoral work, told me that in some ways he underestimated his trainee. “I knew he was really smart. I didn’t appreciate that underneath that laid-back, almost surfer-dude kind of persona is this intense creative and intellectual drive, this intense passion for discovery. He almost hides it by his presentation.”

I did not know this; let’s hope it is better than Ramon y Cajal’s science fiction:

His initial dream, in fact, was to write. He took writing courses as an undergraduate, and when he was a graduate student in both medicine and neuroscience at Stanford he took a fiction-writing class that met two nights a week at a junior college nearby. He remains an avid reader of fiction and poetry, and he is polishing a book of short stories and essays loosely inspired by Primo Levi’s “The Periodic Table.”

We are bombarded with the ‘genius’ and ‘superhuman that needs no sleep’ myths so much that it is worthwhile to see the New Yorker nix that one:

The doubts only motivated Deisseroth. “I felt a sort of personal need to see what was possible,” he says. Malenka told me that this understates the case considerably: “There’s this drive of, like, ‘You think I’m wrong about this, motherfucker? I’m going to show you I was right.’ ” Deisseroth began working furiously. “He was getting up at 4 or 5 A.M. and going to bed at one or two,” Monje says. He kept up this schedule for five years, until optogenetic experiments began working smoothly. “There are people who don’t need as much sleep,” Monje says. “Karl is not one of those people. He’s just that driven.”

But of course this is the best paragraph. I am guessing Deisseroth’s wife still doesn’t quite know understand what she’s dealing with (because it’s so strange):

Deisseroth estimates that optogenetics is now being used in more than a thousand laboratories worldwide, and he takes twenty minutes every Monday morning to sift through written requests for the opsins. It was not until Monje joined her husband at a recent neuroscience conference in Washington, D.C., that she understood the fame that optogenetics had brought him. “People were stopping us at the airport asking to take a picture with him, asking for autographs,” she said. “He can’t walk through the conference hall—there’s a mob. It’s like Beatlemania. I realized, I’m married to a Beatle. The nerdy Beatle.”

I hosted Karl Deisseroth when he visited UCSD last year. He struck me as very humble yet ambitious. Many ‘famous’ researchers come across as a bit airy when they speak of future research, but Deisseroth was very serious about the strengths and weaknesses of everything he did. The most interesting thing that he said was in response to a question about his papers getting a zillion citations. He claimed that it made them work more slowly and carefully; that they published less than they could have because, instead of needing to be 95% certain that what did was correct, they needed to be 99.9% certain. Everything they publish will be put under a microscope (so to speak).

The future ecology of stock traders

I am beyond fascinated by the interactions between competing intelligences that exist in the stock market. It is a bizarre mishmash of humans, AIs, and both (cyborgpeople?).

One recent strategy that exploits this interaction is ‘spoofing‘. The description from the link:

  • You place an order to sell a million widgets at $104.
  • You immediately place an order to buy 10 widgets at $101.
  • Everyone sees the million-widget order and is like, “Wow, lotta supply, the market is going down, better dump my widgets!”
  • So someone is happy to sell you 10 widgets for $101 each.
  • Then you immediately cancel your million-widget order, leaving you with 10 widgets for which you paid $1,010.
  • Then you place an order to buy a million widgets for $101, and another order to sell 10 widgets at $104.
  • Everyone sees the new million-widget order, and since no one has any attention span at all, they are like, “Wow, lotta demand, the market is going up, better buy some widgets!”
  • So someone is happy to buy 10 widgets from you for $104 each.
  • Then you immediately cancel your million-widget order, leaving you with no widgets, no orders and $30 in sweet sweet profits.

Amusingly enough, you don’t even need a fancy computer program for it – you can just hire a bunch of people who are really good at fast video games and they can click click click those keys fast enough for you.

Now some day trader living in his parent’s basement is accused of using this technique and causing the flash crash of 2010 (it possibly wasn’t him directly, but he could have caused some cascade that led to it).

I’m sitting here with popcorn, waiting to see how the ecosystem of varied intelligences evolves in competition with each other. Sounds like Wall Street needs to take some crash courses in ecology.

The Journal of Invited Dissent

“Why aren’t there comments on academic articles?” someone asked me over coffee (yes, I have exciting coffee conversations). “People should point out how silly a lot of this stuff is.”

I shrugged. “Politics,” I said. “Look at the head of any lab: they’ll rip apart a paper in their lab meetings, and then won’t say much in public. They need to keep a congenial public face because those other scientists will be reviewing their papers.”

The truth is there are comment sections on a lot of scientific articles, they are just barely used, or are used poorly (random rants, irrelevant commentary, etc.)

My companion suggested that what we really need is a journal offering critical commentary on other articles: and not just the bad, but the good as well. What does this really say? What is interesting or uninteresting?

This is the Journal of Invited Dissent. Would it work? Probably not: there is too much incentive to keep the veneer of bland congeniality in public. But there is an example of what it might look like (it was not what spurred the conversation above, but it is telling that the problem repeatedly pops up).

Bjorn Brembs has taken exception to an article published in Nature Neuroscience last year. He found the article to be overhyped and under-referenced (though still interesting and useful!). Although he wrote a letter to the editor at NN, they basically shrugged with comments such as “I agree that the article’s tone is a little more breathless than strictly required, but this is the style presently in vogue”.

So he posted the letter to the comments section at PubMed! Something you probably did not even know existed, and are likely to ignore even if you do know of it. And even better, the senior author on the paper publicly responded in the comments!

And these comments illustrate exactly why they are needed: they provide much-needed context outside of the ‘hype’ needed to publish in a high-profile journal. They shine light on the scientific crevices that those few of you who are not experts in motor learning might otherwise pass by.

Whither experimental economics?

When I was applying to graduate school, I looked at three options: neuroscience, computer science, and economics. I had, effectively, done an economics major as an undergrad and had worked at an economic consulting firm. But the lack of controlled experimentation in economics kept me from applying and I ended up as a neuroscientist. (There is, of course, a very experimental non-human economics which goes by the name of ecology, though I did not recognize it at the time.)

I profess to being confused as to the lack of experimentation in economics, especially for a field that constantly tries to defend its status as a science. (Well, I understand: incentives, existing capabilities, and all that.)

A recent dissertation on the history of experimental economics – as opposed to behavioral economics – is enlightening:

“We were describing this mechanism and Vernon says, “You know, I can test this whether it works or not.“ I said, “What do you mean?“ And he says, “I’ll run an experiment.“ I said, “What the heck are you talking about? What do you do?“ And so he hauls seven or eight graduate students into a classroom. He ran the mechanism and it didn’t work. It didn’t converge to the equilibrium. It didn’t produce the outcomes the theory said it would produce. And I thought, okay. So back to [doing] theory. I don’t care; this doesn’t bother me.

It bothered Vernon a lot because we sat around that evening talking and he says, “Oh, I know what I did wrong.“ And he went back the next day and he hauled the students back in the room, changed the rules just a little bit in ways that the theory wouldn’t notice the difference. From our theory point of view, it wouldn’t have mattered. But he changed the rules a little bit and bang that thing zapped in and converged.“

The difference between the two experiments was the information shared with the test subjects. The first time around, the subjects wrote down their number on a piece of paper and then Smith wrote them up on the board. Then he asked the subjects to send another message and if the messages were the same twice in a row he would stop, since that stability would be interpreted as having reached equilibrium. But the messages did not stop the first time Smith had run the experiment a day earlier…

The fact that the experiment did not converge at the first attempt, but did at the second with a change of only one rule (the information structure available to the participants) not required by theory to make its prediction made a lasting impact on Ledyard.

And this is exactly why we do experiments:

[T]he theory didn’t distinguish between those two rules, but Vernon knew how to find a rule that would lead to an equilibrium. It meant he knew something that I didn’t know and he had a way of demonstrating it that was really neat.

In psychology and neuroscience, there are many laboratories doing animal experiments testing some sort of economic decision-making hypothesis, though it is debatable how much of that work has filtered into the economic profession. What the two fields could really use, though, are economic ideas about more than just basic decision-making. Much of economics is about markets and mass decisions; there is very animal experimentation of these questions.

(via Marginal Revolution)

Richard Lewontin: some perspectives on the sociology of ecology

There’s an interesting interview with Richard Lewontin over at the Evolution Institute.

First, he slags off Steven J Gould a bit:

RL: Now I should warn you about my prejudices. Steve and I taught evolution together for years and in a sense we struggled in class constantly because Steve, in my view, was preoccupied with the desire to be considered a very original and great evolutionary theorist. So he would exaggerate and even caricature certain features, which are true but not the way you want to present them. For example, punctuated equilibrium, one of his favorites. He would go to the blackboard and show a trait rising gradually and then becoming completely flat for a while with no change at all, and then rising quickly and then completely flat, etc. which is a kind of caricature of the fact that there is variability in the evolution of traits, sometimes faster and sometimes slower, but which he made into punctuated equilibrium literally. Then I would have to get up in class and say “Don’t take this caricature too seriously. It really looks like this…” and I would make some more gradual variable rates. Steve and I had that kind of struggle constantly. He would fasten on a particular interesting aspect of the evolutionary process and then make it into a kind of rigid, almost vacuous rule, because—now I have to say that this is my view—I have no demonstration of it—that Steve was really preoccupied by becoming a famous evolutionist.

And then his former advisor:

RL: Now, historically one of the most interesting—now I want to talk a little about the sociology of our science—Theodosius Dobzhansky, my professor and then greatest living evolutionary biologist…

DSW: Mr. “Nothing in biology makes sense except in the light of evolution…”

RL: Yeah, right. He was a very bad field observer. Theodosius Dobzhansky never, in his entire life, nor any of his students, me included—I would go out in the field with him, actually–ever saw a Drosophila pseudoobscura in its natural habitat…We didn’t know where they laid their eggs. We couldn’t have counted the number of eggs of different genotypes. How did we study Drosophila in the wild? We went out into the desert, into Death Valley, we moved into a little oasis, we went first to the grocery store, and bought rotten bananas. We mushed up the bananas with yeast till they fermented a bit, we dumped that into the paper containers, put it out in the field and the flies came to us…If I wanted to study evolutionary forces acting on some genetic polymorphism in Drosophila, I would go and look for some species of Drosophila where I could actually look at, perturb, and work with the actual breeding sites and egg laying sites and pick up larvae in nature and so on. And in fact there is such a group of Drosophila. They the cactophilic ones. There is a group [of scientists] from Texas and other places that studies the cactophilic Drosophila in an ecologically sensible way of going to the rot pockets and perturbing them, getting larvae out of them and so on. That group never acquired the prestige associated with the Dobzhansky school because—I don’t know why.

Lewontin is not normally my cup of tea, but this view is very interesting.

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.