#Cosyne17, by the numbers (updated)


Cosyne is the Computational and Systems Neuroscience conference held every year in Salt Lake City (though – hold the presses – it is moving to Denver in 2018). It’s status as the keystone Computational and Systems Neuro conference makes it a fairly good representation of what the direction of the field is. Since I like data, here is this year’s Cosyne data dump.

First is who is the most active – and this year it is Jonathan Pillow who I dub this year’s Hierarch of Cosyne. The most active in previous years are:

  • 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
  • 2016: X. Wang


If you look at the total number of posters across all of Cosyne’s history, Liam Paninski is and probably always will be the leader. Evidently he was so prolific in the early years that they had to institute a new rule to nerf him like some overpowered video game character.

Visualizing the network diagram of co-authors also reveals a lot of structure in the conference (click for PDF):


And the network for the whole conference’s history is a dense mess with a soft and chewy center dominated by – you guessed it – the Paninski Posse (I am clustered into Sejnowski and Friends from my years at Salk).


People on twitter have seemed pretty excited about this data, so I will update this later with a link to a github repository.

Speaking of twitter, it is substantially more active than it has been in the past. Neuroscience Twitter keeps growing and is a great place to learn about new ideas in the field. Here is a feed of everyone that is attending that is on Twitter. Let me know if you want me to add you.

There are two events you should consider attending if you are at Cosyne: the Simons Foundation is hosting a social on Friday evening and on Saturday night there is a Hyperbolic Cosyne Party which you should RSVP to right away…!

On a personal note, I am giving a poster on the first night (I-49) and am co-organizing a workshop on Automated Methods for High-Dimensional Analysis. I hope to see you all there!

Previous years: [2014, 2015, 2016]


Update – I analyzed a few more things based on new data…


I was curious which institution had the most abstracts (measured by the presenting author’s institution.) Then I realized I had last year’s data:


Somehow I had not fully realized NYU was so dominant at this conference.

I also looked at which words are most enriched in accepted Cosyne abstracts:acceptedwords

Ilana said that she sees: behavior. What is enriched in rejected abstracts? Oscillations, apparently (this is a big topic of conversation so far) 😦rejectedwords

Finally, I clustered the most common words that co-occur in abstracts. The clusters?

  1. Modeling/population/activity (purple)
  2. information/sensory/task/dynamics (orange)
  3. visual/cortex/stimuli/responses (puke green)
  4. network/function (bright blue)
  5. models/using/data (pine green)


Sophie Deneve and the efficient neural code

Neuroscientists have a schizophrenic view of how neurons. On the one hand, we say, neurons are ultra-efficient and are as precise as possible in their encoding of the world. On the other hand, neurons are pretty noisy, with the variability in their spiking increasing with the spike rate (Poisson spiking). In other words, there is information in the averaged firing rate – so long as you can look at enough spikes. One might say that this is a very foolish way to construct a good code to convey information, and yet if you look at the data that’s where we are*.

Sophie Deneve visited Princeton a month or so ago and gave a very insightful talk on how to reconcile these two viewpoints. Can a neural network be both precise and random?

Screen Shot 2016-04-23 at 11.06.22 AM Screen Shot 2016-04-23 at 11.06.27 AM

The first thing to think about is that it is really, really weird that the spiking is irregular. Why not have a simple, consistent rate code? After all, when spikes enter the dendritic tree, noise will naturally be filtered out causing spiking at the cell body to become regular. We could just keep this regularity; after all, the decoding error of any downstream neuron will be much lower than for the irregular, noisy code. This should make us suspicious: maybe we see Poisson noise because there is something more going on.

We can first consider any individual neuron as a noisy accumulator of information about its input. The fast excitation, and slow inhibition of an efficient code makes every neuron’s voltage look like a random walk across an internal landscape, as it painstakingly finds the times when excitation is more than inhibition in order to fire off its spike.

So think about a network of neurons receiving some signal. Each neuron of the network is getting this input, causing its membrane voltage to quake a bit up and a bit down, slowly increasing with time and (excitatory) input. Eventually, it fires. But if the whole network is coding, we don’t want anything else to fire. After all, the network has fired, it has done its job, signal transmitted. So not only does the spike send output to the next set of neurons but it also sends inhibition back into the network, suppressing all the other neurons from firing! And if that neuron didn’t fire, another one would have quickly taken its place.network coding


This simple network has exactly the properties that we want. If you look at any given neuron, it is firing in a random fashion. And yet, if you look across neurons their firing is extremely precise!

* Okay, the code is rarely actually Poisson. But a lot of the time it is close enough.


Denève, S., & Machens, C. (2016). Efficient codes and balanced networks Nature Neuroscience, 19 (3), 375-382 DOI: 10.1038/nn.4243

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

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.

Vernon B. Mountcastle

Matteo Farinella Blog

This month neuroscience lost one of its great masters: Vernon B. Mountcastle, who first discovered the columnar organization of the cerebral cortex. His pioneering work has been awarded many prizes and laid the foundations for a lot of contemporary research in the field (including my PhD). Many excellent articles have already been written about it, but I wanted to pay my personal tribute to this great explorer of the brain. Here is how he would have appeared in Neurocomic, reaching new peaks of scientific discovery:Mountcastle Farinella LowRes

View original post

Unrelated to all that, 11/22 edition

Scabs, Scantrons, and Strikes at the University of Oregon

At the heart of the dispute is a demand by the Graduate Teaching Fellows Federation (GTTF) for two weeks of paid leave for illness or childbirth. The city of Eugene, which is where the University is located, mandates that all workers in the city get sick leave benefits. But university employees are exempted from the policy, so the GTTF has to bargain for the benefits.

Late last month senior administrators circulated a secret memorandum to deans and directors outlining a plan to break the strike by hiring scab labor and weakening academic standards for undergraduate education. You’ve got to read the whole thing to believe it, but here are some of my favorite parts. First, the administration moots different possibilities for conscripting scab labor from the unionized faculty ranks…

The article speaks for itself…

Deciphering the syntax of Nature article titles

We all want to publish in Nature. Papers in Nature are (supposed to be) the complete package: reliable results that show something novel; cool techniques; a famous corresponding author. And if you want to get one, you need a title that shows you are a refined gentleperson who belongs in the Nature club.

So to help you, dear blog reader, I have scoured the archives of Nature* to decipher the ideal form of Nature titles:

[research-y verb-ing] a neural circuit for [behaviour]

The 24 hour science challenge

The basic premise is to develop, perform analysis, and write up a scientific project within a 24-hour period. The results should be posted on a public repository for the world to see.

Check out the rules here.

Who’s with me?

The Poop Map of San Francisco


Why More Diversity on Wall Street Might Fight Bubbles

The results were striking. In the markets with ethnic diversity, prices became 21 percent more accurate, relative to the fundamentals of the stocks, as trading proceeded. But in the homogenous markets, pricing accuracy declined by 33 percent over the course of the simulation.

In other words, when a bunch of white guys are trading among themselves, they are more likely to drive prices to irrational levels than when there is more diversity among their trading partners.

“Traders in homogenous markets are more likely to accept offers that are farther from true value,” the authors write. “This supports the notion that traders in homogenous markets place undue trust in the decisions of others — they are more likely to spread others’ errors by accepting inflated offers, paying prices that are far from true values.”

In a way, these results are really obvious: if you add individuals to a market with a larger variety of beliefs, you’ll capture more information.

Global Fishing Patterns


Ursula Le Guin: ‘Wizardry is artistry’

In an astonishing run in the late 1960s and early 70s, Le Guin produced not just Earthsea but several of the great novels of science fiction’s postwar new wave. The Lathe of Heaven, The Dispossessed, The Word for World Is Forest and The Left Hand of Darkness fulfilled the genre’s promise, using speculation to address social, political, ethical and metaphysical questions. Since then she has continued to publish novels and short stories informed by the mystical philosophy of the Tao Te Ching and the west coast tradition of political radicalism, written in a clear, clean prose that is never tainted by inkhorn medievalism or technological jargon. A two-volume collection of stories, The Unreal and the Real, was published this summer, giving an overview of her entire career.

Because of her subject matter, Le Guin isn’t always recognised for what she is, one of the great writers of the American west, a product of a coastal tradition that looks forward at the Pacific with a wilderness at its back and the great cities of Europe very far to the rear.

Le Guin claims to “get very uppity” about the “parochialism and snobbishness” of the East Coast literary establishment. “The idea that everybody lives in a large city in the east, it’s such a strange thing for an American to think.”

The Story That Tore Through the Trees

Outdoorspeople are as varied as any other kind, except that they share one psychological stratum, a layer hard and fine laid down as in geology by the pressure of the Earth. Tim is affable and talkative and has smashed open two of the knuckles on his left hand recently enough to show fresh blood and flecks of white, and not once in an hour does he glance down at them. He was born in Helena, moved away as an adult to Arizona, wondered why, and came back. Now he manages a company that has taken people down this river since 1886, three years before Montana became a state. Some of his clients come to retrace the footsteps of Lewis and Clark, who, on July 19, 1805, “entered much the most remarkable clifts that we have yet seen.” Others come for the remarkable clifts themselves, others to fish the waters beneath them. But some come, as I have, to visit the site of the most famous wildfire in American history.

Just beautiful writing


Round the world

I am currently in Philadelphia on the first leg of a round-the-world tour, so there will continue to be light posting over the next few weeks. I will be in Philadelphia, London, Bangalore/Chennai/etc, and LA.

I had not spent much time in Philadelphia before, though I am now moving here (!). Being from the West Coast, I was somehow unaware that Philadelphia is the second largest city on the East Coast. Philadelphia is the home to the first medical school in the US, at the University of Pennsylvania in 1765. Interestingly, it is also home to an olfactory institute (The Monell Chemical Senses Center).

CSHL cognition meeting (updated with a comparison to a similar meeting in 1990)

cshl cognition

For those that are unaware, CSHL is organizing a ‘supermeeting’ with an obnoxiously great list of invited speakers. Seriously, go check it out. They’ll be discussing cognition apparently, whatever that really means. Anyway, since this is such a list of luminaries, I was curious where they were being invited from. Ladies and gentlemen, the most prosperous universities for neuroscience apparently are:

1. MIT (6)

1. NYU (6)

3. UCSF (5)

4. Harvard (4)

4. CSHL (4)

6. UCSD (3)

6. Columbia University (3)

6. Princeton University (3)

9. Stanford University (2)

9. The Salk Institute (2)

9. University of Geneva (2)

But given that UCSD/Salk are essentially the same institute in terms of neuroscience – every faculty at Salk is associated with UCSD – I’d bump them up to number 3 along with UCSF 😉

Anyway, I’ll leave it to the audience to determine the amount of home cooking, though obviously there is a lesson there either way.

Update: It was suggested that I look at an old list; the last time CSHL had a symposium focused on the brain it was called The Brain (1990). I suppose they’ve gotten more specific with time, but the list itself is pretty interesting. Besides being much larger, it’s WAY more international (there are maybe 2-3 international speakers invited in the 2014 version). There were also more people invited from private industry. Not only were there tons of pharmaceutical companies and Bell Labs, but someone from General Motors came. GM! Anyway, here is the list which I’ve tried to be fair about (ie, Beth Israel+Mass Gen count as Harvard, etc). Once again, Salk + UCSD are affiliated so I’d put them up just behind UCSF at #5.

Update #the second: David Schoppik pointed me to the write-up of the 1990 meeting which is ‘fairly remarkable’.

Old list (1990):

1. Rockefeller University (22)

2. MIT (15)

2. Harvard University (15)

4. UCSF (14)

5. CalTech (11)

5. Columbia University (11)

5. NIH (11)

8. Salk Institute (9)

8. John Hopkins University (9)

10. Washington University (St. Louis) (8)

11. Stanford University (7)

12. Cornell University (6)

12. Max-Planck-Institut (6)

14. Berkeley (4)

14. Yale (4)

14. UCSD (4)

17. University of Oxford (3)

17. New York University (3)

Marine worms, from the cold White Sea to the Great Barrier

Did you know that the segmented worms are among the most common marine organisms? And they’ve got sweet names like “bristleworms”, “sea mice,” and “fire worms.” The wikipedia page has one of the most interesting “internal anatomy and physiology” sections I’ve seen in a while…

So go see a fantastic collection of marine worm photos from Alexander Semenov.

The Alaskan nutrient cycle

My Name Is Legion

Paul Klaver has an absolutely breathtaking short film revealing the nutrient cycle spawned (rimshot) by the salmon in Alaska. It’s gorgeous and I just don’t understand how he managed to get some of the shots. Watch it in fullscreen mode.

I have a fond (?) memory of growing up in Portland, Oregon and heading out to “Outdoor School” for a few days, where they attempted to inculcate a love of the outdoors in us city kids. We visited right after spawning season which meant the stream that ran through the camp was surrounded with decaying salmon carcasses, resulting in the entire place smelling of old fish. Lovely, no?

via Explore

View original post