Showing posts tagged neuroscience

Lee, H., Kim, D., Remedios, R., Anthony, T., Chang, A., Madisen, L., Zeng, H., & Anderson, D. (2014). Scalable control of mounting and attack by Esr1+ neurons in the ventromedial hypothalamus. Nature DOI: 10.1038/nature13169

One of the more terrifying sub-genres of modern neuroscience is the study of animal aggression—specifically, the manipulation of brain circuits that produce unmitigated rage. And it’s no coincidence that David Anderson’s group at Caltech, the ruthless storm trooper horde of the ivory tower, has produced another sick pape that brings us one step closer to the production of ultra-furious super mercenaries.

Humans have been provoking animals for billions of years, but it wasn’t until the pioneering (and brutal) experiments of Phillip Bard in the 1920’s that we realized that animal rage could also be elicited by chopping out specific chunks of the brain. Bard found that surgically removing the cortex of a cat caused it to develop an angry attitude—the kitty would hiss and snarl and attack its previously beloved caretaker/experimenter. This type of behavior was called “sham rage”, because it was not directed at a specifically aggravating stimulus, but presented as a generally foul disposition toward all things great and small.

Using brain lesions in lots of cats, Bard eventually figured out that he could abolish sham rage by disconnecting the hypothalamus and the brainstem, suggesting that the hypothalamus is important for producing aggressive behavior. Walter Hess confirmed this hypothesis a couple decades later, by demonstrating that electrically stimulating the ventromedial hypothalamus is sufficient to produce sham rage. (Walter won the 1949 Nobel Prize for discovering all the crazy things that cats will do when you electrically stimulate the diencephalon.)

this cat's got the sham rage

Now, this recent pape by Hyosang Lee and colleagues has found a (somewhat) specific group of ventromedial hypothalamus neurons that are responsible for triggering unadulterated rage in the mouse. In a Nickelodeon Guts-esque feat of experimental fortitude, the authors searched for neurons that fire during mouse battles by comparing expression of an activity-dependent transcription reporter (c-Fos) to various cell-type specific markers. This led to the discovery of a population of aggression-associated hypothalamus neurons that express the estrogen-receptor (Esr1). Building a Cre knock-in mouse allowed them to virally transfect EsR1+ neurons in the hypothalamus with light-gated ion channels (ChR2 and Halo). They could then manipulate the activity of Esr1 neurons by shining light on the hypothalamus through an implanted fiber optic.

Surprisingly, the Anderson gang found that optogenetically stimulating these neurons in male mice provoked either carnal advances or attack, depending on the intensity of stimulation. At low intensities, male mice would mount other mice (of either sex), while at higher intensities, they would repeatedly sucker-punch their bewildered cage-mates. They also found that optogenetically silencing these same neurons during normal anger sessions terminated the altercation.

Together, the oppressively thorough experiments in this pape show that EsR1 neurons play a critical role in generating behaviors of passion. Of course, we still have no idea how a single population of neurons in the hypothalamus produces such complicated behavioral sequences—it is likely that they provide a gating signal to the exceedingly complex circuits in the brainstem that produce sequences of motor behavior. Working out this hierarchy is going to be a devilish task.

Let’s conclude with some deep thinking. Although most of us have come to accept the fact that our behavior is completely controlled by a goo-bag of neurons behind our eyes, there is still something implausible about the idea that driving activity in an obscure brain circuit can provoke violence. Watching these videos, you can’t help but consider how you would respond to this same manipulation—is there any amount of “self-control” that could overcome the impulse to attack? And would you feel shame or guilt while being artificially compelled to assault an innocent stranger? These are questions that will need to be answered before we can successfully engineer the hyper-wrathful super-soldiers (post-docs) that our military (the Anderson Lab) needs and deserves.

Contributed by butthill

Limits to sustained energy intake. XVIII. Energy intake and reproductive output during lactation in Swiss mice raising small litters. 
Zhao ZJ, Song DG, Su ZC, Wei WB, Liu XB, & Speakman JR (2013).
The Journal of experimental biology, 216 (Pt 12), 2349-58 PMID: 23720804

Although binging is often attributed to weak human character, a substantial binge can also help a man get in touch with his/her reckless animal roots. Whether it involves a steaming heap of elk intestines or 3 seasons of Arrested Development, there are some treats that evolution has wired animals to consume beyond the point of reasonable satiety. Giving in to these deep urges is one of the many so-called flaws that the Catholic Church utterly failed to eradicate from our animal constitution.

A recent binge was triggered by the current issue of The Journal of Experimental Biology, which contained no less than IV sick papes about mouse lactation from Dr. John Speakman and colleagues.  Further research revealed that, over the past decade, Speakman’s lab has published XVIII papers on this subject, each possessing the formulaic title: Limits to sustained energy intake., etc. This linear corpus of papes is ideally suited to sautéing an entire day in thick fatty mouse milk.

Each of these papes poses the same basic question: which factors determine an animal’s physiological limits? Speakman and colleagues study this question in lactating mice, who expend a massive amount of energy to produce milk for their thirsty pups. Two initial proposals were that milk production is limited by (I) the ability of the gut to digest food or (II) the efficiency of the mammary gland itself.

Through the first X papes in the series, Speakman and his jolly giants tested these hypotheses, as well as a couple other clever theories they dreamed up. My favorite among this back-catalogue is the evocatively titled: Limits to sustained energy intake. X. Effects of fur removal on reproductive performance in laboratory mice.

In this pape, the authors test the hypothesis that energy intake is limited by the capacity of an animal to dissipate heat. They increased the ability of lactating female mice to dissipate heat by shaving them bald as porpoises. Shaved mice ate more heartily and produced more milk, which in turn increased the size of their adorable mouse children. This result contradicted the long-held views that nursing performance is limited by the efficiency of the mother mouse’s digestion and subsequent milk production.

Although these initial results suggested that there might be one or a couple limitations to energy expenditure, the most recent papes (XIV - XVIII) show that the story is actually much more complicated. Under different environmental conditions, lactation efficiency and offspring growth are limited by several overlapping factors. There are also important differences across mouse strains. Despite the lack of simplicity in the underlying biology, the narrative organization of these XVIII papes that ask the same, seemingly basic, question, demonstrate an experimental doggedness that you got to respect.

Contributed by butthill

SICK PAPES SPECIAL ON CONTROVERSY: PART 2

Curr Biol. 2010 Sep 14;20(17):1534-8.
The role of the magnetite-based receptors in the beak in pigeon homing.
Wiltschko R, Schiffner I, Fuhrmann P, Wiltschko W.

VERSUS

Nature. 2009 Oct 29;461(7268):1274-7.
Visual but not trigeminal mediation of magnetic compass information in a migratory bird.
Zapka M, Heyers D, Hein CM, Engels S, Schneider NL, Hans J, Weiler S, Dreyer D, Kishkinev D, Wild JM, Mouritsen H.

AND

Nature. 2012 Apr 11;484(7394):367-70.
Clusters of iron-rich cells in the upper beak of pigeons are macrophages not magnetosensitive neurons.
Treiber CD, Salzer MC, Riegler J, Edelman N, Sugar C, Breuss M, Pichler P, Cadiou H, Saunders M, Lythgoe M, Shaw J, Keays DA.

There are some scientific subjects that attract recreational bedlamites like seagulls to a coastal landfill. My favorite of these is magnetoreception: the ability of an animal to perceive an ambient magnetic field. Lots of animals can do this—birds, insects, reptiles— and some of them use the earth’s weak magnetic asymmetry to achieve extraordinary feats of navigation. For example, scientific hero Ken Lohmann has shown that sea turtles navigate thousands of miles through the horrific salty ocean in order to meet their half-shelled-brethren at a specific location for an annual Bacchanalian picnic. Ken’s lab also found that if you move a spiny lobster 20 miles in any direction from its preferred hangout spot, it immediately returns directly to its headquarters using cues from the earth’s magnetic field. These and bajillions of other examples demonstrate that many of the earth’s macro-biotic inhabitants can use a magnetic sense to cruise around in magnificent style, which, in my humble opinion, is absolutely fucking fantastic.

Returning to the bedlamites. There are two dudes in particular that illustrate the fact that magnets exert a certain ineffable force upon the zanier castes of our super-organismic civilization. The first of these is shown in the video above: Mr. Harry Magnet, whose extensive pape on personal perception of magnetic fields cannot be deemed sick or otherwise, because it has not undergone rigorous peer review (but we welcome submissions).

The second example comes from Alane Jackson, the purveyor of a theory called magnetrition, which was first explained to me by a youth soccer referee who lived in a wigwam on an magnetically neutral island in the middle of an Alaskan lake. Basically, Alane’s idea is that mitochondria are magnetically charged, and that jostling our cells around causes cytoplasmic stirring, thereby promoting health. I also recommend another section of Alane’s website, titled Smoking is good.

Buried beneath all of this absolutely essential HTML is an equally intense scientific debate about the mechanisms by which real animals measure magnetic fields. So far, two basic mechanisms have been proposed:

(1) MAGNETITE. The magnetite hypothesis was inspired by the observation that some magnet-loving bacteria produce magnetite (Fe3O4) crystals that cause them to align with and cruise along the local magnetic vibe. Because magnetite has also been found in the snouts/beaks of fish and birds, it was suggested that the rotation of these crystals could be detected by mechanosensory neurons in the brain. Smaller, “superparamagnetic crystals” have also been found in bird beaks. These crystals do not have a permanent magnetic moment, and therefore do not individually rotate to align with the earth’s magnetic field. However, large arrays of these superparamagnetic crystals would attract and repulse each other under different magnetic field conditions, generating forces that could, in principle, be sensed by neurons.

(2) CRYPTOCHROME. This second mechanism is even bonkers-er. Some radical-pair chemical reactions can be influenced by magnetic forces—one example is the absorption of light by retinal photopigments called cryptochromes. The idea is that the ambient magnetic field would alter the rate of cryptochrome photo-isomerization, so that if a bird were gazing upward at a clear blue sky, it could actually “see” a hazy magnetic field image layered on top of the normal visual scene.

The argument surrounding these two mechanisms is best exemplified in the bird magnetoreception literature, which has been enriched in recent years by a flurry of combative pape-slinging. In one camp, (1) the Wiltschkos and their pals claim that birds use little magnetite particles in their beaks to detect magnetic fields, while in another camp (2) Henrik Mouritsen and his pals  claim that magnetoreception arises in the retina, mostly likely through cyptochrome. (3) David Anthony Keays and his buds weighed in on side 2 of the fracas last year, when they suggested that those magnetite particles in the beak are located inside little pieces of biological irrelevance called macrophages.

Although the field of magnetoreception is confusing and controversial, one cannot help but delight in the titillation-level of the questions and the unfettered academic shit-hurling. Magnetoreception is clearly the modern El Dorado, attracting both well-funded academics and itinerant kooks. There is the important possibility that everybody is right— that birds have two independent magnetic senses and so do people, and the booty will be split evenly amongst the Professors and the online gurus. It seems much more likely to me, however, that this entire field is booby-trapped, and that all the magnet-lovers will end up stalking monkeys on a raft as the river below their feet slowly transforms into a cauldron of boiling soup.

Contributed by butthill

Blackiston DJ, & Levin M (2013). Ectopic eyes outside the head in Xenopus tadpoles provide sensory data for light-mediated learning. The Journal of experimental biology, 216 (Pt 6), 1031-40 PMID: 23447666

Our pals in the Department of Futuristic Neuroscience have recently attracted a lot of attention for a whacky pape that demonstrated that one rat could (sort of) learn to detect signals recorded from another rat’s brain. The main finding of this study, that animals connected by electrodes tend not to ignore each other, is fuzzily heartwarming, but ranks close to Feline papillomavirus on the grand scale of illness.

A much more compelling example of the brain’s dynamic ballsiness (i.e., the ability of neural circuits to learn to detect unfamiliar sensory stimuli), is described in a recent exercise in sickness by the duo of Blackiston and Levin. These pre-pubescent-frog-loving maniacs surgically removed the eyeballs of a couple hundred tadpoles, and then transplanted donor eyeballs onto different regions of the tadpole body (fanny, haunch, etc). The donor eyeballs were labeled with a fluorescent protein (RFP), so they could monitor the axons of the transplanted optic nerve. Most of the resettled eyeballs did not successfully innervate the central nervous system, but about ¼ of them managed to connect to the gut, and another ¼ innervated the spinal cord.

Blackiston and Levin then tested the population of chimeric tadpole beasts with an associative learning task that required the tadpoles to detect light in order to avoid an electric shock. A small number of the 200 freak tadpoles could learn to avoid red light, despite the fact that they did not have normal eyes. All of the successful learners had transplanted eyeballs that innervated the spinal cord.

It’s already incredible that transplanted eyeballs can successfully wire up to the spinal cord; the fact that tadpoles can then use the whimsical retina/spinal cord circuit in a behavioral task seems, at first glance, to defy the 14th amendment of biology. But we’ve known for a long time that the nervous system is able to adapt to novel inputs. For example, the visual cortex of blind people can be colonized by auditory and somatosensory inputs, allowing them to fluently read using touch (Braille) and echolocate like bats (??).

The interesting question is not whether animals can learn to detect exogenous signals (e.g., spikes transmitted from a Brazilian rat’s brain), but how the hell the nervous system pulls out such meaningful signals of hope against the noisy background of torrential chaos and despair. This is some boring biology shit. In the meantime let’s get psyched about building an exoskeleton for the World Cup and teaching Big-Dog to throw cinder blocks.

Contributed by butthill

image

Eliasmith, C., Stewart, T., Choo, X., Bekolay, T., DeWolf, T., Tang, Y., & Rasmussen, D. (2012). A Large-Scale Model of the Functioning Brain Science, 338 (6111), 1202-1205 DOI: 10.1126/science.1225266

The H. P. Lovecraft novella At the Mountains of Madness is a story about scientific hubris, and the insignificance of human achievement when confronted with the vastness that is the cosmos. The central characters are scientists searching the Antarctic for novel geological or biological forms. They uncover a world of strange, ancient beings, seemingly preserved in the ice. Their discovery has profound implications for the nature of biological evolution, and perhaps the history — and future — of earth itself. The primary entity they find is a god-like tentacled, winged, gilled monstrosity with strange geometrical features. We are given this account:

“It had digestion and circulation, and eliminated waste matter through the reddish tubes of its starfish-shaped base … The nervous system was so complex and highly developed as to leave [the scientist] aghast. Though excessively primitive and archaic in some responses, the thing had a set of ganglial centers and connectives arguing the very extremes of specialized development. Its five-lobed brain was surprisingly advance and there were signs of a sensory equipment, served in part through the wiry cilia of the head, involving facts alien to any other terrestrial organism … It was partly vegetable, but had three-fourths of the essentials of animal structure.”

I had a similar reaction when reading about S.P.A.U.N., the monstrous creation described by Eliasmith et al. in their pape: “A large-scale model of the functioning brain”. The title alone suggests a new and scary precipice of human achievement. And a most sick pape. 

S.P.A.U.N. is half way between a robot and a computer program. It has a small camera attached to its head, and a robotic appendage extending from an implied torso that is capable of drawing all manner of digits between 0 and 9. Its brain has multiple sub-systems that independently control the encoding of visual input, reward, working memory, decoding, and motor output. The thrust of Eliasmith et al.’s pape is not that any one component of S.P.A.U.N. is new, but that it can perform not just one task but a variety of tasks, all of which humans can perform, and that its modular architecture resembles and realistically models at least some aspects of the human brain. 

How close does S.P.A.U.N. come to resembling the brain? Each of its systems are meant to correspond to cortical and sub-cortical brain areas or functions, though much of the correspondence seems superficial. For example, S.P.A.U.N. has a system for handling “Visual Input”. It’s implied that it corresponds to areas V1, V2, V4, and IT of the primate visual pathway. But S.P.A.U.N. cannot mimic known processing in all those areas because we still don’t know what they do! The visual system of S.P.A.U.N. also reveals that its individual neurons are not as realistic as you might think. The authors stress that it uses biologically-realistic neurons with neurotransmitter dynamics, but most of the visual system instead uses simple linear combinations and thresholding. It’s hard to evaluate these shortcuts because the system is so complex.

So S.P.A.U.N. can do some cool tricks and kind of maybe looks like a brain. Can it fight a bear in one-on-one combat? Definitely not. S.P.A.U.N.‘s proponents admit that it is not the most impressive robot. When I googled “what is the sweetest robot?” I found this strawberry-picking robot. It uses 3D image processing to evaluate ripeness, and can delicately pluck luscious plump strawberries from their stems. That seems more impressive than S.P.A.U.N.

Becoming the best robot is not S.P.A.U.N.’s goal. What is the goal? Building AI systems that perform complex, physical, interactive tasks with flexible, modular systems resembling known biology, that could in principle help us understand how brains work. A longstanding, and recently popularized but criticized, tradition in AI is to build systems that have vast representational power, memory, and fancy statistical learning algorithms, but generally produce simple outputs. For example, a computer vision system that encodes a complex image but only needs to decide which of 10 different kinds of objects it is looking at. But most animals evolved to do more than spit out a 10-bit vector. They engage in real-time with a dynamically changing world. S.P.A.U.N.’s complex motor output and working memory is a step forward, but its emphasis on symbolic reasoning — which number comes next in a sequence? — is excessively abstract. If such symbolic reasoning evolved as an abstraction of more directly-physically-realized functions — when can I jump to make sure I catch the next mouse? — why not first try to build robots that can accomplish those tasks? I recommend the exciting research program of the “embodied robotocist” Rodney Brooks, especially his efforts in the 1990s to build robots with distributed control systems for path finding and navigation. He also appears, looking entirely crazed, in this movie, which features robots, lion taming, tree grooming, and naked mole rats. We are truly standing beneath the Mountains of Madness.

Contributed by istudyvision

Krieger J, Grandy R, Drew MM, Erland S, Stensmyr MC, Harzsch S, & Hansson BS (2012). Giant Robber Crabs Monitored from Space: GPS-Based Telemetric Studies on Christmas Island (Indian Ocean). PloS one, 7 (11) PMID: 23166774

Anybody who knows me will tell you that I have a soft spot in my heart for the hard shell of our fellow crab-man. For all the land-lubbers out there, the crab is a heavily-armored, sideways-running little fellow that specializes in shoveling detritus (= trash) into its adorable little mouth with an often over-sized claw appendage. To me, the main appeal of the crab is its dignified air of feistiness. Unlike most softy animals, crabs do not like to be handled, and if you pick them up they will pinch you with all the hatred they can muster. Crabs also have beautiful brains and, as we shall see, possess a unique brand of crusty intelligence.

There are all sorts of freaky crabs out there, but the most inspiring is the absurdly proportioned giant robber crab that resides on Christmas Island in the South Pacific. These friggin crabs can weigh about 10 lbs, they climb trees, and they rip apart coconuts and devour them like their mike’s and ike’s (sic). This cushy crab lifestyle allows them to live to the ripe age of 60. Some folks in the recently prolific Hansson Lab at the Max Planck Institute for Chemical Ecology somehow convinced somebody to let them go to Christmas Island and study the navigational abilities of giant robber crabs. Their experimental protocol went as follows:

  1. Snatch a robber crab
  2. Glue a GPS tracking device to its carapace
  3. Sit back and watch where it goes via satellite transmission
  4. Snatch the crab again, put in a trash bag, transport it across the island, and release it
  5. See if the crab can get back home

This pape clearly demonstrates that robber crabs live a rambling lifestyle. After spending a few days or weeks in one area, a crab will get the itch to roam, and will pick up and haul his barnacled ass from the inland rainforest to the seashore. After a spell at the shore, he’ll pack up and hitch back into the rainforest. Over time, robber crabs learn preferred routes that they repeatedly traverse throughout their long lives. Most remarkably, if you put a crab in a trash bag and haul it a mile away, it will almost immediately return to the spot where you snatched it.

Aside from the obvious conclusion that robber crabs are dynamic, intelligent beasts, this pape also establishes the robber crab as an important model system for studying what it means to live a deeply fulfilling life. 

Contributed by butthill
Druckmann, S., & Chklovskii, D. (2012). Neuronal Circuits Underlying Persistent Representations Despite Time Varying Activity. Current Biology, 22 (22), 2095-2103 DOI: 10.1016/j.cub.2012.08.058
To celebrate the dawn of December, a month of intense introspection and widespread brooding, Sick Papes brings you an exclusive soul-wrenching interview with neuroscientist and celebrity theoretician, Dr. Shaul Druckmann. Shaul’s recent pape (w/ Mitya Chklovskii) suggests a fresh answer to a beguiling question- how does the brain maintain persistent representations despite the fact that neuronal activity is constantly changing?
Personal experience tells us that the brain can maintain stable representations of images, numbers, and ideas for seconds and minutes. However, the activity of neurons in brain regions thought to be involved in working memory, such as prefrontal cortex, varies on a much faster time scale, (~10-50 milliseconds). Shaul’s pape proposes a network model, called FEVER, which can maintain persistent representations even as the activity of individual neurons varies. It turns out that this network model has many features in common with the organization of real cortical networks.
SP: If I’ve got my mules in order, your model network is constructed such that the receptive field of each neuron is equivalent to a weighted sum of the receptive fields of all other neurons in the network, and the weights in this weighted sum are the strength of synaptic connections between neurons. This allows the activity of individual neurons to vary, while the output of the network remains constant. This structure seems precarious. If I were to go into your brain and cut one single synaptic connection, how would this affect stable representations in a dense FEVER network? In other words, how robust is this network to wanton destruction?
 SD: Yup, your mules are definitely in order and marching. As you say, destroying synaptic connections will momentarily throw the network off balance. However, since the representation is highly overlapping and there are many ways to represent each stimulus there would be no problem readjusting the network so as to ignore the destroyed part of the network. Given the high degree of overcompleteness that we suspect exists in cortex, there is a lot of room to recover from damage.
SP: In his Tractatus, Wittgenstein proposes that, “A logical picture of facts is a thought”; in other words, that thoughts must adhere to the same logical form as things in the real world. Agree or disagree?
SD: Wittgenstein huh? I am not sure I can even properly pronounce his name, much less understand his writings. The end of my serious reading of philosophical literature timeline is more or less with Kant… Regardless, I am not sure I read the sentence the same way you do. “A logical picture of facts is a thought”. First, I like the stress on the term “picture of facts” which for me relates the thought to the many aspects of taking a picture: we select what to put in our frame and what to keep out, the lighting we throw on the objects matters a lot as well as the angle and ultimately it needs to be developed to become a real thing (okay maybe the last one was a stretch). Regarding what thoughts must adhere to, I am not sure thoughts are under control, so lets read “thoughts” as “theories”. I strongly believe that theories must first and foremost have a sound logical structure. In one interpretation that is pretty straightforward since it just means that the math needs to check out. However, I believe that, somewhat related to that sentence, one of the most interesting things about theories is that they rearrange facts that we thought we previously knew into a new order. If that new order makes more “sense” and teaches you (the experts) new things about the facts then the theory is actually valuable. Anyhow, this sounds like something better talked about over a beer…
SP: Your pape addresses how a brain might hold onto specific representations for periods of seconds, even as the activity of individual neurons varies wildly during this period. A slightly different problem is how human thought and perception seems to occur on the time-scale of seconds, despite the fact that neural activity varies on the order of milliseconds. Do you think this is simply a matter of perception, or do evolving network dynamics across longer time scales matter?
SD: Actually our first draft discussed that briefly, but reviewers hated it since it was too speculative. I think there are two possibilities, one is that representation is constantly changing, but there is a little leprechaun working really hard in our brain all the time to make sure our conscious perception is smooth (this may sounds crazy, but think change-detection blindness). The other is that the networks themselves bridge the gap between the time scale of neural activity (milliseconds) and the time scale of the world (seconds say) by mechanisms such as the one we describe in order to allow downstream circuits a smooth readout of the representation and the leprechaun to have a much more relaxed life. Which is true? I really don’t know.
SP: When you are building a model, do you start with the acronym first and work backward? Or do you build the model first and then tweak it until it fits with a catchy acronym?
SD: Given the allowed artistic freedom of basically picking any random word and letter within it for an acronym it is pretty easy to find one once the work is done. But what you suggests sounds fun, randomly thinking up an acronym, finding the most reasonable sentence you can attach to it and seeing whether that inspires and idea worth working through.
SP: Do you think the phrase “persistent representation” accurately describes what is happening in the brain during working memory? For example, remembering a phone number requires a certain amount of active rehearsal, and is susceptible to distraction. Why must prefrontal cortex maintain a representation within itself, rather than relying on repeated structured inputs from other sensory networks?
SD: In the delayed-match-to-sample working memory task design as much as possible is done to eliminate the possibility of input driven memory (turning stimulus on only transiently, long delay periods). Therefore, that is less of an option in my opinion. More generally though, if it is an input driven memory then one has to answer the question how does whatever circuit that provides the input keep its ability to provide an input for such a long time despite the transient stimulus. Then all our explanations would need to be shifted to that area. I don’t think it has been worked out in an airtight manner that this isn’t a possibility, but I think it is less likely.
SP: In Borges’ story, ”Funes the Memorious”, a young boy falls off a horse and loses his ability to forget. His life is haunted by the banal details of every moment he has ever experienced, including all the associated physical and emotional sensations. Are there certain conditions under which a FEVER network architecture could result in such a condition?
SD: Good point! In fact the way we develop the math in the first section leads to a network with an infinite integration, which is exactly Borges’ idea, sans the horse. That’s why we later add the scaling factor to the equation that allows you to have a very long, but not infinite, time constant. Otherwise, with an infinite time constant one would run into  all kinds of problems such as saturation due to the integration of all the (banal) past stimuli ever encountered.
SP: One method to test the relevance of the FEVER network is to compare the synaptic structure of a cortical network to the range of eigenvalues predicted by the model. Are there any unexpected features of the eigenspectrum that you could look for in real cortical networks? You mention a few in the paper that support your model (e.g., prevalence of reciprocal connections), but are there others that would be worth looking for?
SD: In terms of synaptic reconstruction, I think the neat thing to do is to try to map the receptive field of neurons and then do EM reconstruction a la Denk. Then one option is trace down the axon of a single cell, find all the post-synaptic cells, sum up their receptive fields and see if you come up with the original neuron’s own receptive field (I guess you could do it with trans-synaptic viruses in principle too). The tricky part is that you need to know the weight of the connection, which might not be easy/possible from EM (actually everything about that idea is tricky). More generally, I think the most interesting concept to look for is the idea of coding vs. non-coding directions in activity space which our theory suggests. Not all activity patterns were created equal! I believe this has serious implications for how to interpret multi-neuron population recordings and that is something I want to take a closer look at.
SP: What is the sickest pape you have read in the last 2 months?
SD: Sickest pape: ice in Mercury’s north pole. Ice was apparently delivered by comets or asteroids! Surface temperatures of 400 celsius (not in the shade) but alien (to mercury) ice in the deep shade still survived. How cool is that?

Druckmann, S., & Chklovskii, D. (2012). Neuronal Circuits Underlying Persistent Representations Despite Time Varying Activity. Current Biology, 22 (22), 2095-2103 DOI: 10.1016/j.cub.2012.08.058

To celebrate the dawn of December, a month of intense introspection and widespread brooding, Sick Papes brings you an exclusive soul-wrenching interview with neuroscientist and celebrity theoretician, Dr. Shaul Druckmann. Shaul’s recent pape (w/ Mitya Chklovskii) suggests a fresh answer to a beguiling question- how does the brain maintain persistent representations despite the fact that neuronal activity is constantly changing?

Personal experience tells us that the brain can maintain stable representations of images, numbers, and ideas for seconds and minutes. However, the activity of neurons in brain regions thought to be involved in working memory, such as prefrontal cortex, varies on a much faster time scale, (~10-50 milliseconds). Shaul’s pape proposes a network model, called FEVER, which can maintain persistent representations even as the activity of individual neurons varies. It turns out that this network model has many features in common with the organization of real cortical networks.

SP: If I’ve got my mules in order, your model network is constructed such that the receptive field of each neuron is equivalent to a weighted sum of the receptive fields of all other neurons in the network, and the weights in this weighted sum are the strength of synaptic connections between neurons. This allows the activity of individual neurons to vary, while the output of the network remains constant. This structure seems precarious. If I were to go into your brain and cut one single synaptic connection, how would this affect stable representations in a dense FEVER network? In other words, how robust is this network to wanton destruction?

SD: Yup, your mules are definitely in order and marching. As you say, destroying synaptic connections will momentarily throw the network off balance. However, since the representation is highly overlapping and there are many ways to represent each stimulus there would be no problem readjusting the network so as to ignore the destroyed part of the network. Given the high degree of overcompleteness that we suspect exists in cortex, there is a lot of room to recover from damage.

SP: In his Tractatus, Wittgenstein proposes that, “A logical picture of facts is a thought”; in other words, that thoughts must adhere to the same logical form as things in the real world. Agree or disagree?

SD: Wittgenstein huh? I am not sure I can even properly pronounce his name, much less understand his writings. The end of my serious reading of philosophical literature timeline is more or less with Kant… Regardless, I am not sure I read the sentence the same way you do. “A logical picture of facts is a thought”. First, I like the stress on the term “picture of facts” which for me relates the thought to the many aspects of taking a picture: we select what to put in our frame and what to keep out, the lighting we throw on the objects matters a lot as well as the angle and ultimately it needs to be developed to become a real thing (okay maybe the last one was a stretch). Regarding what thoughts must adhere to, I am not sure thoughts are under control, so lets read “thoughts” as “theories”. I strongly believe that theories must first and foremost have a sound logical structure. In one interpretation that is pretty straightforward since it just means that the math needs to check out. However, I believe that, somewhat related to that sentence, one of the most interesting things about theories is that they rearrange facts that we thought we previously knew into a new order. If that new order makes more “sense” and teaches you (the experts) new things about the facts then the theory is actually valuable. Anyhow, this sounds like something better talked about over a beer…

SP: Your pape addresses how a brain might hold onto specific representations for periods of seconds, even as the activity of individual neurons varies wildly during this period. A slightly different problem is how human thought and perception seems to occur on the time-scale of seconds, despite the fact that neural activity varies on the order of milliseconds. Do you think this is simply a matter of perception, or do evolving network dynamics across longer time scales matter?

SD: Actually our first draft discussed that briefly, but reviewers hated it since it was too speculative. I think there are two possibilities, one is that representation is constantly changing, but there is a little leprechaun working really hard in our brain all the time to make sure our conscious perception is smooth (this may sounds crazy, but think change-detection blindness). The other is that the networks themselves bridge the gap between the time scale of neural activity (milliseconds) and the time scale of the world (seconds say) by mechanisms such as the one we describe in order to allow downstream circuits a smooth readout of the representation and the leprechaun to have a much more relaxed life. Which is true? I really don’t know.

SP: When you are building a model, do you start with the acronym first and work backward? Or do you build the model first and then tweak it until it fits with a catchy acronym?

SD: Given the allowed artistic freedom of basically picking any random word and letter within it for an acronym it is pretty easy to find one once the work is done. But what you suggests sounds fun, randomly thinking up an acronym, finding the most reasonable sentence you can attach to it and seeing whether that inspires and idea worth working through.

SP: Do you think the phrase “persistent representation” accurately describes what is happening in the brain during working memory? For example, remembering a phone number requires a certain amount of active rehearsal, and is susceptible to distraction. Why must prefrontal cortex maintain a representation within itself, rather than relying on repeated structured inputs from other sensory networks?

SD: In the delayed-match-to-sample working memory task design as much as possible is done to eliminate the possibility of input driven memory (turning stimulus on only transiently, long delay periods). Therefore, that is less of an option in my opinion. More generally though, if it is an input driven memory then one has to answer the question how does whatever circuit that provides the input keep its ability to provide an input for such a long time despite the transient stimulus. Then all our explanations would need to be shifted to that area. I don’t think it has been worked out in an airtight manner that this isn’t a possibility, but I think it is less likely.

SP: In Borges’ story, ”Funes the Memorious”, a young boy falls off a horse and loses his ability to forget. His life is haunted by the banal details of every moment he has ever experienced, including all the associated physical and emotional sensations. Are there certain conditions under which a FEVER network architecture could result in such a condition?

SD: Good point! In fact the way we develop the math in the first section leads to a network with an infinite integration, which is exactly Borges’ idea, sans the horse. That’s why we later add the scaling factor to the equation that allows you to have a very long, but not infinite, time constant. Otherwise, with an infinite time constant one would run into  all kinds of problems such as saturation due to the integration of all the (banal) past stimuli ever encountered.

SP: One method to test the relevance of the FEVER network is to compare the synaptic structure of a cortical network to the range of eigenvalues predicted by the model. Are there any unexpected features of the eigenspectrum that you could look for in real cortical networks? You mention a few in the paper that support your model (e.g., prevalence of reciprocal connections), but are there others that would be worth looking for?

SD: In terms of synaptic reconstruction, I think the neat thing to do is to try to map the receptive field of neurons and then do EM reconstruction a la Denk. Then one option is trace down the axon of a single cell, find all the post-synaptic cells, sum up their receptive fields and see if you come up with the original neuron’s own receptive field (I guess you could do it with trans-synaptic viruses in principle too). The tricky part is that you need to know the weight of the connection, which might not be easy/possible from EM (actually everything about that idea is tricky). More generally, I think the most interesting concept to look for is the idea of coding vs. non-coding directions in activity space which our theory suggests. Not all activity patterns were created equal! I believe this has serious implications for how to interpret multi-neuron population recordings and that is something I want to take a closer look at.

SP: What is the sickest pape you have read in the last 2 months?

SD: Sickest pape: ice in Mercury’s north pole. Ice was apparently delivered by comets or asteroids! Surface temperatures of 400 celsius (not in the shade) but alien (to mercury) ice in the deep shade still survived. How cool is that?

Contributed by butthill
Mainen, Z., & Sejnowski, T. (1995). Reliability of spike timing in neocortical neurons Science, 268 (5216), 1503-1506 DOI: 10.1126/science.7770778
It is with great ambivalence that we recently learned that Hostess Bakeries, the corporation that coated generations of sniveling youngsters with a thin sticky film of fructose, has permanently extinguished its great roaring Twinkie ovens. Since the Great Depression, the specter of Hostess has haunted the American childhood, transforming many precocious naturalists-to-be into taffy-gargling, scrap-booking diabetic uncles. My own personal savior from the purgatory of Ding-Dong-dom was the health-food alternative 4” Table Talk Pie, which came (and continues to come) packed with one of 63 delicious fillings, including (if my memory serves) such classics as apple crumb, pumpkin marshmallow, and raspberry bourbon.
There are striking parallels between the spheres of snack foods and papes . The artisanal cheeses and home-butchered pig jowls are the niche journals, often packed with abstruse but thorough minutiae: satisfying to the connoisseur but unappealing to the masses. At the other end of the spectrum are the sticky pre-packaged pastries, high profile journals that publish short format papers designed to maximize caloric efficiency. Wrapped in sexy packaging and found in gas stations worldwide, these tempting morsels promise redemption, but often leave the consumer with a raw, yawning hunger. As in the world of gas station snacking, it is rare to find a short format paper that delivers true satisfaction.
A pape that I consider a gas station staple is “Reliability of Spike Timing in Neocortical Neurons”, by Zach Mainen and Terry Sejnowski. Published in Science in 1995, this pape uses a series of straightforward electrophysiology experiments to make the argument that the timing of action potential firing can be precise and reliable, under the right conditions.
Previous experiments (and many since) have found that the temporal precision of neuronal spikes is variable. For example, if you record from a neuron in visual cortex and repeatedly present the same visual stimulus, the number and timing of action potentials fired on each trial is highly irregular. This fact disturbed neuroscientists who were trying to understand how the brain builds a reliable representation of the world, and it led to some nifty ideas about what it really means for neurons to “encode information”. 
Taking a different approach, Mainen and Sejnowski asked what happens if you provide a neuron with a more naturalistic input than a boring square-wave stimulus. Recording from cortical neurons in brain slices, they injected current pulses that mimicked typical synaptic inputs. They found that these noisy stimuli produced highly reliable firing patterns, with a precision of ~1 ms, while square current pulses resulted in more variable spiking responses. This result suggests that the variability of spiking activity arises from noise in the synaptic input, rather than noisiness of the neuron itself. Although this does not fully explain why neural responses in vivo are often variable (there are many other reasons for this), it demonstrates that neurons in the cortex at least have the ability to encode information with high temporal fidelity. Reliability of spike-timing would, in principal, allow the brain to synchronize action potentials across neurons through network oscillations, and do lots of other interesting shit.
The reason that this humdinger works well as a Science pape is that it presents a single digestible idea that can be conveyed in a glossy 3 figure package. Unfortunately, most present-day short-format papes take the less elegant route of cramming five years worth of experiments into 1500 carefully chosen words. This is not the fault of the authors— for some reason, the two top journals insist that the papes they publish adhere to strict length requirements. Although some Nature and Science papes can be molded into delicious Table Talk delicacies, many others that would work well as Thanksgiving feasts end up tasting like friggn Ding-Dongs.

Mainen, Z., & Sejnowski, T. (1995). Reliability of spike timing in neocortical neurons Science, 268 (5216), 1503-1506 DOI: 10.1126/science.7770778

It is with great ambivalence that we recently learned that Hostess Bakeries, the corporation that coated generations of sniveling youngsters with a thin sticky film of fructose, has permanently extinguished its great roaring Twinkie ovens. Since the Great Depression, the specter of Hostess has haunted the American childhood, transforming many precocious naturalists-to-be into taffy-gargling, scrap-booking diabetic uncles. My own personal savior from the purgatory of Ding-Dong-dom was the health-food alternative 4” Table Talk Pie, which came (and continues to come) packed with one of 63 delicious fillings, including (if my memory serves) such classics as apple crumb, pumpkin marshmallow, and raspberry bourbon.

There are striking parallels between the spheres of snack foods and papes . The artisanal cheeses and home-butchered pig jowls are the niche journals, often packed with abstruse but thorough minutiae: satisfying to the connoisseur but unappealing to the masses. At the other end of the spectrum are the sticky pre-packaged pastries, high profile journals that publish short format papers designed to maximize caloric efficiency. Wrapped in sexy packaging and found in gas stations worldwide, these tempting morsels promise redemption, but often leave the consumer with a raw, yawning hunger. As in the world of gas station snacking, it is rare to find a short format paper that delivers true satisfaction.

A pape that I consider a gas station staple is “Reliability of Spike Timing in Neocortical Neurons”, by Zach Mainen and Terry Sejnowski. Published in Science in 1995, this pape uses a series of straightforward electrophysiology experiments to make the argument that the timing of action potential firing can be precise and reliable, under the right conditions.

Previous experiments (and many since) have found that the temporal precision of neuronal spikes is variable. For example, if you record from a neuron in visual cortex and repeatedly present the same visual stimulus, the number and timing of action potentials fired on each trial is highly irregular. This fact disturbed neuroscientists who were trying to understand how the brain builds a reliable representation of the world, and it led to some nifty ideas about what it really means for neurons to “encode information”.

Taking a different approach, Mainen and Sejnowski asked what happens if you provide a neuron with a more naturalistic input than a boring square-wave stimulus. Recording from cortical neurons in brain slices, they injected current pulses that mimicked typical synaptic inputs. They found that these noisy stimuli produced highly reliable firing patterns, with a precision of ~1 ms, while square current pulses resulted in more variable spiking responses. This result suggests that the variability of spiking activity arises from noise in the synaptic input, rather than noisiness of the neuron itself. Although this does not fully explain why neural responses in vivo are often variable (there are many other reasons for this), it demonstrates that neurons in the cortex at least have the ability to encode information with high temporal fidelity. Reliability of spike-timing would, in principal, allow the brain to synchronize action potentials across neurons through network oscillations, and do lots of other interesting shit.

The reason that this humdinger works well as a Science pape is that it presents a single digestible idea that can be conveyed in a glossy 3 figure package. Unfortunately, most present-day short-format papes take the less elegant route of cramming five years worth of experiments into 1500 carefully chosen words. This is not the fault of the authors— for some reason, the two top journals insist that the papes they publish adhere to strict length requirements. Although some Nature and Science papes can be molded into delicious Table Talk delicacies, many others that would work well as Thanksgiving feasts end up tasting like friggn Ding-Dongs.

Contributed by butthill

Sick Papes Special on Central Pattern Generators, Part 2

Finan DS, & Barlow SM (1998). Intrinsic dynamics and mechanosensory modulation of non-nutritive sucking in human infants. Early human development, 52 (2), 181-97 PMID: 9783819

There is a rumor in the scientific community that, by entering the right combination of keywords and Boolean expressions into PubMed, one can unlock a clandestine trove of high-quality, peer-reviewed, NIH-funded pornography. Although the cipher has not yet been cracked (it’s definitely not “intrinsic+sucking+dynamics-nutritive”), this exercise recently led us to a fetching little pape of disarming sickness.

In 1998, Donald Finan and Steven Barlow embarked on the exploration of the central pattern generator that regulates baby feeding, referred to in this pape as the “suck CPG”. Since Aristotle, and perhaps even before, it has been known that babies will happily slurp on a gorgeous nipple. However, it was not known whether this behavior requires mechanical feedback from the mouth, or if it is controlled exclusively by feedforward signals from the brain. To solve this inscrutable question, Finan and Barlow endeavored to control the mechanical stimulation that babies experienced as they sucked.

The sword in the stone that enabled these experiments was a home-made device called “the actifier” (described in a separate technical report).  The actifier was to pacifiers what the 1998 Arctic Cat Jag 440 Deluxe was to snowmobiles: that is, voluptuous. The actifier came fully loaded with 4 pairs of EMG electrodes (to record jaw muscle signals), a pressure transducer (to track the sucking amplitude of the baby), and a strain gauge (to measure jaw displacement). Unlike the ’98 Jag, she did not have a Big Slam sized cup-holder with built-in koozie, but made up for it with a pneumatic cylinder coupled to a breast-like “baglet”. My impression is that, in terms of blowing the mind of stoned high school kids who have just discovered the unfettered liberty of complimentary snowmobile test drives, the actifier would have given the Arctic Cat a run for its proverbial money.

That needlessly complex description should not dissuade you from fully appreciating this instrument. Let’s start over. Basically, what these guys built is a fake boob that measures baby sucking. It’s non-nutritive cause the babies don’t get fed. The experimenters pump the baglet in various ways, and observed that baby sucking activity depends on the baglet’s movements.

According to my lovely girlfriend, who is not herself a mother as far as I know, but an avid eavesdropper of breastfeeding street-women, it can actually be kind of hard to get your baby “to latch on” to the nipple. Indeed, the authors argue that “non-nutritive sucking is a deceptively complex behavior”, because it is not purely controlled by a central pattern generator, but also involves some sensory feedback. We should all be thankful that babies don’t go around needlessly sucking all over town, but only feel compelled to do so when they encounter a nipple or sinusoidally inflating baglet.

The thing is, although this pape is kind of ridiculous in its discussion of the “suck CPG” and the “cortical sucking area”, it’s got some deeply embedded sickness. If President Sarah Palin were to cut all funding for pure basic research, this is exactly the type of shit we would all love to work on. These Hoosiers got to spend months, or, more likely, years, building a nifty little virtual reality nip consisting of a bunch of sensors and actuators. I feel that this is something that the Burning Man community could really get behind, and probably ruin for everybody.

Contributed by butthill

The Tangential Nucleus Controls a Gravito-inertial Vestibulo-ocular Reflex.
Bianco IH, Ma LH, Schoppik D, Robson DN, Orger MB, Beck JC, Li JM, Schier AF, Engert F, Baker R.
Curr Biol. 2012 Jul 24;22(14):1285-95. 

Rather than praising the drastic sickness of this pape, I want to go out on a limb and directly address the monumental sickness of this interview. Holy Shit. Someday, when the impact factor of Sick Papes exceeds all other journals combined, we will look back on this transcendent moment when the first piece of sick data hit the Sick Papes deck.

Now, a bit about the pape: An incredible truth about animals is that they can keep their eyes pointing straight ahead while shaking their heads back and forth. This is because of a little thing we tree-huggers like to call the vestibulo-ocular reflex, which is basically a neural circuit that compensates for head movements by rotating the eyes in the opposite direction. Without a functioning vestibulo-ocular reflex, you wouldn’t be able to read papes at all, because every small head tremor would cause your eyes to bobble around the page.

Freaks have been studying this reflex in monkeys and rabbits and shit for a long time, but the problem with those critters is that they are genetically frigid. That’s why our pals Bianco, Ma, and Schoppik began studying the vestibulo-ocular reflex in the adorable larval zebrafish, which will definitely allow you to feel its genome on the first date, and you can even manipulate it a bit with some savoir-faire. These guys recently dropped a Sick Pape in the pages of Current Biology, in which they crack the tiny circuit that controls the larval zebrafish vestibulo-ocular reflex. We sat down with co-author Dr. David Schoppik over some fried flounder to get his opinions on all things vestibulo.

SP: Your pape elegantly demonstrates that when you shake larval zebrafish up and down, the fish rotate their eyeballs back and forth, helping to stabilize their visual field. Does this behavior (the vestibulo-ocular reflex) occur during both self-imposed and externally-generated movements? How did you make sure that the fish were not visually fixated on an object while you wiggled them up and down? Did you control for constant background giggling during these experiments?

DS: Little is known about the natural movements in three dimensions of the larval zebrafish. Generally, behavioral experiments tend to be performed in relatively shallow water, allowing focus on X and Y, without much love for the Z dimension (depth). So we’re not entirely sure what the larval zebrafish would do when, say, they dive down in the water column. Further, the little suckers move really fast, and their eyes are super small, so we’ve never been able to observe precisely what their eyes are doing.

That said, it’s pretty easy to see the eye of an adult fish rotate to compensate for the body under normal swimming movements. I recommend spending some time pressed up against the next aquarium you come across, following the eyes of the fish as they move about in the torsional plane. Then, while still in front of the aquarium, turn your head such that your ear moves towards your shoulder. This will give the fish ample opportunity to observe your torsional eye movements, which we feel is only fair.

Our experiments took place in the dark to eliminate the contribution of the visual system.  All giggling, snickering, guffaws or chortles were restricted to periods of the data analysis, or reviewing each other’s drafts. All experiments were conducted with the utmost reverence.

SP: Do zebrafish blink? If not, do they exhibit a vestibulo-ocular reflex when they are asleep? Have you thought about repeating these experiments in upside-down sleeping sharks?

DS: Physiologically speaking, without an eyelid or nictitating membrane zebrafish have no way to blink. However, working from the title of Malcolm Gladwell’s book, “Blink: The Power of Thinking Without Thinking,” we feel that there is a strong chance that larval zebrafish may be Thinking Without Thinking. Fortunately, we study reflexes, which don’t require Thinking, with or Without Thinking. Regrettably, we currently have no reliable way to determine whether or not a larval zebrafish is sleeping, such that we could compare the VOR during sleep and wake. However, many of the experiments were carried out at different points during the day, and with different levels of rest in between, and we observed no reliable differences between “early” and “late” experiments. As per Figure 6, since the otolithic organs work similarly regardless of whether the fish is upside-down or in a normal orientation, we would expect similar results to obtain in an upside-down shark, sleeping or not.

SP: Your pape traces the vestibulo-ocular reflex from sensory input to motor output. How does this three neuron circuit compare to the vestibulo-ocular  circuitry in your average dude loitering outside Dunkin’ Donuts?

By and large, the “three neuron circuit” we find in the larval zebrafish is indistinguishable from the canonical VOR circuit proposed by the anatomists of old.  Crucially, with respect to the functional aspects of the circuit, our local Dunkin’ Donuts is located in Central Square, Cambridge. As such, for an appropriate comparison, I must refer you to the following oh-so-sick pape characterizing the VOR in pigeons: Anastasio, T.J. and Correia, M.J.. “A frequency and time domain study of the horizontal and vertical vestibuloocular reflex in the pigeon.” J Neurophsyiol 59:1143-1161, 1988. (c.f. “During the rotation paradigms, the pigeons were either pharmacologically aroused (using amphetamine) or drug free (normal).”)

SP: Of all previous US presidents, who do you think had the most robust vestibulo-ocular reflex? The weakest?

DS: Too much work to make the little animated GIF based on Millard Fillmore’s Wikipedia page portrait. But if you want to make it, we’ll write you a caption.

SP: In humans, the vestibulo-ocular reflex is somewhat plastic; for example, wearing prismatic goggles for a few weeks can cause changes in the amplitude and direction of compensatory eye movements (Sick Papes, unpublished observations). Is this also the case in zebrafish? How might such learning occur within the simple three neuron circuit you have identified?

Each generation thinks that it discovered sex, and so it goes with the remarkable plasticity of the human VOR. In an oh-so-sick pape, Gonshor and Melvill Jones (1976, J Physiol. 256 pp 381-414) report functional reversal of the sign of the VOR in humans with prism-induced horizontal reversal of the visual field. Basically, all your unpublished observations belong to Gonshor and Melvill Jones.

Using the VOR as a model to understand plasticity has a long history, full of sick papes too numerous to list here. While there is no evidence as of yet that visually-guided learning takes place in the larval zebrafish, if it did it would likely involve projections from the cerebellum to central vestibular neurons, as has been described in the primate. We are delighted to refer your readers to the Ebola virus of sick papes: the series of three papers published by Lisberger et. al. in the Journal of Neurophysiology, August 1994. Allow me to just paraphrase his introduction, because it’s best to just let the man speak for himself: “In the past 10 years, we have conducted a systematic analysis of brain stem and cerebellar neurons that may participate in motor learning in the VOR. We present our results in three papers. The first paper shows that changes in the gain of the VOR cause large changes in the responses of one class of brainstem neurons that receive input from the cerebellum, and respond rapidly enough to drive the behavior. The second paper reports the effects of motor learning on the responses of Purkinje (i.e. output) neurons in the cerebellum, and shows that most of these neurons respond too late to drive the behavior. The third paper uses measurements of eye movements and computer simulations to develop a new hypothesis for the sites of motor learning in the VOR.” Just beautiful.

SP: What sort of neural transformations do you think are occurring in the tangential nucleus? Have you recorded or imaged from these neurons? If so, would you be willing to publish this preliminary data on Sick Papes?

There’s no shortage of work describing the response properties of avian and anural tangential nucleus neurons. However, perhaps the most interesting transformations in the larval zebrafish tangential nucleus are those that accompany the drastic improvement in behavior in the first week or so of life. We imagine these neurons are intimately involved, and that their maturation likely matches the ability of the zebrafish to perform the VOR. We are in the process of both recording intracellularly and imaging Ca2+ activity in these neurons, and are delighted to share with you the electrical responses of a putative tangential nucleus neuron, Ascending type, to increasing amounts of injected current (see below).

spikes

SP: Larval zebrafish possess otolithic organs, and can only detect linear accelerations. Human dudes (and adult fish) also have semicircular canals, which can detect angular acceleration. Can you describe what it would feel like if we had only otolithic organs, and could not detect angular acceleration? Does this ever happen to people?

Amazingly, reports of semicircular canal aplasia can be found, but they are usually accompanied by other symptoms (e.g. CHARGE association). By and large, though, information from our other sensory systems (vision, proprioception, otoliths) does a remarkable job at masking developmental disorders of the vestibular apparatus. So, if we had only otolithic organs from birth, we probably wouldn’t notice much of a difference. It would be a bit more difficult to make our way in the dark, and stabilizing gaze during high frequency movements would be harder. The symptoms associated with acute loss of semicircular canal function would likely be more profound: dizziness and vertigo are quite likely.

SP: It seems that the changes in pressure brought about by swimming up and down in a big friggn lake could affect the function of vestibular organs (like when I am scuba diving in complete darkness and I lose my sense of which direction is up and which is down and from whence I came). Are the vestibular systems of underwater critters fundamentally different from those of above-water critters? 

DS: This sort of disorientation sounds to me like a bit of a first world problem. Changing atmospheric pressure, say, by going where humans clearly don’t belong, can indeed result in awful things like perilymph fistula. You don’t want any of that — it is treated with stool softeners. Generally, because the inner ear is a bony structure, we aren’t aware of any fundamental changes to the organization of the labyrinth. However, Arthur Popper has suggested that because of the limited light available in the deep sea, there is pressure on other senses, particularly hearing, and there may be specialized adaptations that allow greater auditory sensitivity.

SP: In your pape, you show that  the vestibulo-ocular reflex is driven by the tangential nucleus, a part of the brain first described by our man Ramon y Cajal. Cajal predicted the function of many of the brain regions he studied. Did he make any sterling prophesies about the tangential nucleus, and if so, was he right? Have you ever considered adopting Cajal’s well-manicured soul-patch vibe?

Here, we must admit our ignorance: the original paper Cajal wrote on the tangential nucleus is in French. Consequentially, we can only claim to have read it at approximately a seventh grade level. Fortunately, this is more than sufficient for Sick Papes. Also, we have the benefit of 100 years of research that showed that indeed, as he predicted, most of the neurons in this area are descending vestibular neurons, except for some that go to the cerebellum, and some that go to the oculomotor nuclei.

Contributed by butthill
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