Piketty, Thomas. Capital in the Twenty-First Century, Cambridge, MA: Harvard University Press, 2014.
We live in the so-called “information age.” Mid-way through my recent hippie wedding to my brilliant and beautiful hippie wife, the cold hard facts of the times in which we live broke through the fuzzy math of our timeless love. The scents of lavender and rosemary wafted through the wooden ceilings and floors of the quaint nondemoninationalinterfaithseriouslyanyidentityiscool chapel. A founding editor of Sick Papes — z/s/he who must not be named — arose to give a rousing, heartfelt testimonial of our incontrovertible goodness-of-fit. I was moved to tears. Then, our fearless editor let drop some critical supplemental material regarding the woman who was moments away from becoming my betrothed. “But there’s one thing you should just accept right now. Your wife,” z/s/he deadpanned. “She is a data monster.”
Now my liberal arts hippie education had taught me that the roots of our modern world lie in white supremacy, patriarchy, and the cultural hegemony of the West. But a new life of knowledge lay ahead of me. From now on, to paraphrase a t-shirt I once bought at South New Jersey’s Cowtown Fleamarket, if you ain’t a data fan, you ain’t shit.
Luckily, my wedding coincided with the release of a sick book about a data-driven approach that I can get behind. In his new book, Capital in the Twenty-First Century, Francophone Thomas Piketty dances the gavotte with a trove of data so sick, so monstrous, so exhaustive and so beautiful that even the usually irascible Paul Krugman had to just be like, ‘Imma step back and let you finish.’ As though forged from the consummation of all my intellectual and spiritual obsessions, the themes of the book and its reception also bear more than a passing resemblance to rock and roll heroes, anti-heroes and feuds of the twentieth century. This is an issue that I will get to in a moment.
But first, here’s one way to describe the basic argument. Essentially, insatiable data séducteur Piketty marshals centuries of wealth and income records from France, Britain, the United States, and occasionally a few other Northern European countries, to demonstrate some disturbing tendencies of capitalism. In particular, his data show that inequality has grown significantly since the industrial revolution in the West due to the observed reality that the rate of return to wealth has generally been much greater than the rate of growth in an economy.
There are actually a lot of arguments in this book. Coming in at over 600 pages, one might suspect Piketty is afflicted by logorrhea. Or maybe he’s trying to overwhelm his critics with the sheer volume of his words/figures/publicly accessible excel spreadsheets. But you know what? Sometimes that’s just how a data monster rolls. So here’s the summary slide in layman’s terms: if you own capital (things like real estate, financial stock, and industrial equipment) then you will get much richer, much quicker than if you rely on the income you expect from being a working man/woman/Z. This is because the growth of jobs is, in the bigger scheme of things, highly dependent on the growth of the economy as a whole, while growth of capital is dependent on other things such as accessing returns to production using existing capital, which can be relatively or even totally independent of labor.
As a side note, one of the twists on this argument, especially in the United States, is that there is also a major divergence in income inequality. Especially with respect to the top 1% and even the top .01% of earners, this is because of the emergence of a new class of so-called “supermanagers.” This term can mean one of two things. Either A) there is this new class that is just so fucking good at raking in cash for their companies that there is no way they could not be deserving of astronomical salaries and bonuses, hundreds of times the earnings of the average employee in a given firm. Or B) this group of “supermanagers” is actually a group of “super-board-packers,” and ensure that the people who decide to hire them, give them raises and bonuses, are their fuck buddies who get titillated by — or are willing to pretend to get titillated by — all the nasty butt speak in option A.
Anyway, these findings are all well and good, but Sick Papes is first and foremost a highly relevant cultural blog as I had understood it. So I’ll leave the economic crap for now. Instead, it has come the time for me to reprise a question that I last asked regarding Kanye West almost ten years ago. Is Thomas Piketty the new Bob Dylan?
Let’s examine the evidence. This French novelist-inspired, surrealist economist draws on the traditions of counter-cultural folk economics (eg. Karl Marx aka the Woody Guthrie of the social sciences), upends accepted mores with state of the art technologies of the field (eg. Stata aka the Stratocaster of data computing), and yells “va te faire foutre!” to the data haters while the guardians of the neo-classical flame try to cut off his mic with an axe (eg. the Financial Times aka Pete Seeger).
Hold up. The Financial Times? Let me explain. Indeed, Piketty is now engaged in a cultural battle last witnessed almost a half century ago when Lynyrd Skynyrd and Neil Young went head to head on rock radio airwaves. Arguably, Young fired the first shot, releasing a stinging, and highly empirical condemnation of racism in the southern United States in his song, ‘Southern Man.’ Here’s a typical verse:
I saw cotton / and I saw black, tall white mansions / and little shacks / Southern man, when will you pay them back? / I heard screamin’ and bullwhips cracking / How long? How long?
Well you know who else became one of “those people” last week? The aforementioned economics editor of the Financial Times. Suddenly, he claimed that, most explosively, Piketty had ignored a dataset that seemed to indicate that inequality had actually been dropping in Britain to levels that would make the UK even more egalitarian than Sweden. Then the FT splashed this “finding” across the front page of the newspaper in what basically amounts to academic cyber-bullying, that is, publication without peer-review.
Those people. Leeching off of the hard work of others and claiming their right to journalistic handouts. SMH.
Piketty took six days to release his ultimate smackdown. In this 4000 word response, he elucidates a very clear statistical methodology that also exposes just how erroneous the Financial Times’ approach was. Even the new data set upon which the FT’s case rests is self-described as “experimental.” And not in the good way. I suspect Piketty must have been listening to a recent album by liberal arts-educated hip-hoppers Das Racist. Piketty essentially said to the Financial Times, “Sit down, man. It’s time for a global tax on the wealth of all of these uncivilized wealth-hoarders.” I suspect he hit “send” on his review, and then went out to buy a Shure SM57 microphone just so he could drop it like the economic bad-ass that he is.
As Bruce Springsteen once sang, “we learned more from a three minute record than we ever learned in school.” Well, I sure learned a hell of a lot from these extracurricular experiences this past month. First, I learned to comprehend in such a profoundly joyous way the love that surrounds me and my lovely wife, the “data monster.” And, soon afterwards, when I finished this sick treatise, its last words resounded deep in my soul:
“It seems to me that all social scientists, all journalists, and commentators, all activists in the unions and in politics of whatever stripe, and especially all citizens should take a serious interest in money, its measurement, the facts surrounding it, and its history. Those who have a lot of it never fail to defend their interests. Refusing to deal with numbers rarely serves the interests of the least well-off.” (577)
Shout out to my editor on this piece, aka sickest pape writer ever, aka “the data monster,” aka my wife.
We have recently learned that a dear friend of ours, Camille Barr, is ill with brain cancer. Camille was a very important friend and mentor to many of us here at Sick Papes, and we wanted to pay tribute to her science and to her contagious love for life.
In the hustle and muscle of the quest for the next Sick Pape, it is easy to forget that one of our most important responsibilities as scientists is to train and mentor the next generation of sicksters. It can be a thankless job to babysit and clean up after infant scientists, and yet there are heroes among us who embrace this task with grace and compassion. Today, we recognize one such hero, a singular woman whose kindness, humor, and rigor as a scientist made an indelible mark on the impressionable minds of three fledgling scientists.
Way back in 2006, Camille Barr was a post-doc in Lila Fishman’s lab at the University of Montana. Three of us Sick Papes vets had our first lab technician jobs in Lila’s lab (a 4th worked across the hall with her husband, Scott). We were fresh out of college and excited to learn how to do biology. Camille was the one who taught us how to purify DNA, how to do PCR in 96-well plates, and how to stay on the good side of the evil She-Goblin who ran the sequencing facility. We spent many afternoons working side by side with Camille in the greenhouse, growing the 9,000 seedlings that formed the basis of her big project and today’s Sick Pape.
Barr CM, & Fishman L (2010). The nuclear component of a cytonuclear hybrid incompatibility in Mimulus maps to a cluster of pentatricopeptide repeat genes. Genetics, 184 (2), 455-65 PMID: 19933877
Blooming flowers pack a tremendous whallop of human emotion: delicate beauty, tenderness, love and - if incorporated into the right tattoos - a horrifying link to the Army of the Night. But the beauty of floral diversity is more than skin deep.The radiations that spread flowers all over the world also offer a surfeit of human opportunity to understand the molecular mechanisms by which dumb luck and ecological adaptation drive the creation of new species, which are often exquisitely adapted to whatever swamp, mountain ridge or post-apocalyptic amusement park they ended up in.
Since plants can’t move (A. Bruce Saunders, personal communication circa 2005), neighboring flower populations often exist at different points of the species boundary continuum. In the lab, you can test the functionality of these boundaries directly by artificially mating neighboring sub-species of flowers. The resulting flower-children have mosaic genomes and by sampling a small piece of tissue from each plant, it’s possible to attribute each genetic chunk of each mosaic chromosome to either parent species. Some combinations of parent genomes make a functional plant. Others do not, and it is likely that these chunks of the genome are responsible for the divergence between the emerging species. By sampling thousands of plants with mosaic genomes, you can infer statistically what genome combinations are lacking and are thus incompatible. You can also test which “mutt” plants are producing working pollen and which are shooting blanks, and whose sterility will thus be an evolutionary dead end.
Genetic incompatibilities are the fuel of speciation, the final straw. Their biochemical details often highlight near misses in essential processes for building a viable organisms. In essence, protein gears from one species that have mutated just far enough not to fit in the protein cog of the other. Once we know what genetic mismatches build boundaries in the lab, we can dip out, return to the field, smoke some grass, and track how ecology and evolution utilize these particular genes as gears and cogs in the wild.
One epic and historically important stage for tracking flower species boundaries is Iron Mountain in the Southern Cascades in Oregon. Every spring, just after the snow melts, two neighboring populations of Monkey flowers (Mimulus) come bursting out of the ground (Figure 1). Before she got her own lab at the University of Montana, Lila Fishman, working with John Willis at Duke, had taken Mimulus guttatus and Mimulus nasutus from Iron Mountain, made crosses, and grew up the mutt plants in the greenhouse. One of her startling discoveries was mutt plants carrying a particular piece of nasutus chromosome had sterile pollen (Figure 2). But only when those mutt plants were generated from matings wherein guttatus was used as the “mom”. When nasutus was the mom, the same chunk of nasutus chromosome - called the cytoplasmic male sterility (CMS) locus - left the equivalent mutts with perfectly normal pollen.
Figure 1. Mimulus (the yellow flowers) growing on Iron Mountain. Photograph courtesy of Sick Papes.
Turns out in plants, just like in humans, the plant-egg (called a gametophyte) donates all the cell-juice (cytoplasm) to the developing organism. And what essential organelle lives in the cytoplasm and has a genome of its own? The mitochondria! Thus the CMS phenotype arises via a genetic interaction between the mitochondrial and nuclear genome. While both genomes care about the health of the plant, only the nuclear genomes gives a flying Fuze drink about pollen. Another tragedy of male sexuality. Kamikaze mitochondrial mutations that affect the plant’s ability to produce eggs would be a dead end, but mutations that affect pollen production? No biggie for mitochondrial survival to the next generation. But without pollen, the plant population will quickly crash and burn. This situation creates intense evolutionary pressure to select for mutations in the nuclear genome that counteract what went wrong in the mitochondria to restore pollen fertility.
Figure 2. Sterile pollen (left) and viable pollen (right) of Mimulus mutts (taken from Fishman and Willis 2006)
And sure enough, some of the Mimulus mutts that should have been pollen sterile were not. These fertile freaks contained a mystery part of their genome that, when it originated from the same species as the mom (guttatus), were completely spunky. Lila called that version of the gene “The Restorer.” In the wild, the current guttatus population has both the pollen-damning mitochondrial mutation and the counterbalancing Restorer mutation so, despite the internal drama, their pollen was normal.
In these experiments, Lila didn’t know what genetic elements constituted the CMS or the Restorer, she only had meaningless genetic markers located close to these genes. Some brave soul needed to ID these friggin’ genes and bring this genomic turf war to the streets.
Enter our hero, Camille. Identifying the gene that constituted the Restorer would yield insights into both the mysterious ways the nuclear and mitochondrial gene products can interact (a basic, largely unknown cell biological phenomenon) and how evolutionary pressures sculpt the genetic landscape and natural history of a natural population of flowers. But for such rich insights, there was a difficult experimental burden. In order to tease apart the large region where the Restorer was situated, and to distinguish guttatus/nasutus alleles, Camille would need to add many more genetic markers. She would need to breed a plant that carried the sterilizing mutant mitochondria and was almost completely nasutus but still had functional pollen. Then the only guttatus genome chunk still present would implicate the genomic region that contained the Restorer.
After creating the markers, Camille undertook a massive breeding experiment, genotyping and pollen phenotyping of over 6,000 plants. She paid particular attention to a large array of pentatricopeptide repeat genes (PPRs), within the region containing the Restorer. PPRs had been implicated in restoring pollen fertility in crop plants. PPRs bind mitochondrial mRNAs and regulate their expression, thus changes in PPR function offer a plausible mechanism to buffer otherwise sterilizing mitochondrial mutations. In a heroic effort of mapping, Camille determined that the Restorer resided in two small PPR clusters very close to each other on the same chromosome. Why two instead of one? Camille and Lila provided evidence that if either one of the clusters was guttatus in origin it was sufficient to Restore. And by further narrowing the candidate genes in each cluster to those whose sequence suggested they would be targeted to the mitochondria, Camille isolated 1 and 6 likely genes in each cluster.
Figure 3. Chromosome schematic of the two Restorer PPR clusters in the Mimulus guttatus genome. PPR genes are shown as rectangles. Black rectangles denotes those PPR genes putatively targeting the mitochondria (form the sick pape itself).
Camille’s results suggest that the PPR genes combat selfish mitochondrial mutations across the plant kingdom. More vividly, they capture evolution in action: the presence of two closely spaced PPR clusters that are sufficient to restore pollen fertility suggest a recent duplication of the restoring region. These duplications create the PPR diversity essential to buffer future mitochondrial mishaps. Considering that the Mimulus genome, like other plant genomes, is chock full of PPRs, this nuclear/mitochondrial arms race is likely an ancient and powerful force in sculpting the genomic landscape of plants.
After she slayed the Mimulus Restorer, Camille decided to switch things up. Soon after we left Montana, she decided to go to law school. In 2012, she successfully became a practicing attorney, specializing in intellectual law. But even as she was studying law at UC Irvine, Camille would regularly visit the populations of wildflowers she had studied during her Phd. Somehow, in the midst of becoming a high-octane, power-suit-wearing attorney, Camille discovered a new flower species, which she named Nemophila hoplandensis after one of her favorite haunts— the UC’s Hopland Research & Extension Center. Camille’s Pape describing the new species (the white one below), which includes genetic crosses with related Nemophila species and molecular phylogenetics data, will be appearing in an upcoming issue of Madroño, the journal of the California Botanical Society.
Thinking back on our days in Missoula, Camille was as bright and exuberant as those thousands of flowers we grew together. Today, reading our names in the compact Acknowledgements section of this Pape, it is difficult to describe the depth of experience hidden in those few sentences, and it certainly does not capture the warmth and affection Camille gave to her crew of sloppy techs.
In response to overwhelming (and legally binding) demands from fanboys and House Republicans alike, we have joined Twitter. So now all the non-Tumblr people can stay up to date on what’s really and truly hot right now. See you there!!
Sick Papes sat down with Jonathan Tang to discuss his recent paper “A Nanobody-Based System Using Fluorescent Proteins as Scaffolds for Cell-Specific Gene Manipulation.” Sick Papes also did this interview the old fashioned way, like an idiot, by recording and transcribing rather than emailing and relaxing. Hence the big delay. But like rediscovering a bottle of once lost liquor in your dirty clothes pile, you should be excited: Jonathan took advantage of antibodies from a camel to make GFP – the head honcho fluorescent protein for cellular visualization – friggin’ functional, as the key scaffolding ingredient in a threesome of transcriptional hedonism. He calls these nanobodies “transcription devices” and if you F with GFP, you better start getting creative.
Jonathan Tang et al. 2013. A Nanobody-Based System Using Fluorescent Proteins as Scaffolds for Cell-Specific Gene Manipulation. Cell 154, 928–939
SP: I’d like to start this interview with a quote from the movie Nacho Libre. Have you ever seen Nacho Libre?
SP: Okay well it’s a movie where Jack Black plays a Mexican wrestler and at one very important point in the movie he says, “Under the clothes we find the man and beneath the man we find… his nucleus.” What type of man are you and what’s up with your nucleus?
JT: Okay. I guess on the surface I’m pretty shy person. Underneath I am someone who wants to change the world. And my nucleus? I hope it’s functioning well, with little UV induced damages.
SP: You’ve invented a technology for retrofitting transgenic organisms called “transcription devices dependent on GFP.” Can you explain GFP and “transcription devices” to our readership?
JT: GFP stands for green fluorescent protein, it was discovered in a jellyfish 40-50 years ago and emits green fluorescent light. GFP has been put to use as a tool in molecular biology since 1994, allowing researchers to tag proteins and visualize cellular processes. This has been a powerful, Nobel prize winning tool for researchers. Regarding “transcription devices,” that’s a fancy name I gave to an engineered, hybrid transcription factor. The idea is to make the device activate transcription, but only when its two independent protein parts are tethered to GFP. If GFP is present in the cell, the device be fully formed and functional to initiate transcription in a downstream gene of interest.
SP: Most SP readers have a 3rd grade education. How would you explain this technology to a 3rd grader?
JT: I don’t know if a 3rd grader would understand genes, but here it goes: the transcription devices are present throughout an organism but remain inactive except in cells with GFP. In these cells, devices tether themselves to GFP and initiate events inside cells to turn on other genes.
SP: How does this interaction actually work?
JT: It’s based on protein-protein interactions. The devices are binding proteins derived from camel antibodies that bind to GFP with high affinity. The reason why we use camel antibodies is because the antigen recognition domain is contained in a single peptide segment. Conventional antibodies are hard to express in cells as they are made of two proteins joined by a breakable disulfide bond. I found that there were pairs of the these camel antibodies that recognized different parts of GFP and could co-occupy GFP. This allows one to simultaneously tether different protein domains on to GFP. In this case, I tethered a DNA binding domain with one camel antibody and a transcription activation domain with another. GFP is then the scaffold for forming an active transcription factor which can then initiate transcription of any gene of interest downstream of its genome binding site.
SP: It seems like you kind of owe the camel a lot. Pretend I’m a camel. What would you like to say to me?
JT: I guess for the sake of the next Nature paper, tell me why you evolved single chain antigen binding domains. Please tell me that. If you do, I’ll pay you back with a lot of water.
SP: Like middle-author type water?
JT: Like a gallon of water. Other than that, thank you very much you solved my problem.
SP: At any point in your project, did you make a scale model of GFP in your kitchen to try and identify where the transcription devices would bind?
JT: Not quite like that, but I did do a look at a lot of crystal structures and computational models of GFP structure, along with the structures of the GFP binding nanobodies. I just kept trying to fit them together. Turns out it was a waste of my time, because in the end I had to empirically pair-wise test all 6 nanobodies.
SP: How happy were you when you found a pair that worked ?
JT: I was pretty happy actually. I was in the lab at like 5 o’clock in the morning (editors note, JT is a confirmed night owl) and there was nobody around. I was just so happy, but there was no one to tell. Then my adrenaline went up and I walked around the building looking for people to tell but there was still no one. So I went back to work.
SP: That was a breakthrough moment in the project?
JT: Yes. There was no way to know if the system would work at all. I only had the six nanobodies which were generously given to us.
SP: It’s amazing how a couple of hours of positivity can energize us to wade through a swamp of disappointment that can last years.
JT: That’s true. Prior to that moment there was a lot of disappointment.
SP: Did you try other systems?
JT: Yes, I tried to make a Cre recombinase into a GFP-dependent into Cre recombinase. It was a naïve idea. But those experiments were helpful, as they did told me that the nanobodies could direct GFP to distinct compartments in the cell. That was the first clue the reagents I had could tether GFP.
SP: How do you think about, or visualize, these high affinity interactions between the nanobody devices and GFP? Like a key in a lock? Bugs on a windshield?
JT: Yes, I think of them as locks and keys, they simply come together. Without the high affinity, I don’t think it would work very well.
SP: One of my favorite things about this paper is that the technology that’s developed is not only an important proof of concept, but is immediately of practical use. What is the current utility of your GFP nano-bodies? Where do you see this technology going forward?
JT: One of the exciting applications is for retrofitting transgenic GFP animals. Many GFP lines have been engineered to express GFP in genetically defined populations of cells. For example, the GENSAT (http://www.gensat.org/index.html) project has over 1,500 mouse lines for labeling neuron populations in the brain and retina. Now the question is can we use these nanobody devices to perturb function in GFP expressing cells. One idea would be to turn on the light-sensitive ion channel channelrhodopsin in GFP expressing brain cells to make these neurons fire action potentials with light. As we show in the paper, with this technology you can probe the downstream brain circuitry from the cells that were previously only visualizable. In the long term, this paper suggests that GFP itself is a great transgene. Because it can be used for anything. You can imagine building many types of synthetic systems that use GFP to turn on or off different cellular processes, by mating GFP animals to other animals carrying nanobody devices or by introducing these devices with viruses.
SP: Have you thought about targeting your transcriptional devices to other proteins too?
JT: You mean using other proteins for turning on the system? That’s something that we’re looking into doing.
SP: One more question for you, on behalf of the molecular aficionado readership: In your paper, you note that there are pros and cons to your devices vs. traditional recombinases for manipulating genomes. Can you explain those pros and cons?
JT: The current system uses three components to form the hybrid transcription factor. While this is not as efficient as functional single molecules like Cre, it does have the ability to achieve more specificity through intersectional expression of the individual components. The other problem we experienced was having too much GFP, which sequesters individual nano-devices without the paired binding necessary for transcriptional activation. So the nano-devices have to be tested with each transgenic line. Unlike with Cre, which tends to enact permanent changes in a cell and its progeny, this system can also be reversible, dependent on the continued presence of GFP.
Year in and year out since the beginning of time, the amber fields of research programs across this great land are sprinkled with NSF fertilizer and grow the science crops that feed our hungry brain-mouths. While most days we feed our bloated carcasses on the high fructose corn syrup of the mind, every once in a while, you fill your cow horns with the right kind of manure, nail the astrological planting cycle and BLAMMO! - when the research harvest comes in, it comes in big. Well, it’s a boom year and the organic veggie du jour is bee learning and cognition. Here’s just one hors d’eouvre to whet your appetite:
My most vivid memories of childhood summers come from wandering along the Maine coast listening to my Aunt describe the auras of unwitting passersby, from “deep-blue” for the kid on a skateboard, “wispy green” for the owner of the Life is Good shop, and “surprisingly rectangular camo-colored” for the potbelly-sporting middle-aged man with a warm Budweiser and a Kiss lunchbox. Like these divine beach-goers, all living things (including the most heartless beasts of all creation: plants) give off subtle electrical fields. Despite its profound implications for literally everything, research on electric field perception has been mainly restricted to publications in Frontiers in Quack Science and F1000’s “What the $&*% do we know?” section. Two recent papers, though, are finally lending heft to the otherworldly electro-perceptational abilities of bees.
Up first is a sick pape showing that bees can sense electric fields created by plants. By creating artificial flowers (“E-flowers”, or E-cigarettes for bees) where they could measure and manipulate the electric field, Clarke and friends showed that bees can learn to differentiate between flowers that are completely identical except for their electric field. Mind-blowingly, the mere presence of the bee near a flower also changes the flower’s electrical pattern, so bees may be able to use their aura-sniffing abilities to figure out which flowers have been recently cleaned out by some other nectar-hungry bee.
While this study definitively showed the presence of the Third Eye in bees, more questions are raised than answered: Does the third eye align with the seventh chakra? Can the NSA use it to track my Private Browsing content? What causes Third Eye Blindness?
Thankfully, in a case of cosmic alignment, within a couple of weeks of this pape coming out, YET ANOTHER sick pape from a totally separate group gave us insight into how this might work. Coulomb’s law states that two charged particles will exert a physical force upon each other. Since insect antennae carry a charge, they could theoretically move in the presence of an electric field, allowing bees to perceive these electric fields.
In a beautiful series of “set em up and knock em down” experiments in our second sick pape, Greggers and amigos showed that bee antennae move in response to electric fields and that these movements juice up some specific neural pathways that allow the bee brains to perceive electricity. Indubitably sick.
sick papes would like to officially call out those nobel prize winners who only grow their hair out after they got their prize. i’m embarrassed i even have to write this, you poser shits. as if you weren’t already getting enough attention. if we see you in the street we’re apt to de-tail you through the confiscation of your “life is good” scrunchy. get a grip, last warning.
Gene-Swapping Spits Insight into the Mouth of the Vertebrate Mind
Nithianantharajah et al. 2012. Synaptic scaffold evolution generated components of vertebrate cognitive complexity. Nat Neuro
Ryan et al. 2012. Evolution of GluN2A/B cytoplasmic domains diversified vertebrate synaptic plasticity and behavior. Nat Neuro
Start private browsing. Under my favorite categories of experiments there on the right you’ll find “gene swapping.” Click on that. O sweet gene swapping. I’m back. It’s like momma earth just spat out DNA here just so experimentalists could do gene swap experiments and fucking rub their hands together and snort and drink coffee and wait for the results. I should start explaining gene swap experiments in this sentence but I just need to say one more time: in the world of dazzling complexity that is the cell or (eek) tissue or even (eek eek) the whole enchilada, swapping genetic elements offers a straightforward molecular razor for whatever. Currently we do it one element at a time, but in the future, who knows how many combinations we can apply and track before our brains explode.
Okay a gene swap experiment is pretty much exactly like it sounds. Change a single gene in some subtle or not so subtle way to something else. Make it non-functional say, or maybe just get a mutation that turns the protein in the human form or resistant to a flavor of post-translational modifications or swap subsets of gene-parts to figure out what part of the protein does what. And it’s slick as shit. Cause that baby’s siblings don’t have the change and you just compare your normal dude to the mutant you’re studying. Get at that infinitely complex cool and mysterious result stemming from something very discreet you did on the atomic/nanometer scale. Not bad human experimentalism not bad!
I’m blowing chunks on a couple of back to back Nature Neuroscience boon-diggler gene swap experiments right now: Nithianantharajah et al. and Ryan et al. (2012). I honestly follow this shit dropping from the Grant lab in the UK but I don’t understand it. I mean I understand it. I get their experiments for sure and that they’re trying to use a comparative approach across species to examine the evolution of the synapse and, well, cognition. But as pretty much the only guys in this business, it’s hard to predict what they’re going to pop out next.
Nithianantharajah et al (just fyi, it takes 10 ocean mana to tap this character into play but it’s worth it cause he’s got 12 hit points) assay the cognitive capabilities of mice that lack one of four Dlg genes. The Dlg family constitute major structural components of that sweet little signaling organelle that makes up the receiving half of the excitatory synapse. If the post-synaptic density is a lobster trap, then the Dlgs are the different gauges of chicken wire. There are four of these boogers because of ancient genome duplications in the vertebrate lineage. So to understand how each Dlg contributes to cognition is to understand how the duplication of genes allow each dupli-can’t to involve into a dupli-can!: a twisted sister of it’s own specialized function. One cool thing about this pape is the authors assay the cognitive prowess of each Dlg mutant mouse by forcing them to play an iPad. Like our society, but literally thirsty instead of spiritually thirsty. Each individual Dlg knock out showed different cognitive deficiencies suggesting a lack of functional redundancy in each of the 4 genes. Interestingly, Dlg3 knock out mice showed increased performance in tasks requiring cognitive flexibility and attention, meaning they might have a shot at beating my Mom at bejeweled. The take home load is that in these knock-out swap experiments, the authors demonstrate that ancient genome duplications allowed for the elaboration of the cognition of mice. That’s a pretty big rip on theory bong. Thanks straightforward knock out experiments and tablet computing!
Ryan et al. swap out the intracellular tails of another set of duplicated synaptic genes. This time the targets are the two main subunits of the NMDA receptors. NMDA receptors are ion channels that serve as coincidence detectors of neuronal activity and flux calcium, in what is equivalent of a particular synapse sending a text message about it’s state (“party’s on/party sux”) to it’s nearest neighbors and in some cases the friggin nucleus. The tails of the two subunits are a particularly informed switch since these parts of the proteins are the most divergent and function to bind different swaths of intra-cellular molecules. So it would seem each tail recruits a different signaling network to respond to calcium. So how do we test how this tail divergence influences cognition? GENE SWAP and iPADS baby!
So keep in mind: swapping out the tail of sub-unit A onto B means that both proteins have A tails and no B tail exists. So get double-duty of one tail and a complete lack of duty of the other. So whatever phenotypes emerge from these swappings could be due to a lack of B or over-binding from A (or synergies in between).
These dudes conveniently grouped the behaviors that were insensitive to the swap, only sensitive to unidirectional swaps, or sensitive to both swaps. Only impulsivity related behaviors required having both tails. Perception, anxiety, coordination and general activity levels required having one tail or the other. Learning in general remained intact when tails were swapped. Using the divergent tails of the NMDA receptor tails as a proxy, the authors suggest that more sophisticated regulation of motivational and emotional behaviors was selected for during the early evolution of vertebrates; learning is based on function that is redundant across tails and thus an older phenomenon.
Wow! Duh! And that’s how it goes in the field of synapse evolution
Waters, J., Holbrook, C., Fewell, J., & Harrison, J. (2010). Allometric Scaling of Metabolism, Growth, and Activity in Whole Colonies of the Seed‐Harvester Ant Pogonomyrmex californicus The American Naturalist, 176 (4), 501-510 DOI: 10.1086/656266/>
We all know the feeling: You’re lying naked in a sun-soaked field after taking a fistful of mushrooms and watching waves of energy explode through your friends’ braincases. And no matter how long you watch the trees breathe, just can’t shake the question: “Where does my body end and the world begin?” Turns out this cosmic question has a hallowed tradition, and just about no one knows how to draw boundaries around a body.
The little guys that fucks with our best minds most royally on this distinguished issue are the social Hymenoptera (ants, bees, and wasps). Dudes have been flubberbusting long and hard about whether we should think about the bees in a hive (or people in a city, or dicks in a game of dick jenga) as a wonderful communion of separate beings or as all just the dangly bits of one MegaMan. As the disturbing old saying goes, there’s many ways to skin a cat, but what perverted shitbag wants to to skin a cat a bunch of different ways? So the world was on the verge of turning its back forever on this age old question and exploding in a supernova of its own ignorance.
That is until some brave souls (Dr. James Waters and colleagues) figured out the illest of ways to blow the lid off a part of this problem. But let me slow my roll a bit and fill in the rubbly background that makes it crystalline just way this pape is so sick:
So, what these dudes did was investigate this same problem in ants, the superest of superorganisms. In an ant colony, you should be able to predict how much energy the whole colony is using based on their average body mass (e.g. you should be able to just sum up the metabolic rate of a bunch of small ants). But when they put whole colonies of these little guys in a fancy box that measures how fast they’re using up their cosmic energies, turns out they’re doing exactly not that. Specifically, their metabolic rate is what you’d predict for a single organism that had the collective mass of all the ants. And metabolic rate changes with colony size the same way it does for bigger bodies. So, in summary, ants (a) are fucking crazy, and (b) on both the mystical and physical planes appear to be working just like a single, physically integrated body does. Why? Lord knows. But this paper is opening up ways to answer that question and new ways to think about the most basic aspects of how organisms are put together. Sick.
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.