This is an extended version of my piece in the December issue of Prospect.
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Metaphors in science are notoriously slippery, but biologists seem particularly poorly attuned to the implications of theirs. The tenacity of the misleading “genes for” picture is one of their legacies.
You might think it’s sheer bad luck to be struck by lightning. But some of us are cursed with a struck-by-lightning (SBL) gene. Sure, as with many genetic conditions, if you have the SBL gene it doesn’t mean you will be struck by lightning, just that your chances are higher (here by a factor of about three or four) than those without it. But that seems a fairly big risk factor to me – and I should know, because I’ve got the gene.
Yet no one is working on a genetic remedy. Scandalous? Not really, because SBL can be identified as the gene better known as SRY, the sex-determining gene on the Y chromosome, which makes an embryo develop into a male. Yes, men get hit by lightning more often, because their behaviour – rushing about on golf courses and football pitches in the rain, that sort of thing – makes it more likely. Call it stereotyping all you like: the statistics don’t lie.
Geneticist Steve Jones has used this example to point to the absurdity of the concept of a “gene for”. If we knew nothing else about what SRY does, and it fell out of a statistical search for genetic associations with being hit by lightning, we might indeed conclude that warrants the label SBL. But the association with lightning strikes is merely a side-product of the way the gene’s effects play out in a particular environment. SRY could equally be misattributed as a gene for criminality, murder, baldness, watching Top Gear.
“The most dangerous word in genetics is ‘for’”, Jones has said. “Only fifteen years ago people expected that they would find genes for cancer, heart disease or diabetes. But medicine’s big secret is that we haven’t found them. And we haven’t found them because they are not there.” Compare that with Bill Clinton promising, next to smiling scientists in 2000, that the decoding of the human genome means “doctors increasingly will be able to cure diseases like Alzheimer's, Parkinson's, diabetes and cancer by attacking their genetic roots.”
What does this mean for the much vaunted age of “personalized medicine” – of health care tailored to our individual genome, which can now be decoded for a few thousand dollars and might soon be as common a feature as blood group and cholesterol index on everyone’s health records? The answer is complicated. Genetic data do reveal a lot about our inherent predispositions to certain medical conditions. But that doesn’t necessarily mean we have the “genes for” those conditions in any meaningful sense – genes that can be considered to lie at the “roots”.
The tendency to assign genes the responsibility for well defined personal attributes doesn’t just muddy the waters of post-genomic medicine. It distorts the whole public discourse around genetics, and arguably around the way genomes are shaped by natural selection. And it takes us down some dark avenues, from the notorious history of eugenics to the recurring minefield of how genes are influenced by race. The furore over the views expressed by former New York Times science reporter Nicholas Wade in his book A Troublesome Inheritance: Genes, Race and Human History is just the latest skirmish in this ongoing saga. Wade suggests that differences in social behaviour and characteristics among human societies may be genetically encoded. It’s an old argument, although expressed less crudely than in the anthropology of yore: the intellectual and economic hegemony of Western culture is down to innate biological differences. Scientists have lined up to savage Wade’s book, but the contentious questions it asks – are differences in, say, intelligence, rationality and social cohesion down to our genes? – won’t go away. Nor should they – but we’re not going to make much headway with them until we get to grips with the distinctions between what genes do and what genes are “for”.
Born that way
Geneticists now gnash their teeth at the bad journalism that proclaims the discovery of a “gene for”. But the burden of guilt for this trope lies with the research community itself. It’s not hard to find both implicit and explicit references to “genes for” in the literature or pronouncements of biologists. They are not always as ill-judged as DNA pioneer James Watson’s suggestion that genetic testing for “gay genes” could offer a woman the opportunity to abort a child that carried them. But the implication that traits such as personality and susceptibility to disease are necessarily determined by one or a few genes permeates the field. Without that sort of functional autonomy, for example, it is hard to see how the notion of selfish genes can be coherent. References to blueprints, lists of parts and instruction manuals during the Human Genome Project carried the same baggage.
It’s understandable how this habit began. As the modern era of genetics dawned and it became possible to probe the effects of particular genes by mutating, adding or silencing them (the latter being called “knockout” experiments) in flies, mice and other laboratory animals, researchers began to find clear links between the presence or absence of a gene variant – for brevity I’ll follow the sloppy convention and just say “gene” – in an organism’s genome and certain traits of the whole organism. Surely it stands to reason that, if you see a particular trait in the presence of a gene but not in its absence, that gene is in some sense a gene “for” the trait?
Well, yes and no. So-called coding genes contain the instructions for making particular proteins: enzymes that comprise the biomolecular machinery, and protein fabrics of the body. That’s the only thing they are really “for”. Spiders have a “gene for silk”; humans have a “gene for digesting the milk sugar lactose”. Mutations of these genes can be responsible for inheritable conditions.
But the lack or malfunction of a particular enzyme due to a genetic mutation can have complex knock-on effects in the body. What’s more, most genes are non-coding: they don’t encode proteins, but instead regulate the activity of other genes, creating complex networks of gene interactions. Most human traits arise out of this network, which blurs the picture a “genes for” picture. As the spurious “SBL gene” shows, it’s then wrong to infer causation from correlation. That’s not just a difficulty of finding the right genes within the network. For some traits, even if they are genetically encoded it can be inappropriate to talk of causative mechanisms and explanations at the genetic level.
Indeed, gene knockout studies tended to undermine the “gene for” picture more than they confirmed it. Time and again geneticists would find that, if they knocked out a gene apparently “for” a feature indispensible to an organism’s vitality, the organism hardly seemed to bat an eyelid. We now know that this is at least partly because of the immense complexity of gene networks, which have redundancy built in. If there’s a failure in one part of the network then, just as with closing a station on the London Underground, there may be an alternative route to the same goal.
Nothing here would surprise engineers. They know that such redundancy and failsafe mechanisms are an essential part of the robustness of any complex system, whether it is a chemicals plant or a computer. There is nothing that need have surprised geneticists either, who have known since the 1960s that genes work in self-regulating networks. All the same, I sat through countless editorial meetings at Nature in the early 1990s in which a newly accepted paper would be described breathlessly as showing that a gene thought to do this had now been shown to do that too. The language remained resolutely that of “genes for”: such genes were just multi-tasking.
One of the most notorious episodes of “genes for” from that period was a 1993 study by a team of geneticists at the US National Cancer Institute, who published in the premier journal Science the claim that with “99.5% certainty there is a gene (or genes) in [a particular] area of the X chromosome that predisposes a male to become a heterosexual” – in other words, in effect a “gay gene”.
Anyone interested in genes was already primed to accept that idea. Geneticists had been talking about a genetic basis for homosexuality since the 1970s, and in his 1982 book The Extended Phenotype Richard Dawkins used the possibility (“for the sake of argument”) to explore the notion of how a gene might exert different effects in different environments. For Dawkins, this environmental influence shows only that we must recognize a contingency about what a gene is “for”, not that the whole idea of it being “for” a particular trait or behaviour may be meaningless.
This complexity in the emerging view of what genes do is tellingly, and perhaps inadvertently, captured in Matt Ridley’s book Genome, published in 1999 as the completion of the Human Genome Project was about to be announced. Ridley offered little portraits of inheritable traits associated with each of the 23 human chromosomes. He began with a confident description of how the gene associated with Huntington’s chorea was tracked down. Here, surely, is a “gene for” – if you are unlucky enough to have the particular mutation, you’ll develop the disease.
But then Ridley gets to asthma, intelligence, homosexuality and “novelty-seeking”. All do seem to have an inherited component. “In the late 1980s, off went various groups of scientists in confident pursuit of the ‘asthma gene’”, Ridley writes. By 1998 they had found not one, but fifteen. Today some researchers admit that hundreds might be involved. In the other cases, Ridley admitted, the jury is still out. But it’s not any more: today, all the candidate “genes for” he mentioned in relation to intelligence, homosexuality and novelty-seeking have been ruled out. Isn’t this odd? There was Ridley, an (unusually well informed) science writer, declaring the futility of quests for specific genes “for” complex personality traits, yet finding himself compelled to report on geneticists’ efforts find them. So who was to blame?
Intelligence tests
On genes for intelligence, Ridley mentioned the work of Robert Plomin, who in 1998 reported an association between IQ and a gene called IGF2R. The fact that the gene was known to encode a protein responsible for a very routine and mundane cell function might have been a clue that the connection was at best indirect. That the gene had previously been associated with liver cancer might have been another. Still, Ridley said, we’ll have to see. In 2002 we saw: Plomin and others reported (to scant press attention) that they had not been able to replicate the association of IGF2R with IQ. “It doesn’t look like that has panned out,” he said in 2008.
“Anybody who gets evidence of a link between a disease and a gene has a duty to report it”, Ridley wrote. “If it proves an illusion, little harm is done.” Isn’t that just the way science works, after all? Surely – but whether innocent errors and false trails cause harm depends very much on how they are reported. Studies like Plomin’s are well motivated and valuable, and he has deplored the “genes for” picture himself. But there’s little hope that this research will avoid such associations unless biologists can do a better job of correcting the deeply misleading narrative that exists about what genes do, which has flourished amidst their often complacent attitude towards explaining it.
If you want to see the hazards of illusory gene associations, take the recent claim by Michael Gove’s education adviser Dominic Cummings that findings on the inherited, innate aspect of intelligence (in particular the work of Plomin) are being ignored. For a start, the very mention of genetics seemed to send rational argument out of the window. Some on the left sucked their teeth and muttered darkly about eugenics, or declared the idea “incendiary” and outrageous without bothering to explain why. That’s why Jill Boucher, writing in Prospect, had a point when she excoriated the “politically correct” attacks on Cummings’ comments. But unless Boucher can point to an educationalist or teacher who denies that children differ in their innate abilities, or who regards them all as potential Nobel laureates, she is erecting something of a straw man.
A real problem with Cummings’ comments was not that they attribute some of our characteristics to our genes but that they gave the impression of genetics as a fait accompli – if you don’t have the right genes, nothing much will help. This goes against the now accepted consensus that genes exert their effects in interaction with their environment. And the precise extent of inheritability is unclear. While IQ is often quoted as being about 50% inheritable, there is some evidence that the association with genetics is much weaker in children from poor backgrounds: that good genes won’t help you much if the circumstances are against it. (This finding is seemingly robust in the US, but not in Europe, where social inequalities might not be pronounced enough to produce the effect.)
Nonetheless, there’s nothing wrong in principle with Cummings’ suggestion that research to identify “high IQ” genes should be encouraged. But if he were to look a little more deeply into what it has already discovered (and sometimes un-discovered again), he might wonder what it offers education policy. A 2012 study pointed out that most previous claims of an association between intelligence and specific genes don’t stand up to scrutiny. Nor is there much encouragement from ones that do. In September an international consortium led by Daniel Benjamin of Cornell University in New York reported on a search for genes linked to cognitive ability using a new statistical method that overcomes the weaknesses of traditional surveys. The method cross-checks such putative associations against a “proxy phenotype” – a trait that can ‘stand in’ for the one being probed. In this case the proxy for cognitive performance was the number of years that the tens of thousands of test subjects spent in education.
From several intelligence-linked genes claimed in previous work, only three survived this scrutiny. More to the point, those three were able to account for only a tiny fraction of the inheritable differences in IQ. Someone blessed with two copies of all three of the “favourable” gene variants could expect a boost of just 1.8 IQ points relative to someone with none of these variants. As the authors themselves admitted, the three gene variants are “not useful for predicting any particular individual’s performance because the effect sizes are far too small”.
Perhaps, then, the media would be best advised not to call these “IQ genes”. But you could forgive them for doing so, for they’d only have been echoing one of the paper’s authors, the influential cognitive scientist Steven Pinker of Harvard University. The proper response to a study showing that most existing candidates for gene-intelligence associations were wrong, and that the few that weren’t contribute almost negligibly to inheritability, surely isn’t “Here they are at last”, but “Jesus, is this all there is?”
Where, then, is the remainder of the inherited component? It must presumably reside among a host of genes whose effects are too subtle to be detected by current methods. Those genes will surely be involved in other physiological functions, their effects in intelligence being highly indirect. They are in no meaningful sense “genes for intelligence”, any more than SRY is a gene for being struck by lightning.
So it’s not clear, pace Cummings, what this kind of study adds to the conventional view that some kids are more academically able than others. It’s not clear why it should alter the goal of helping all children achieve what they can, to the best of their ability. Such findings offer very dim prospects for Plomin’s hope, laudable in principle, that education might be tailored to the strengths and weaknesses of individual pupils’ genetic endowment.
Race matters
So, then, to Wade’s claims that genetics causes racial differences in traits such as the propensity for violence or the organization of social institutions. As Wade’s book has shown, the issue of race and genes remains as tendentious as ever. On the one hand, of the total genetic variation between random individuals, around 90% is already present in populations on a single continent – Asia, say – and only 10% more would accrue from pooling Europeans, Africans and Asians together. Some biologists argue that this makes the notion of race biologically meaningless. Yet ancestry does leave an imprint in our genomes: for example, lactose intolerance is more common in Africa and Asia, sickle-cell anemia in people of African origin, and cystic fibrosis in white northern Europeans. That’s why the concept of race is useful as a proxy for medical risk assessment and diagnosis. Besides, arguments about statistical clusters of gene variation don’t alter the fact that culturally conventional indicators of race – pigmentation and eye shape, say – are genetically determined.
What you choose to emphasize and ignore in this matter is largely a question of ideology, not science. But arguments like those Wade puts forward draw their strength from the simplistic notions of how genes relate to phenotype. We know that what we can, in this case, reasonably call cystic-fibrosis or sickle-cell genes (because the conditions derive from a single gene mutation) differ in incidence among racial groups. We also know that genetic variation, while gradual, is not geographically uniform. Might it not be that those variations could encompass genes for intelligence, say?
Yet if the genetic constitution of such traits is really so dispersed, this is a little like grabbing a hundred Scrabble tiles from some huge pile and expecting them to spell out this sentence. Ah, but such random grabs are then filtered into meaningful configurations by natural selection, Wade argues: genes producing a predisposition to capitalism or tribalism might be more useful in some populations than others. Setting aside the improbability of those particular genes existing in the first place, this idea relies on the assumption that every inheritable trait can be selected for, because it stems from genes “for” that trait. That’s precisely the fallacy that once supported eugenic arguments for the betterment of the human race: that we can breed out genes for criminality, stupidity, mendacity.
While it has been reassuring to watch Wade’s thesis be comprehensively dismantled (here and here and here, say) by scientists and other knowledgeable commentators, it’s hard not to contrast their response with that to James Watson’s claim in 2007 that the idea that all races share “equal powers of reason” is a delusion. Despite the fact that Watson adduced as “evidence” only the alleged experience of “people who have to deal with black employees”, he was defended as the victim of a witch-hunt by an “illiberal and intolerant thought police”. Even though it is hard to disentangle genuine prejudice from habitual liberal-baiting in Watson’s remarks, all we are really seeing here is one natural endpoint of the “genes for” and “instruction book” mentality underpinning the Human Genome Project that Watson helped establish and initially led.
The dark genome
The dispersed, “polygenic” nature of inheritable intelligence is likely to be the norm in genetics, at least for many traits we care about. Much the same applies to many inheritable medical conditions, such as schizophrenia and multiple sclerosis: like asthma, they seem to arise from the action of many, perhaps even hundreds, of genes, and there’s not one gene, or even a small number, that can be identified as the main culprits. This “missing heritability”, sometimes called the “dark matter” of the genome, is one of the biggest challenges to the promised personalized medicine of the post-genome era. But it should also be seen as challenging our understanding of genetics per se. Jones, who has been energetic about puncturing the worse misunderstandings of the “genes for” picture, admits that he wouldn’t now attempt to explain how genetics really works, in a manner akin to his brilliant The Language of the Genes (1994), because the field has got so damned complicated.
Yet the linguistic analogy – with genes as words and genomes as books – might remain a serviceable one, if only it were taken more seriously. Combing the genome for genes for many (not all) complex traits seems a little like analyzing Hamlet to look for the words in which Hamlet’s indecision resides. Sure, there’s a lot riding on the cluster “To be or not to be”, but excise it and his wavering persists. Meanwhile, “to” does a lot of other work in the play, and is in no meaningful sense an “indecisive Hamlet” word.
The irony is that a study like the latest “IQ genes” report, while showing yet again the inadequacy of the “gene for” picture, is likely to perpetuate it. As Jones has pointed out, such work has the unfortunate side-effect of feeding our fascination with the putative genetic basis of social problems such as discrimination or differences in educational achievement, about which we can do rather little, while distracting us from the often more significant socioeconomic causes, about which we could do a great deal.
Thursday, November 13, 2014
Friday, November 07, 2014
Who are you calling a journalist?
When from time to time I’m fortunate enough to be asked to give a talk at a scientific meeting in a country that requires a visa, I always anticipate a bit of wary quizzing.
“So which institution are you from, Dr Ball?”
“Well, I’m not.”
“So you’re writing about this meeting?”
“Well, I might, but I’m going to give a talk…”
[US version: Sardonic glance, which says “Who is this joker?”]
[Chinese version: “Whatever. We’re giving you a short-term journalist visa, pal.”]
It’s pretty much the only time I have to think about my professional status within the scientific community. I’m generally content to call myself a writer, often a “science writer”, but I don’t trouble too much about whether this merges into a kind of quasi-scientist role. Well, I suppose the other time is when I write a paper for the academic literature, and feel oddly exposed when the only thing I can write for my address is “25 Brenchley Grove SE23” [not really], without the shield of an institution. Otherwise I have no real reason to think about this stuff, not least because, with extremely rare exceptions (a spectacularly insecure Nobel laureate being one), scientists themselves seem supremely unconcerned about whether you are a “scientist”, “writer”, “journalist” or whatever – in my experience they are true to the egalitarian spirit of science in being glad to talk to you or listen to you without the need for any kind of label, so long as they are interested in what you have to say.
All this springs to mind not just because I’ve recently returned from speaking at a conference in China but because of the latest round in the spat between Richard Dawkins and E. O. Wilson. I have felt very little sympathy previously for the rather intemperate way that Dawkins has launched into Wilson for his support of group selection – an argument that Wilson makes in collaboration with Martin Nowak on the back of some serious mathematics. But Wilson now does himself no credit at all by dismissing Dawkins’ challenges on the ground that Richard is a “journalist” – “and journalists are people that report what the scientists have found.” For one thing, this is just a part of what science journalists do; they also provide context for and sometimes critique of what the scientists have found. They are not just PR monkeys. But it is patently absurd to call Richard a journalist, even though sometimes he does write journalistic pieces. We all know that he has not really conducted original research for many years now. We know that this is pretty much true too of various other scientists in academic positions whose main job now is the communication of science. And so what? To suggest that that activity disqualifies them as real scientists is not just silly but speaks of the kind of snobbish disdain for popularization that Carl Sagan long suffered from. I can’t believe for a moment that Wilson feels that disdain, since he is such a splendid popularizer himself, and so I can only suppose that this humane man had a moment of irritation that got the better of him. If he thinks Dawkins is wrong, he needs to say why, not to discount the arguments on the grounds that Richard doesn’t do research. (By the same token, of course, if other evolutionary biologists think Wilson is wrong , they shouldn’t be saying so by going round drumming up signatures for mass letters to Nature saying how he’s let the side down. Arguments from authority or weight of numbers are precisely what scientists are meant to eschew.)
I suppose one could argue, however, that Richard is only getting a taste of his own medicine. When he compiled the Oxford Book of Modern Science Writing, he didn’t even acknowledge the existence of scientifically trained people who write about science for a living. Rather, his choices were apparently made between “professional scientists” and “excursions into science by professional writers” (he excludes the latter). This implies that, if you’re not a “professional scientist” then you are a dilettante – a suggestion that I don’t take personally but which strikes me as spectacularly insulting to the truly great science writers such as James Gleick, Carl Zimmer, Deborah Blum, and, oh sorry guys, loads of others I should mention. The mighty Thomas Levenson saw this attitude off more comprehensively and persuasively than I ever could. Maybe it would do Richard no harm to join us for a bit. There’s no shame in it. After all, his writing has precisely the kind of writerly virtues that Robin McKie says in this Guardian science podcast (on the Royal Society Winton Book Prize) that he finds much more often in the works of professional writers than in those of scientists writing books about their pet topic.
Oh, and by the way: visa officials aren’t the only ones who insist that you’re only to be taken seriously if you have “Department of…” after your name. I know for a fact that this is the criterion for inclusion on Radio 4’s In Our Time too. But I suppose the folks making those choices are arts graduates – and while I love the humanities, I know how strongly the argument from authority still holds sway there.
“So which institution are you from, Dr Ball?”
“Well, I’m not.”
“So you’re writing about this meeting?”
“Well, I might, but I’m going to give a talk…”
[US version: Sardonic glance, which says “Who is this joker?”]
[Chinese version: “Whatever. We’re giving you a short-term journalist visa, pal.”]
It’s pretty much the only time I have to think about my professional status within the scientific community. I’m generally content to call myself a writer, often a “science writer”, but I don’t trouble too much about whether this merges into a kind of quasi-scientist role. Well, I suppose the other time is when I write a paper for the academic literature, and feel oddly exposed when the only thing I can write for my address is “25 Brenchley Grove SE23” [not really], without the shield of an institution. Otherwise I have no real reason to think about this stuff, not least because, with extremely rare exceptions (a spectacularly insecure Nobel laureate being one), scientists themselves seem supremely unconcerned about whether you are a “scientist”, “writer”, “journalist” or whatever – in my experience they are true to the egalitarian spirit of science in being glad to talk to you or listen to you without the need for any kind of label, so long as they are interested in what you have to say.
All this springs to mind not just because I’ve recently returned from speaking at a conference in China but because of the latest round in the spat between Richard Dawkins and E. O. Wilson. I have felt very little sympathy previously for the rather intemperate way that Dawkins has launched into Wilson for his support of group selection – an argument that Wilson makes in collaboration with Martin Nowak on the back of some serious mathematics. But Wilson now does himself no credit at all by dismissing Dawkins’ challenges on the ground that Richard is a “journalist” – “and journalists are people that report what the scientists have found.” For one thing, this is just a part of what science journalists do; they also provide context for and sometimes critique of what the scientists have found. They are not just PR monkeys. But it is patently absurd to call Richard a journalist, even though sometimes he does write journalistic pieces. We all know that he has not really conducted original research for many years now. We know that this is pretty much true too of various other scientists in academic positions whose main job now is the communication of science. And so what? To suggest that that activity disqualifies them as real scientists is not just silly but speaks of the kind of snobbish disdain for popularization that Carl Sagan long suffered from. I can’t believe for a moment that Wilson feels that disdain, since he is such a splendid popularizer himself, and so I can only suppose that this humane man had a moment of irritation that got the better of him. If he thinks Dawkins is wrong, he needs to say why, not to discount the arguments on the grounds that Richard doesn’t do research. (By the same token, of course, if other evolutionary biologists think Wilson is wrong , they shouldn’t be saying so by going round drumming up signatures for mass letters to Nature saying how he’s let the side down. Arguments from authority or weight of numbers are precisely what scientists are meant to eschew.)
I suppose one could argue, however, that Richard is only getting a taste of his own medicine. When he compiled the Oxford Book of Modern Science Writing, he didn’t even acknowledge the existence of scientifically trained people who write about science for a living. Rather, his choices were apparently made between “professional scientists” and “excursions into science by professional writers” (he excludes the latter). This implies that, if you’re not a “professional scientist” then you are a dilettante – a suggestion that I don’t take personally but which strikes me as spectacularly insulting to the truly great science writers such as James Gleick, Carl Zimmer, Deborah Blum, and, oh sorry guys, loads of others I should mention. The mighty Thomas Levenson saw this attitude off more comprehensively and persuasively than I ever could. Maybe it would do Richard no harm to join us for a bit. There’s no shame in it. After all, his writing has precisely the kind of writerly virtues that Robin McKie says in this Guardian science podcast (on the Royal Society Winton Book Prize) that he finds much more often in the works of professional writers than in those of scientists writing books about their pet topic.
Oh, and by the way: visa officials aren’t the only ones who insist that you’re only to be taken seriously if you have “Department of…” after your name. I know for a fact that this is the criterion for inclusion on Radio 4’s In Our Time too. But I suppose the folks making those choices are arts graduates – and while I love the humanities, I know how strongly the argument from authority still holds sway there.
The science of artificial olives
My Chemistry World Crucible column for November... And I really do want to give this a go one day.
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How would you like your soup, madam – one lump or two? If you ever had the chance (and financial resources) to dine at elBulli on the Catalonian Costa Brava before it closed in 2011, you’ll understand how soup can be served this way. The celebrity chef Ferran Adrià has worked for years to perfect the technique of spherification, a method of encapsulating liquid foods in an edible polymer skin. It is one of the most striking coups of molecular gastronomy – cooking based on advanced chemistry – and I am reliably informed that elBulli’s spherificated olives, made from puréed olive, were out of this world.
[Actually the recommendation, from the RSC’s Phil Robinson, deserves to be quoted in full: “The spherificated olives certainly were good. But the rabbit brain and sea anemone dish was surf and turf too far removed for my taste.”]
Spherification goes back a long way. It was invented in the 1940s and patented for the production of “artificial edible cherries”. Innovative chefs such as Hervé This, the doyen of molecular gastronomy, explored it in later decades. It uses sodium alginate, a natural food thickener extracted from brown seaweed, which is gelated from solution when exposed to calcium ions. The usual method is to place a dollop of the food ingredient, mixed with sodium alginate, into a bath of a calcium salt such as calcium lactate gluconate. As it gels, the blob is pulled into a sphere by surface tension.
Adrià came across the technique in 2003 and began at once to experiment with it, creating ravioli-like dishes from puréed pea and mango and varying the recipes to tune the texture of the gel. But in 2005 the “scientific department” of his restaurant came up with a new approach that turned the chemistry inside out. Adrià realized that the liquid core could be kept more fluid by allowing it to grow a thin skin within a solution of sodium alginate. In other words, instead of adding alginate droplets to a calcium bath, he began adding liquids naturally rich in calcium (or supplemented with it if necessary) into an alginate bath. Within just a few minutes of this reverse spherification, the droplets develop a membrane tough enough for them to be lifted out gently on a spoon. After rinsing in water, they’re ready to eat: one bite releases a flood of the flavoursome ingredients, whether it’s tomato soup, puréed strawberries or olives. It works for just about any liquid, and is a rare example of haute cuisine that you can do at home – Adrià even supplies kits with all the ingredients.
The basic process of gelation is no mystery. But the details haven’t been clear. Why is calcium alginate a gel whereas the sodium salt is soluble? And what effect does the chemistry of the encapsulated fluid have on the membrane? To answer such questions, Adrià is collaborating with biophysicist Christophe Chipot of the University of Illinois at Urbana-Champaign and a team at Nankai University in Tianjin, China. In their first foray they used molecular dynamics simulations to study the process (H. Fu et al., J. Phys. Chem. B 118, 11747 (2014)).
Since it’s not feasible either to investigate a full-sized hors d’oeuvre this way or to include the chemical complexity of puréed olive, the researchers have looked at nanospheres of representative liquids such as a hydrocarbon (dodecane), a fatty acid (oleic) and its sodium and calcium salts. Alginate is a polysaccharide, a somewhat random copolymer of two sugars, and in the simulations these polymers encapsulated the core droplets in a hydrogel matrix. With calcium ions present the alginate forms a well-defined membrane, but with sodium oleate as the core the membrane failed to cohere into a compact form. Evidently the calcium ions are essential. Why? The researchers find that, while both sodium and calcium ions are coordinated to electron-donating oxygen atoms in the alginate chains, the average coordination number for calcium is a little over 3, while that for sodium is about 2. This means that calcium ions are considerably better at cross-linking the polysaccharide chains by chelation and thereby stabilizing the membrane network – a conclusion supported by thermodynamic calculations of the binding free energies.
A pure hydrocarbon core doesn’t easily grow a stable membrane either, even with calcium ions present, since it can neither sequester the ions to its surface nor benefit from direct interactions with the alginate, for example by hydrogen bonding, so as to adsorb a coating that the calcium ions can then cross-link. That’s why, if you want to make a spherificated morsel with an oily filling, the researchers say that “some avant-garde cuisine techniques” are needed – as Adrià has apparently already discovered.
elBulli closed because of the massive losses it was incurring, despite typical dining costs of around $250 per head and an absurdly oversubscribed booking list. It’s not clear what will spring from it now. The elBullifoundation announces that the restaurant will be replaced with an “exhibition centre” to “help understand its historical and culinary evolution”, to archive the history of cooking generally, and to “provide facilities related to the process of creativity.” It all sounds mysteriously intriguing, but I suspect most visitors will be hoping that there’s a café attached.
Particle Fever: nearly all good
I finally got around to watching all of Particle Fever. It’s great, and makes me all the happier that Fabiola Gianotti will be the new director. I fully agree with Peter Woit that “if you want to get someone turned on to high energy particle physics, or just convince a young person that a career in science is an attractive idea, the CERN footage in this film should do the job better than anything I’ve seen from even the highly competent CERN press office.” I don’t withdraw my complaint about how the director has spoken about the role of the LHC in physics more generally, but that’s a minor quibble given what a splendid job he’s done.
But I was intrigued to discover this comment from Woit:
“As for the really bad idea, it’s the introduction of the multiverse into the theory part of the film. Kaplan is shown claiming that the multiverse predicts a 140 GeV Higgs, based on this paper of Yasunori Nomura and Lawrence Hall (who was Arkani-Hamed’s advisor). This is at a time when there were experimental hints of a 140 GeV Higgs. After they went away, and the mass came out at 125 GeV, the “prediction” is forgotten, but a long segment still has Arkani-Hamed going on about the CC and arguing for the multiverse. Just before this segment though, Dunford the experimentalist is shown Skyping with the filmmaker, warning them “Don’t listen to theorists”. At the film showing, Kaplan and Arkani-Hamed were there and answered questions at the end. One of the first questions (not from me…) was from an audience member who asked why they had put the material about the multiverse in the film, even though it had no real link to the Higgs or the LHC experiments. Arkani-Hamed admitted that the 140 Gev prediction was tenuous, there was no “sharp” link of the multiverse to the Higgs, and that no way is now known to get predictions out of the multiverse idea or test it. Kaplan explained that the intention was to make an “experiential” film, focusing on what theorists were talking about and thinking about, without getting into really trying to fully explain the scientific issues. The problem with this is that the film comes through as promoting the Dimopoulos/Arkani-Hamed view that no SUSY means a multiverse, without showing any challenge to such an argument.”
I’m no expert, to understate absurdly, but Woit is, and it does rather sound as though there was a little bit of an agenda here. After all, everyone loves a good multiverse. Or do they? Watch this space.
But I was intrigued to discover this comment from Woit:
“As for the really bad idea, it’s the introduction of the multiverse into the theory part of the film. Kaplan is shown claiming that the multiverse predicts a 140 GeV Higgs, based on this paper of Yasunori Nomura and Lawrence Hall (who was Arkani-Hamed’s advisor). This is at a time when there were experimental hints of a 140 GeV Higgs. After they went away, and the mass came out at 125 GeV, the “prediction” is forgotten, but a long segment still has Arkani-Hamed going on about the CC and arguing for the multiverse. Just before this segment though, Dunford the experimentalist is shown Skyping with the filmmaker, warning them “Don’t listen to theorists”. At the film showing, Kaplan and Arkani-Hamed were there and answered questions at the end. One of the first questions (not from me…) was from an audience member who asked why they had put the material about the multiverse in the film, even though it had no real link to the Higgs or the LHC experiments. Arkani-Hamed admitted that the 140 Gev prediction was tenuous, there was no “sharp” link of the multiverse to the Higgs, and that no way is now known to get predictions out of the multiverse idea or test it. Kaplan explained that the intention was to make an “experiential” film, focusing on what theorists were talking about and thinking about, without getting into really trying to fully explain the scientific issues. The problem with this is that the film comes through as promoting the Dimopoulos/Arkani-Hamed view that no SUSY means a multiverse, without showing any challenge to such an argument.”
I’m no expert, to understate absurdly, but Woit is, and it does rather sound as though there was a little bit of an agenda here. After all, everyone loves a good multiverse. Or do they? Watch this space.
Sunday, October 12, 2014
Mind control
Here's a pre-edited version of my piece for the Observer today, with a little bit more stuff still in it and some links. This was a great topic to research, and a bit disconcerting at times too.
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Be careful what you wish for. That’s what Joel, played by Jim Carrey, discovers in Charlie Kaufmann’s 2004 film Eternal Sunshine of the Spotless Mind, when he asks a memory-erasure company Lacuna Inc. to excise the recollections of a painful breakup from his mind. While the procedure is happening, Joel realizes that he doesn’t want every happy memory of the relationship to vanish, and seeks desperately to hold on to a few fragments.
The movie offers a metaphor for how we are defined by our memories, how poignant is both their recall and their loss, and how unreliable they can be. So what if Lacuna’s process is implausible? Just enjoy the allegory.
Except that selective memory erasure isn’t implausible at all. It’s already happening.
Researchers and clinicians are now using drugs to suppress the emotional impact of traumatic memories. They have been able to implant false memories in flies and mice, so that innocuous environments or smells seem to be “remembered” as threatening. They are showing that memory is not like an old celluloid film, fixed but fading; it is constantly being changed and updated, and can be edited and falsified with alarming ease.
“I see a world where we can reactivate any kind of memory we like, or erase unwanted memories”, says neuroscientist Steve Ramirez of the Massachusetts Institute of Technology. “I even see a world where editing memories is something of a reality. We’re living in a time where it’s possible to pluck questions from the tree of science fiction and ground them in experimental reality.” So be careful what you wish for.
But while it’s easy to weave capabilities like this into dystopian narratives, most of which the movies have already supplied – the authoritarian memory-manipulation of Total Recall, the mind-reading police state of Minority Report, the dream espionage of Inception – research on the manipulation of memory could offer tremendous benefits. Already, people suffering from post-traumatic stress disorder (PTSD), such as soldiers or victims of violent crime, have found relief from the pain of their dark memories through drugs that suppress the emotional associations. And the more we understand about how memories are stored and recalled, the closer we get to treatments for neurodegenerative conditions such as Alzheimer’s and other forms of dementia.
So there are good motivations for exploring the plasticity of memory – how it can be altered or erased. And while there are valid concerns about potential abuses, they aren’t so very different from those that any biomedical advance accrues. What seems more fundamentally unsettling, but also astonishing, about this work is what it tells us about us: how we construct our identity from our experience, and how our recollections of that experience can deceive us. The research, says Ramirez, has taught him “how unstable our identity can be.”
Best forgotten
Your whole being depends on memory in ways you probably take for granted. You see a tree, and recognize it as a tree, and know it is called “tree” and that it is a plant that grows. You know your language, your name, your loved ones. Few things are more devastating, to the individual and those close to them, than the loss of these everyday facts. As the memories fade, the person seems to fade with them. Christopher Nolan’s film Memento echoes the case of Henry Molaison, who, after a brain operation for epilepsy in the 1950s, lost the ability to record short-term memories. Each day his carers had to introduce themselves to him anew.
Molaison’s surgery removed a part of his brain called the hippocampus, giving a clue that this region is involved in short-term memory. Yet he remembered events and facts learnt long ago, and could be taught new ones, indicating that long-term memory is stored somewhere else. Using computer analogies for the brain is risky, but it’s reasonable here to compare our short-term memory with a computer’s ephemeral working memory or RAM, and the long-term memory with the hard drive that holds information more durably. While short-term memory is associated with the hippocampus, long-term memory is more distributed throughout the cortex. Some information is stored long-term, such as facts and events we experience repeatedly or that have an emotional association; other items vanish within hours. If you look up the phone number of a plumber, you’ll probably have forgotten it by tomorrow, but you may remember the phone number of your family home from childhood.
What exactly do we remember? Recall isn’t total – you might retain the key aspects of a significant event but not what day of the week it was, or what you were wearing, or exactly what was said. Your memories are a mixed bag: facts, feelings, sights, smells. Ramirez points out that, while Eternal Sunshine implies that all these features of a memory are bundled up and stored in specific neurons in a single location in the brain, in fact it’s now clear that different aspects are stored in different locations. The “facts”, sometimes called episodic memory, are filed in one place, the feelings in another (generally in a brain region called the amygdala). All the same, those components of the memory do each have specific addresses in the vast network of our billions of neurons. What’s more, these fragments remain linked and can be recalled together, so that the event we reconstruct in our heads is seamless, if incomplete. “Memory feels very cohesive, but in reality it’s a reconstructive process”, says Ramirez.
Given all this filtering and parceling out, it’s not surprising that memory is imperfect. “The fidelity of memory is very poor”, says psychologist Alain Brunet of McGill University in Montreal. “We think we remember exactly what happens, but research demonstrates that this is a fallacy.” It’s our need for a coherent narrative that misleads us: the brain elaborates and fills in gaps, and we can’t easily distinguish the “truth” from the invention. You don’t need fancy technologies to mess with memory – just telling someone they experienced something they didn’t, or showing them digitally manipulated photos, can be enough to seed a false conviction. That, much more than intentional falsehood, is why eye-witness accounts may be so unreliable and contradictory.
It gets worse. One of the most extraordinary findings of modern neuroscience, reported in 2000 by neurobiologist Joseph LeDoux and his colleagues at New York University, is that each time you remember something, you have to rebuild the memory again. LeDoux’s team reported that when rats were conditioned to associate a particular sound with mild electric shocks, so that they showed a “freezing” fear response when they heard the sound subsequently, this association could be broken by infusing the animals’ amygdala with a drug called anisomycin. The sound then no longer provoked fear – but only if the drug was administered within an hour or so of the memory being evoked. Anisomycin disrupts biochemical processes that create proteins, and the researchers figured that this protein manufacture was essential for restoring a memory after it has arisen. This is called reconsolidation: it starts a few minutes after recall, and takes a few hours to complete.
So those security questions asking you for the name of your first pet are even more bothersome than you thought, because each time you have to call up the answer (sorry if I just made you do it again), your brain then has to write the memory back into long-term storage. A computer analogy is again helpful. When we work on a file, the computer makes a copy of the stored version and we work on that – if the power is cut, we still have the original. But as Brunet explains, “When we remember something, we bring up the original file.” If we don’t write it back into the memory, it’s gone.
This rewriting process can, like repeated photocopying, degrade the memory a little. But LeDoux’s work showed that it also offers a window for manipulating the memory. When we call it up, we have the opportunity to change it. LeDoux found that a drug called propranolol can weaken the emotional impact of a memory without affecting the episodic content. This means that the effect of painful recollections causing PTSD can be softened. Propranolol is already known to be safe in humans: it is a beta blocker used to treat hypertension, and (tellingly) also to combat anxiety, because it blocks the action of the stress hormone epinephrine in the amygdala. A team at Harvard Medical School has recently discovered that xenon, the inert gas used as an anaesthetic, can also weaken the reconsolidation of fear memories in rats. An advantage of xenon over propranolol is that it gets in and out of the brain very quickly, taking about three minutes each way. If it works well for humans, says Edward Meloni of the Harvard team, “we envisage that patients could self-administer xenon immediately after experiencing a spontaneous intrusive traumatic memory, such as awakening from a nightmare.” The timing of the drug relative to reactivation of the trauma memory may, he says, be critical for blocking the reconsolidation process.
These techniques are now finding clinical use. Brunet uses propranolol to treat people with PTSD, including soldiers returned from active combat, rape victims and people who have suffered car crashes. “It’s amazingly simple,” he says. They give the patients a pill containing propranolol, and then about an hour later “we evoke the memory by having patients write it down and then read it out.” That’s often not easy for them, he says – but they manage it. The patients are then asked to continue reading the script regularly over the next several weeks. Gradually they find that its emotional impact fades, even though the facts are recalled clearly.
“After three or four weeks”, says Brunet, “our patients say things like ‘I feel like I’m smiling inside, because I feel like I’m reading someone else’s script – I’m no longer personally gripped by it.’” They might feel empathy with the descriptions of the terrible things that happened to this person – but that person no longer feels like them. No “talking cure” could do that so quickly and effectively, while conventional drug therapies only suppress the symptoms. “Psychiatry hasn’t cured a single patient in sixty years”, Brunet says.
These cases are extreme, but aren’t even difficult memories (perhaps especially those) part of what makes us who we are? Should we really want to get rid of them? Brunet is confident about giving these treatments to patients who are struggling with memories so awful that life becomes a torment. “We haven’t had a single person say ‘I miss those memories’”, he says. After all, there’s nothing unnatural about forgetting. “We are in part the sum of our memories, and it’s important to keep them”, Brunet says. “But forgetting is part of the human makeup too. We’re built to forget.”
Yet it’s not exactly forgetting. While propranolol and xenon can modify a memory by dampening its emotional impact, the memory remains: PTSD patients still recall “what happened”, and even the emotions are only reduced, not eliminated. We don’t yet really understand what it means to truly forget something. Is it ever really gone or just impossible to recall? And what happens when we learn to overcome fearful memories – say, letting go of a childhood fear of dogs as we figure that they’re mostly quite friendly? “Forgetting is fairly ill-defined”, says neuroscientist Scott Waddell at the University of Oxford. “Is there some interfering process that out-competes the original memory, or does the original memory disappear altogether?” Some research on flies suggests that forgetting isn’t just a matter of decay but an active process in which the old memory is taken apart. Animal experiments have also revealed the spontaneous re-emergence of memories after they were apparently eliminated by re-training, suggesting that memories don’t vanish but are just pushed aside. “It’s really not clear what is going on”, Waddell admits.
Looking into a fly’s head
That’s not so surprising, though, because it’s not fully understood how memory works in the first place. Waddell is trying to figure that out – by training fruit flies and literally looking into their brains. What makes flies so useful is that it’s easy to breed genetically modified strains, so that the role of specific genes in brain activity can be studied by manipulating or silencing them. And the fruit fly is big and complex enough to show sophisticated behavior, such as learning to associate a particular odour with a reward like sugar, while being simple enough to comprehend – it has around 100,000 neurons, compared to our many billions.
What’s more, a fruit fly’s brain is transparent enough to look right through it under the microscope, so that one can watch neural processing while the fly is alive. By attaching fluorescent molecules to particular neurons, Waddell can identify the neural circuitry linked to a particular memory. In his lab in Oxford he showed me an image of a real fly’s brain: a haze of bluish-coloured neurons, with bright green spots and filaments that are, in effect, a snapshot of a memory. The memory might be along the lines of “Ah, that smell – the last time I followed it, it led to something tasty.”
How do you find the relevant neurons among thousands of others? The key is that when neurons get active to form a memory, they advertise their state of busyness. They produce specific proteins, which can be tagged with other light-emitting proteins by genetic engineering of the respective genes. One approach is to inject benign viruses that stitch the light-emission genes right next to the gene for the protein you want to tag; another is to engineer particular cells to produce a foreign protein to which the fluorescent tags will bind. When these neurons get to work forming a memory, they light up. Ramirez compares it to the way lights in the windows of an office block at night betray the location of workers inside.
This ability to identify and target individual memories has enabled researchers like Waddell and Ramirez to manipulate them experimentally in, well, mind-boggling ways. Rather than just watching memories form by fluorescent tagging, they can use tags that act as light-activated switches to turn gene activity on or off with laser light directed down an optical fibre into the brain. This technique, called optogenetics, is driving a revolution in neuroscience, Ramirez says, because it gives researchers highly selective control over neural activity – enabling them in effect to stimulate or suppress particular thoughts and memories.
Waddell’s lab is not a good place to bring a banana for lunch. The fly store is packed with shelves of glass bottles, each full of flies feasting on a lump of sugar at the bottom. Every bottle is carefully labeled to identify the genetic strain of the insects it contains: which genes have been modified. But surely they get out from time to time, I wonder – and as if on cue, a fly buzzes past. Is that a problem? “They don’t survive for long on the outside,” Waddell reassures me.
Having spent the summer cursing the plague of flies gathering around the compost bin in the kitchen, I’m given fresh respect for these creatures when I inspect one under the microscope and see the bejeweled splendor of its red eyes. It’s only sleeping: you can anaesthetize fruit flies with a puff of carbon dioxide. That’s important for mapping neurons to memories in the microscope, because there’s not much going on in the mind of a dead fly.
These brain maps are now pretty comprehensive. We know, for example, which subset of neurons (about 2,000 in all) is involved in learning to recognize odours, and which neurons can give those smells good or bad associations. And thanks to optogenetics, researchers have been able to switch on some of these “aversive” neurons while flies smell a particular odour, so that they avoid it even though they have actually experienced nothing bad (such as shock treatment) in its presence – in other words, you might say, to stimulate a fictitious false memory. For a fly, it’s not obvious that we can call this “fear”, Waddell says, but “it’s certainly something they don’t like”. In the same way, by using molecular switches that are flipped with heat rather than light, Waddell and his colleagues were able to give flies good vibes about a particular smell. Flies display these preferences by choosing to go in particular directions when they are placed in little plastic mazes, some of them masterfully engineered with little gear-operated gates courtesy of the lab’s 3D printer.
Ramirez, working in a team at MIT led by Susumu Tonegawa, has practiced similar deceptions on mice. In an experiment in 2012 they created a fear memory in a mouse by putting it in a chamber where it experienced mild electric shocks to the feet. While this memory was being laid down, the researchers used optogenetic methods to make the corresponding neurons, located in the hippocampus, switchable with light. Then they put the mouse in a different chamber, where it seemed perfectly at ease. But when they reactivated the fear memory with light, the mouse froze: suddenly it had bad feelings about this place.
That’s not exactly implanting a false memory, however, but just reactivating a true one. To genuinely falsify a recollection, the researchers devised a more elaborate experiment. First, they placed a mouse in a chamber and labeled the neurons that recorded the memory of that place with optogenetic switches. Then the mouse was put in a different chamber and given mild shocks – but while these were delivered, the memory of the first chamber was triggered using light. When the mouse was then put back in the first chamber it froze. Its memory insisted, now without any artificial prompting, that the first chamber was a nasty place, even though nothing untoward had ever happened there. It is not too much to say that a false reality had been directly written into the mouse’s brain.
You must remember this
The problem with memory is often not so much that we totally forget something or recall it wrongly, but that we simply can’t find it even though we know it’s in there somewhere. What triggers memory recall? Why does a fly only seem to recall a food-related odour when it is hungry? Why do we feel fear only if we’re in actual danger, and not all the time? Indeed, it is the breakdown of these normal cues that produces PTSD, where the fear response gets triggered in inappropriate situations.
A good memory is largely about mastering this triggering process. Participants in memory competitions that involve memorizing long sequences of arbitrary numbers are advised to “hook” the information onto easily recalled images. A patient named Solomon Shereshevsky, studied in the early twentieth century by the neuropsychologist Alexander Luria, exploited his condition of synaesthesia – the crosstalk between different sensory experiences such as sound and colour – to tag information with colours, images, sounds or tastes so that he seemed able to remember everything he heard or read. Cases like this show that there is nothing implausible about Jorge Luis Borges’ fictional character Funes the Memorious, who forgets not the slightest detail of his life. We don’t forget because we run out of brain space, even if it sometimes feels like that.
Rather than constructing a complex system of mnemonics, perhaps it is possible simply to boost the strength of the memory as it is imprinted. “We know that emotionally arousing situations are more likely to be remembered than mundane ones”, LeDoux has explained. “A big part of the reason is that in significant situations chemicals called neuromodulators are released, and they enhance the memory storage process.” So memory sticks when the brain is aroused: emotional associations will do it, but so might exercise, or certain drugs. And because of reconsolidation, it seems possible to enhance memory after it has already been laid down. LeDoux has found that a chemical called isoproterenol has the opposite effect from propranolol on reconsolidation of memory in rats, making fear memories even stronger as they are rewritten into long-term storage in the amygdala. If it works for humans too, he speculates that the drug might help people who have “sluggish” memories.
Couldn’t we all do with a bit of that, though? Ramirez regards chemical memory enhancement as perfectly feasible in principle, and in fact there is already some evidence that caffeine can enhance long-term memory. But then what is considered fair play? No one quibbles about students going into an exam buoyed up by an espresso, but where do we draw the line?
Mind control
It’s hard to come up with extrapolations of these discoveries that are too far-fetched to be ruled out. You can tick off the movies one by one. The memory erasure of Eternal Sunshine is happening right now to some degree. And although so far we know only how to implant a false memory if it has actually been experienced in another context, as our understanding of the molecular and cellular encoding of memory improves Ramirez thinks it might be feasible to construct memories “from the ground up”, as in Total Recall or the implanted childhood recollections of the replicant Rachael in Blade Runner. As Rachael so poignantly found out, that’s the way to fake a whole identity.
If we know which neurons are associated with a particular memory, we can look into a brain and know what a person is thinking about, just by seeing which neurons are active: we can mind-read, as in Minority Report. “With sufficiently good technology you could do that”, Ramirez affirms. “It’s just a problem of technical limitations.” By the same token, we might reconstruct or intervene in dreams, as in Inception (Ramirez and colleagues called their false-memory experiment Project Inception). Decoding the thought processes of dreams is “a very trendy area, and one people are quite excited about”, says Waddell.
How about chips implanted in the brain to control neural activity, Matrix-style? Theodore Berger of the University of Southern California has implanted microchips in rats’ brains that can duplicate the role of the hippocampus in forming long-term memories, recording the neural signals involved and then playing them back. His most recent research shows that the same technique of mimicking neural signals seems to work in rhesus monkeys. The US Defense Advanced Research Projects Agency (DARPA) has two such memory-prosthesis projects afoot. One, called SUBNETS, aims to develop wireless implant devices that could treat PTSD and other combat-related disorders. The other, called RAM (Restoring Active Memories), seeks to restore memories lost through brain injury that are needed for specialized motor skills, such as how to drive a car or operate machinery. The details are under wraps, however, and it’s not clear how feasible it will be to record and replay specific memories. LeDoux professes that he can’t imagine how it could work, given that long-term memories aren’t stored in a single location. To stimulate all the right sites, says Waddell, “you’d have to make sure that your implantation was extremely specific – and I can’t see that happening.”
Ramirez says that it’s precisely because the future possibilities are so remarkable, and perhaps so unsettling, that “we’re starting this conversation today so that down the line we have the appropriate infrastructure.” Are we wise enough to know what we want to forget, to remember, or to think we remember? Do we risk blanking out formative, instructive and precious experiences, or finding ourselves one day being told, as Deckard tells Rachael in Blade Runner, “those aren’t your memories – they’re someone else’s”?
“The problems are not with the current research, but with the question of what we might be able to do in 10-15 years,” says Brunet. It’s one thing to bring in legislation to restrict abuses, just as we do for other biomedical technologies. But the hardest arguments might be about not what we prohibit but what we allow. Should individuals be allowed to edit their own memories or have false ones implanted? Ramirez is upbeat, but insists that the ethical choices are not for scientists alone to thrash out. “We all have some really big decisions ahead of us,” he says.
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Be careful what you wish for. That’s what Joel, played by Jim Carrey, discovers in Charlie Kaufmann’s 2004 film Eternal Sunshine of the Spotless Mind, when he asks a memory-erasure company Lacuna Inc. to excise the recollections of a painful breakup from his mind. While the procedure is happening, Joel realizes that he doesn’t want every happy memory of the relationship to vanish, and seeks desperately to hold on to a few fragments.
The movie offers a metaphor for how we are defined by our memories, how poignant is both their recall and their loss, and how unreliable they can be. So what if Lacuna’s process is implausible? Just enjoy the allegory.
Except that selective memory erasure isn’t implausible at all. It’s already happening.
Researchers and clinicians are now using drugs to suppress the emotional impact of traumatic memories. They have been able to implant false memories in flies and mice, so that innocuous environments or smells seem to be “remembered” as threatening. They are showing that memory is not like an old celluloid film, fixed but fading; it is constantly being changed and updated, and can be edited and falsified with alarming ease.
“I see a world where we can reactivate any kind of memory we like, or erase unwanted memories”, says neuroscientist Steve Ramirez of the Massachusetts Institute of Technology. “I even see a world where editing memories is something of a reality. We’re living in a time where it’s possible to pluck questions from the tree of science fiction and ground them in experimental reality.” So be careful what you wish for.
But while it’s easy to weave capabilities like this into dystopian narratives, most of which the movies have already supplied – the authoritarian memory-manipulation of Total Recall, the mind-reading police state of Minority Report, the dream espionage of Inception – research on the manipulation of memory could offer tremendous benefits. Already, people suffering from post-traumatic stress disorder (PTSD), such as soldiers or victims of violent crime, have found relief from the pain of their dark memories through drugs that suppress the emotional associations. And the more we understand about how memories are stored and recalled, the closer we get to treatments for neurodegenerative conditions such as Alzheimer’s and other forms of dementia.
So there are good motivations for exploring the plasticity of memory – how it can be altered or erased. And while there are valid concerns about potential abuses, they aren’t so very different from those that any biomedical advance accrues. What seems more fundamentally unsettling, but also astonishing, about this work is what it tells us about us: how we construct our identity from our experience, and how our recollections of that experience can deceive us. The research, says Ramirez, has taught him “how unstable our identity can be.”
Best forgotten
Your whole being depends on memory in ways you probably take for granted. You see a tree, and recognize it as a tree, and know it is called “tree” and that it is a plant that grows. You know your language, your name, your loved ones. Few things are more devastating, to the individual and those close to them, than the loss of these everyday facts. As the memories fade, the person seems to fade with them. Christopher Nolan’s film Memento echoes the case of Henry Molaison, who, after a brain operation for epilepsy in the 1950s, lost the ability to record short-term memories. Each day his carers had to introduce themselves to him anew.
Molaison’s surgery removed a part of his brain called the hippocampus, giving a clue that this region is involved in short-term memory. Yet he remembered events and facts learnt long ago, and could be taught new ones, indicating that long-term memory is stored somewhere else. Using computer analogies for the brain is risky, but it’s reasonable here to compare our short-term memory with a computer’s ephemeral working memory or RAM, and the long-term memory with the hard drive that holds information more durably. While short-term memory is associated with the hippocampus, long-term memory is more distributed throughout the cortex. Some information is stored long-term, such as facts and events we experience repeatedly or that have an emotional association; other items vanish within hours. If you look up the phone number of a plumber, you’ll probably have forgotten it by tomorrow, but you may remember the phone number of your family home from childhood.
What exactly do we remember? Recall isn’t total – you might retain the key aspects of a significant event but not what day of the week it was, or what you were wearing, or exactly what was said. Your memories are a mixed bag: facts, feelings, sights, smells. Ramirez points out that, while Eternal Sunshine implies that all these features of a memory are bundled up and stored in specific neurons in a single location in the brain, in fact it’s now clear that different aspects are stored in different locations. The “facts”, sometimes called episodic memory, are filed in one place, the feelings in another (generally in a brain region called the amygdala). All the same, those components of the memory do each have specific addresses in the vast network of our billions of neurons. What’s more, these fragments remain linked and can be recalled together, so that the event we reconstruct in our heads is seamless, if incomplete. “Memory feels very cohesive, but in reality it’s a reconstructive process”, says Ramirez.
Given all this filtering and parceling out, it’s not surprising that memory is imperfect. “The fidelity of memory is very poor”, says psychologist Alain Brunet of McGill University in Montreal. “We think we remember exactly what happens, but research demonstrates that this is a fallacy.” It’s our need for a coherent narrative that misleads us: the brain elaborates and fills in gaps, and we can’t easily distinguish the “truth” from the invention. You don’t need fancy technologies to mess with memory – just telling someone they experienced something they didn’t, or showing them digitally manipulated photos, can be enough to seed a false conviction. That, much more than intentional falsehood, is why eye-witness accounts may be so unreliable and contradictory.
It gets worse. One of the most extraordinary findings of modern neuroscience, reported in 2000 by neurobiologist Joseph LeDoux and his colleagues at New York University, is that each time you remember something, you have to rebuild the memory again. LeDoux’s team reported that when rats were conditioned to associate a particular sound with mild electric shocks, so that they showed a “freezing” fear response when they heard the sound subsequently, this association could be broken by infusing the animals’ amygdala with a drug called anisomycin. The sound then no longer provoked fear – but only if the drug was administered within an hour or so of the memory being evoked. Anisomycin disrupts biochemical processes that create proteins, and the researchers figured that this protein manufacture was essential for restoring a memory after it has arisen. This is called reconsolidation: it starts a few minutes after recall, and takes a few hours to complete.
So those security questions asking you for the name of your first pet are even more bothersome than you thought, because each time you have to call up the answer (sorry if I just made you do it again), your brain then has to write the memory back into long-term storage. A computer analogy is again helpful. When we work on a file, the computer makes a copy of the stored version and we work on that – if the power is cut, we still have the original. But as Brunet explains, “When we remember something, we bring up the original file.” If we don’t write it back into the memory, it’s gone.
This rewriting process can, like repeated photocopying, degrade the memory a little. But LeDoux’s work showed that it also offers a window for manipulating the memory. When we call it up, we have the opportunity to change it. LeDoux found that a drug called propranolol can weaken the emotional impact of a memory without affecting the episodic content. This means that the effect of painful recollections causing PTSD can be softened. Propranolol is already known to be safe in humans: it is a beta blocker used to treat hypertension, and (tellingly) also to combat anxiety, because it blocks the action of the stress hormone epinephrine in the amygdala. A team at Harvard Medical School has recently discovered that xenon, the inert gas used as an anaesthetic, can also weaken the reconsolidation of fear memories in rats. An advantage of xenon over propranolol is that it gets in and out of the brain very quickly, taking about three minutes each way. If it works well for humans, says Edward Meloni of the Harvard team, “we envisage that patients could self-administer xenon immediately after experiencing a spontaneous intrusive traumatic memory, such as awakening from a nightmare.” The timing of the drug relative to reactivation of the trauma memory may, he says, be critical for blocking the reconsolidation process.
These techniques are now finding clinical use. Brunet uses propranolol to treat people with PTSD, including soldiers returned from active combat, rape victims and people who have suffered car crashes. “It’s amazingly simple,” he says. They give the patients a pill containing propranolol, and then about an hour later “we evoke the memory by having patients write it down and then read it out.” That’s often not easy for them, he says – but they manage it. The patients are then asked to continue reading the script regularly over the next several weeks. Gradually they find that its emotional impact fades, even though the facts are recalled clearly.
“After three or four weeks”, says Brunet, “our patients say things like ‘I feel like I’m smiling inside, because I feel like I’m reading someone else’s script – I’m no longer personally gripped by it.’” They might feel empathy with the descriptions of the terrible things that happened to this person – but that person no longer feels like them. No “talking cure” could do that so quickly and effectively, while conventional drug therapies only suppress the symptoms. “Psychiatry hasn’t cured a single patient in sixty years”, Brunet says.
These cases are extreme, but aren’t even difficult memories (perhaps especially those) part of what makes us who we are? Should we really want to get rid of them? Brunet is confident about giving these treatments to patients who are struggling with memories so awful that life becomes a torment. “We haven’t had a single person say ‘I miss those memories’”, he says. After all, there’s nothing unnatural about forgetting. “We are in part the sum of our memories, and it’s important to keep them”, Brunet says. “But forgetting is part of the human makeup too. We’re built to forget.”
Yet it’s not exactly forgetting. While propranolol and xenon can modify a memory by dampening its emotional impact, the memory remains: PTSD patients still recall “what happened”, and even the emotions are only reduced, not eliminated. We don’t yet really understand what it means to truly forget something. Is it ever really gone or just impossible to recall? And what happens when we learn to overcome fearful memories – say, letting go of a childhood fear of dogs as we figure that they’re mostly quite friendly? “Forgetting is fairly ill-defined”, says neuroscientist Scott Waddell at the University of Oxford. “Is there some interfering process that out-competes the original memory, or does the original memory disappear altogether?” Some research on flies suggests that forgetting isn’t just a matter of decay but an active process in which the old memory is taken apart. Animal experiments have also revealed the spontaneous re-emergence of memories after they were apparently eliminated by re-training, suggesting that memories don’t vanish but are just pushed aside. “It’s really not clear what is going on”, Waddell admits.
Looking into a fly’s head
That’s not so surprising, though, because it’s not fully understood how memory works in the first place. Waddell is trying to figure that out – by training fruit flies and literally looking into their brains. What makes flies so useful is that it’s easy to breed genetically modified strains, so that the role of specific genes in brain activity can be studied by manipulating or silencing them. And the fruit fly is big and complex enough to show sophisticated behavior, such as learning to associate a particular odour with a reward like sugar, while being simple enough to comprehend – it has around 100,000 neurons, compared to our many billions.
What’s more, a fruit fly’s brain is transparent enough to look right through it under the microscope, so that one can watch neural processing while the fly is alive. By attaching fluorescent molecules to particular neurons, Waddell can identify the neural circuitry linked to a particular memory. In his lab in Oxford he showed me an image of a real fly’s brain: a haze of bluish-coloured neurons, with bright green spots and filaments that are, in effect, a snapshot of a memory. The memory might be along the lines of “Ah, that smell – the last time I followed it, it led to something tasty.”
How do you find the relevant neurons among thousands of others? The key is that when neurons get active to form a memory, they advertise their state of busyness. They produce specific proteins, which can be tagged with other light-emitting proteins by genetic engineering of the respective genes. One approach is to inject benign viruses that stitch the light-emission genes right next to the gene for the protein you want to tag; another is to engineer particular cells to produce a foreign protein to which the fluorescent tags will bind. When these neurons get to work forming a memory, they light up. Ramirez compares it to the way lights in the windows of an office block at night betray the location of workers inside.
This ability to identify and target individual memories has enabled researchers like Waddell and Ramirez to manipulate them experimentally in, well, mind-boggling ways. Rather than just watching memories form by fluorescent tagging, they can use tags that act as light-activated switches to turn gene activity on or off with laser light directed down an optical fibre into the brain. This technique, called optogenetics, is driving a revolution in neuroscience, Ramirez says, because it gives researchers highly selective control over neural activity – enabling them in effect to stimulate or suppress particular thoughts and memories.
Waddell’s lab is not a good place to bring a banana for lunch. The fly store is packed with shelves of glass bottles, each full of flies feasting on a lump of sugar at the bottom. Every bottle is carefully labeled to identify the genetic strain of the insects it contains: which genes have been modified. But surely they get out from time to time, I wonder – and as if on cue, a fly buzzes past. Is that a problem? “They don’t survive for long on the outside,” Waddell reassures me.
Having spent the summer cursing the plague of flies gathering around the compost bin in the kitchen, I’m given fresh respect for these creatures when I inspect one under the microscope and see the bejeweled splendor of its red eyes. It’s only sleeping: you can anaesthetize fruit flies with a puff of carbon dioxide. That’s important for mapping neurons to memories in the microscope, because there’s not much going on in the mind of a dead fly.
These brain maps are now pretty comprehensive. We know, for example, which subset of neurons (about 2,000 in all) is involved in learning to recognize odours, and which neurons can give those smells good or bad associations. And thanks to optogenetics, researchers have been able to switch on some of these “aversive” neurons while flies smell a particular odour, so that they avoid it even though they have actually experienced nothing bad (such as shock treatment) in its presence – in other words, you might say, to stimulate a fictitious false memory. For a fly, it’s not obvious that we can call this “fear”, Waddell says, but “it’s certainly something they don’t like”. In the same way, by using molecular switches that are flipped with heat rather than light, Waddell and his colleagues were able to give flies good vibes about a particular smell. Flies display these preferences by choosing to go in particular directions when they are placed in little plastic mazes, some of them masterfully engineered with little gear-operated gates courtesy of the lab’s 3D printer.
Ramirez, working in a team at MIT led by Susumu Tonegawa, has practiced similar deceptions on mice. In an experiment in 2012 they created a fear memory in a mouse by putting it in a chamber where it experienced mild electric shocks to the feet. While this memory was being laid down, the researchers used optogenetic methods to make the corresponding neurons, located in the hippocampus, switchable with light. Then they put the mouse in a different chamber, where it seemed perfectly at ease. But when they reactivated the fear memory with light, the mouse froze: suddenly it had bad feelings about this place.
That’s not exactly implanting a false memory, however, but just reactivating a true one. To genuinely falsify a recollection, the researchers devised a more elaborate experiment. First, they placed a mouse in a chamber and labeled the neurons that recorded the memory of that place with optogenetic switches. Then the mouse was put in a different chamber and given mild shocks – but while these were delivered, the memory of the first chamber was triggered using light. When the mouse was then put back in the first chamber it froze. Its memory insisted, now without any artificial prompting, that the first chamber was a nasty place, even though nothing untoward had ever happened there. It is not too much to say that a false reality had been directly written into the mouse’s brain.
You must remember this
The problem with memory is often not so much that we totally forget something or recall it wrongly, but that we simply can’t find it even though we know it’s in there somewhere. What triggers memory recall? Why does a fly only seem to recall a food-related odour when it is hungry? Why do we feel fear only if we’re in actual danger, and not all the time? Indeed, it is the breakdown of these normal cues that produces PTSD, where the fear response gets triggered in inappropriate situations.
A good memory is largely about mastering this triggering process. Participants in memory competitions that involve memorizing long sequences of arbitrary numbers are advised to “hook” the information onto easily recalled images. A patient named Solomon Shereshevsky, studied in the early twentieth century by the neuropsychologist Alexander Luria, exploited his condition of synaesthesia – the crosstalk between different sensory experiences such as sound and colour – to tag information with colours, images, sounds or tastes so that he seemed able to remember everything he heard or read. Cases like this show that there is nothing implausible about Jorge Luis Borges’ fictional character Funes the Memorious, who forgets not the slightest detail of his life. We don’t forget because we run out of brain space, even if it sometimes feels like that.
Rather than constructing a complex system of mnemonics, perhaps it is possible simply to boost the strength of the memory as it is imprinted. “We know that emotionally arousing situations are more likely to be remembered than mundane ones”, LeDoux has explained. “A big part of the reason is that in significant situations chemicals called neuromodulators are released, and they enhance the memory storage process.” So memory sticks when the brain is aroused: emotional associations will do it, but so might exercise, or certain drugs. And because of reconsolidation, it seems possible to enhance memory after it has already been laid down. LeDoux has found that a chemical called isoproterenol has the opposite effect from propranolol on reconsolidation of memory in rats, making fear memories even stronger as they are rewritten into long-term storage in the amygdala. If it works for humans too, he speculates that the drug might help people who have “sluggish” memories.
Couldn’t we all do with a bit of that, though? Ramirez regards chemical memory enhancement as perfectly feasible in principle, and in fact there is already some evidence that caffeine can enhance long-term memory. But then what is considered fair play? No one quibbles about students going into an exam buoyed up by an espresso, but where do we draw the line?
Mind control
It’s hard to come up with extrapolations of these discoveries that are too far-fetched to be ruled out. You can tick off the movies one by one. The memory erasure of Eternal Sunshine is happening right now to some degree. And although so far we know only how to implant a false memory if it has actually been experienced in another context, as our understanding of the molecular and cellular encoding of memory improves Ramirez thinks it might be feasible to construct memories “from the ground up”, as in Total Recall or the implanted childhood recollections of the replicant Rachael in Blade Runner. As Rachael so poignantly found out, that’s the way to fake a whole identity.
If we know which neurons are associated with a particular memory, we can look into a brain and know what a person is thinking about, just by seeing which neurons are active: we can mind-read, as in Minority Report. “With sufficiently good technology you could do that”, Ramirez affirms. “It’s just a problem of technical limitations.” By the same token, we might reconstruct or intervene in dreams, as in Inception (Ramirez and colleagues called their false-memory experiment Project Inception). Decoding the thought processes of dreams is “a very trendy area, and one people are quite excited about”, says Waddell.
How about chips implanted in the brain to control neural activity, Matrix-style? Theodore Berger of the University of Southern California has implanted microchips in rats’ brains that can duplicate the role of the hippocampus in forming long-term memories, recording the neural signals involved and then playing them back. His most recent research shows that the same technique of mimicking neural signals seems to work in rhesus monkeys. The US Defense Advanced Research Projects Agency (DARPA) has two such memory-prosthesis projects afoot. One, called SUBNETS, aims to develop wireless implant devices that could treat PTSD and other combat-related disorders. The other, called RAM (Restoring Active Memories), seeks to restore memories lost through brain injury that are needed for specialized motor skills, such as how to drive a car or operate machinery. The details are under wraps, however, and it’s not clear how feasible it will be to record and replay specific memories. LeDoux professes that he can’t imagine how it could work, given that long-term memories aren’t stored in a single location. To stimulate all the right sites, says Waddell, “you’d have to make sure that your implantation was extremely specific – and I can’t see that happening.”
Ramirez says that it’s precisely because the future possibilities are so remarkable, and perhaps so unsettling, that “we’re starting this conversation today so that down the line we have the appropriate infrastructure.” Are we wise enough to know what we want to forget, to remember, or to think we remember? Do we risk blanking out formative, instructive and precious experiences, or finding ourselves one day being told, as Deckard tells Rachael in Blade Runner, “those aren’t your memories – they’re someone else’s”?
“The problems are not with the current research, but with the question of what we might be able to do in 10-15 years,” says Brunet. It’s one thing to bring in legislation to restrict abuses, just as we do for other biomedical technologies. But the hardest arguments might be about not what we prohibit but what we allow. Should individuals be allowed to edit their own memories or have false ones implanted? Ramirez is upbeat, but insists that the ethical choices are not for scientists alone to thrash out. “We all have some really big decisions ahead of us,” he says.
Thursday, October 09, 2014
Do we tell the right stories about evolution?
There’s a super discussion on evolutionary theory in Nature this week. It’s prompted by the views of Kevin Laland at St Andrews, who has been arguing for some time that the traditional “evolutionary synthesis” needs to be extended beyond its narrow focus on genetics. In response, Gregory Wray at Duke University and others accuse Laland et al. of presenting a caricature of evolutionary biology and of ignoring all the work that is already being done on the issues Laland highlights.
It all sounds remarkably like the response I got to my article in Nature a couple of years back, which was suggesting that, not only is there much we still don’t understand about the way evolution happens at the molecular/genetic level but that the question of how genetic inheritance works seems if anything to be less rather than more clear in the post-genomic era. That too led some biologists to respond in much the same way: No, all is well. (The well-known fact that rules of academic courtesy don’t apply towards “journalists” meant that one or two didn’t quite phrase it that way. You get used to it.)
I guess you might expect, in the light of this, that I’d side with Laland et al. But in fact it looks to me as though Wray et al. have a perfectly valid case. After all, my article was formulated after speaking to several evolutionary biologists – and ones who sit well within what could be considered the mainstream. In particular, I think they are right to imply that the diverse mechanisms of evolutionary change known today are ones that, if Darwin didn’t already suspect, would be welcomed avidly by him.
The real source of the argument, it seems to me, is expressed right at the outset by Laland et al.: “mainstream evolutionary theory has come to focus almost exclusively on genetic inheritance and processes that change gene frequencies”. I’m not sure that this is true, although for good reason this is certainly a major focus – perhaps the major one – of the field. Wray et al. regard this as a caricature, but I think that what Laland et al. are complaining about here is what I wanted to highlight too: not so much the way most evolutionary biologists think, but how evolutionary biology is perceived from the outside. Part of the reason for that predominant “popular” focus on genes is due (ironically, given what it is actually revealing) to the genomics revolution itself, not least because we were promised that this was going to answer every question about who we are and where we came from. But of course, the popular notion that evolution is simply a process of natural selection among genes was well in place before the industrial-scale sequencing of genomes – and one doesn’t have to look too hard to find the origins of that view. As Wray et al. rightly say, the basic processes that produce evolutionary change are several-fold: natural selection, drift, mutation, recombination and gene flow. Things like phenotypic plasticity add fascinating perspectives to this, and my own suspicion is that an awful lot will become clearer once we have tools for grappling with the complexities of gene regulatory networks. There doesn’t seem to be a huge amount of argument about this. But attempts to communicate much beyond a simple equation of evolution with natural selection at the genetic level have been few and far between.
And some of the responses to my article made it clear that this is sometimes a conscious decision. Take the view of Paul Griffith, philosopher of science at the University of Sydney. According to ABC News,
“While simplistic communication about genetics can be used to hype the importance of research, and it can encourage the impression that genes determine everything, Professor Griffiths said he does not believe the answer is to communicate more complexity.”
Then there’s “science communication academic” Joan Leach from The University of Queensland, who apparently “agrees the average member of the public is not going to be that interested in the complexity of genetics, unless its relevant to an issue that they care about.” The ABC story goes on:
"Is there a problem that we need to know about here?" Dr Leach said in response to Dr Ball's article. "There are dangers in telling the simple story, but he hasn't spelt out the advantages of embracing complexity in public communication."
Sorry plebs, you’re too dumb to be told the truth – you’ll have to make do with the simplistic stories we told many decades ago.
It all sounds remarkably like the response I got to my article in Nature a couple of years back, which was suggesting that, not only is there much we still don’t understand about the way evolution happens at the molecular/genetic level but that the question of how genetic inheritance works seems if anything to be less rather than more clear in the post-genomic era. That too led some biologists to respond in much the same way: No, all is well. (The well-known fact that rules of academic courtesy don’t apply towards “journalists” meant that one or two didn’t quite phrase it that way. You get used to it.)
I guess you might expect, in the light of this, that I’d side with Laland et al. But in fact it looks to me as though Wray et al. have a perfectly valid case. After all, my article was formulated after speaking to several evolutionary biologists – and ones who sit well within what could be considered the mainstream. In particular, I think they are right to imply that the diverse mechanisms of evolutionary change known today are ones that, if Darwin didn’t already suspect, would be welcomed avidly by him.
The real source of the argument, it seems to me, is expressed right at the outset by Laland et al.: “mainstream evolutionary theory has come to focus almost exclusively on genetic inheritance and processes that change gene frequencies”. I’m not sure that this is true, although for good reason this is certainly a major focus – perhaps the major one – of the field. Wray et al. regard this as a caricature, but I think that what Laland et al. are complaining about here is what I wanted to highlight too: not so much the way most evolutionary biologists think, but how evolutionary biology is perceived from the outside. Part of the reason for that predominant “popular” focus on genes is due (ironically, given what it is actually revealing) to the genomics revolution itself, not least because we were promised that this was going to answer every question about who we are and where we came from. But of course, the popular notion that evolution is simply a process of natural selection among genes was well in place before the industrial-scale sequencing of genomes – and one doesn’t have to look too hard to find the origins of that view. As Wray et al. rightly say, the basic processes that produce evolutionary change are several-fold: natural selection, drift, mutation, recombination and gene flow. Things like phenotypic plasticity add fascinating perspectives to this, and my own suspicion is that an awful lot will become clearer once we have tools for grappling with the complexities of gene regulatory networks. There doesn’t seem to be a huge amount of argument about this. But attempts to communicate much beyond a simple equation of evolution with natural selection at the genetic level have been few and far between.
And some of the responses to my article made it clear that this is sometimes a conscious decision. Take the view of Paul Griffith, philosopher of science at the University of Sydney. According to ABC News,
“While simplistic communication about genetics can be used to hype the importance of research, and it can encourage the impression that genes determine everything, Professor Griffiths said he does not believe the answer is to communicate more complexity.”
Then there’s “science communication academic” Joan Leach from The University of Queensland, who apparently “agrees the average member of the public is not going to be that interested in the complexity of genetics, unless its relevant to an issue that they care about.” The ABC story goes on:
"Is there a problem that we need to know about here?" Dr Leach said in response to Dr Ball's article. "There are dangers in telling the simple story, but he hasn't spelt out the advantages of embracing complexity in public communication."
Sorry plebs, you’re too dumb to be told the truth – you’ll have to make do with the simplistic stories we told many decades ago.
A tale of many electrons
In what I hope might be a timely occasion with Nobel-fever in the air, here is my leader for the latest issue of Nature Materials. This past decision was a nice one for physics, condensed matter and materials – although curiously it was a chemistry prize.
______________________________________________________________________
Density functional theory, invented half a century ago, now supplies one of the most convenient and popular shortcuts for dealing with systems of many electrons. It was born in a fertile period when theoretical physics stretched from abstruse quantum field theory to practical electrical engineering.
It’s often pointed out that quantum theory is not just a source of counter-intuitive mystery but also an extraordinarily effective intellectual foundation for engineering. It supplies the theoretical basis for the transistor and superconductor, for understanding molecular interactions relevant from mineralogy to biology, and for describing the basic properties of all matter, from superhard alloys to high-energy plasmas. But popular accounts of quantum physics rarely pay more than lip service to this utilitarian virtue – there is little discussion of what it took to turn the ideas of Bohr, Heisenberg and Schrödinger into a theory that works at an everyday level.
One of the milestones in that endeavour occurred 50 years ago, when Pierre Hohenberg and Walter Kohn published a paper [1] that laid the foundations of density functional theory (DFT). This provided a tool for transforming the fiendishly complicated Schrödinger equation of a many-body system such as the atomic lattice of a solid into a mathematically tractable problem that enables the prediction of properties such as structure and electrical conductivity. The milieu in which this advance was formulated was rich and fertile, and from the distance of five decades it is hard not to idealize it as a golden age in which scientists could still see through the walls that now threaten to isolate disciplines. Kohn, exiled from his native Austria as a young Jewish boy during the Nazi era and educated in Canada, was located at the heart of this nexus. Schooled in quantum physics by Julian Schwinger at Harvard amidst peers including Philip Anderson, Rolf Landauer and Joaquin Luttinger, he was also familiar with the challenges of tangible materials systems such as semiconductors and alloys. In the mid-1950s Kohn worked as a consultant at Bell Labs, where the work of John Bardeen, Walter Brattain and William Shockley on transistors a few years earlier had generated a focus on the solid-state theory of semiconductors. And his ground-breaking paper with Hohenberg came from research on alloys at the Ecole Normale Supérieure in Paris, hosted by Philippe Nozières.
Now that DFT is so familiar a technique, used not only to understand electronic structures of molecules and materials but also as a semi-classical approach for studying the atomic structures of fluids, it is easy to forget what a bold hypothesis its inception required. In principle one may write the electron density n(r) of an N-electron system as the integral over space of the N-electron wavefunction, and then to use this to calculate the total energy of the system as a functional of n(r) and the potential energy v(r) of each electron interacting with all the fixed nuclei. (A functional here is a “function of a function” – the energy is a function of the function v(r), say.) Then one could do the calculation by invoking some approximation for the N-electron wavefunction. But Kohn inverted the idea: what if you didn’t start from the complicated N-body wavefunction, but just from the spatially varying electron density n(r)? That’s to say, maybe the external potential v(r), and thus the total energy (for the ground state of the system), depend only on the equilibrium n(r)? Then, that density function is all you needed to know. As Andrew Zangwill puts it in a recent commentary on Kohn’s career [2], “This was a deep question. Walter realized he wasn’t doing alloy theory any more.”
Kohn figured out a proof of this remarkable conjecture, but it seemed so simple that he couldn’t believe it hadn’t been noticed before. So he asked Hohenberg, a post-doc in Nozières’ lab, to help. Together the pair formulated a rigorous proof of the conjecture for the case of an inhomogeneous electron gas; since their 1964 paper, several other proofs have been found. That paper was formal and understated to the point of desiccation, and one needed to pay it close attention to see how remarkable the result was. The initial response was muted, and Hohenberg moved subsequently into other areas, such as hydrodynamics, phase transitions and pattern formation.
Kohn, however, went on to develop the idea into a practical method for calculating the electronic ground states of molecules and solids, working in particular with Hong Kong-born postdoc Lu-Jeu Sham. Their crucial paper3 was much more explicit about the potential of this approach as an approximation for calculating real materials properties of solids, such as cohesive energies and elastic constants, from quantum principles. It is now one of the most highly cited papers in all of physics, but was an example of a “sleeper”: still the community took some time to wake up to what was on offer. Not until the work of John Pople in the early 1990s did chemists begin to appreciate that DFT could offer a simple and convenient way to calculate electronic structures. It was that work which led to the 1998 Nobel prize in chemistry for Pople and Kohn – incongruous for someone so immersed in physics.
Zangwill argues that DFT defies the common belief that important theories reflect the Zeitgeist: it was an idea that was not in the air at all in the 1960s, and, says Zangwill, “might be unknown today if Kohn had not created it in the mid-1960s.” Clearly that’s impossible to prove. But there’s no mistaking the debt that materials and molecular sciences owe to Kohn’s insight, and so if Zangwill is right, all the more reason to ask if we still create the right sort of environments for such fertile ideas to germinate.
1. Hohenberg, P. & Kohn, W. Phys. Rev. 136, B864-871 (1964).
2. Zangwill, A., http://www.arxiv.org/abs/1403.5164 (2014).
3. Kohn, W. & Sham, L. J. Phys. Rev. 140, A1133-1138 (1965).
______________________________________________________________________
Density functional theory, invented half a century ago, now supplies one of the most convenient and popular shortcuts for dealing with systems of many electrons. It was born in a fertile period when theoretical physics stretched from abstruse quantum field theory to practical electrical engineering.
It’s often pointed out that quantum theory is not just a source of counter-intuitive mystery but also an extraordinarily effective intellectual foundation for engineering. It supplies the theoretical basis for the transistor and superconductor, for understanding molecular interactions relevant from mineralogy to biology, and for describing the basic properties of all matter, from superhard alloys to high-energy plasmas. But popular accounts of quantum physics rarely pay more than lip service to this utilitarian virtue – there is little discussion of what it took to turn the ideas of Bohr, Heisenberg and Schrödinger into a theory that works at an everyday level.
One of the milestones in that endeavour occurred 50 years ago, when Pierre Hohenberg and Walter Kohn published a paper [1] that laid the foundations of density functional theory (DFT). This provided a tool for transforming the fiendishly complicated Schrödinger equation of a many-body system such as the atomic lattice of a solid into a mathematically tractable problem that enables the prediction of properties such as structure and electrical conductivity. The milieu in which this advance was formulated was rich and fertile, and from the distance of five decades it is hard not to idealize it as a golden age in which scientists could still see through the walls that now threaten to isolate disciplines. Kohn, exiled from his native Austria as a young Jewish boy during the Nazi era and educated in Canada, was located at the heart of this nexus. Schooled in quantum physics by Julian Schwinger at Harvard amidst peers including Philip Anderson, Rolf Landauer and Joaquin Luttinger, he was also familiar with the challenges of tangible materials systems such as semiconductors and alloys. In the mid-1950s Kohn worked as a consultant at Bell Labs, where the work of John Bardeen, Walter Brattain and William Shockley on transistors a few years earlier had generated a focus on the solid-state theory of semiconductors. And his ground-breaking paper with Hohenberg came from research on alloys at the Ecole Normale Supérieure in Paris, hosted by Philippe Nozières.
Now that DFT is so familiar a technique, used not only to understand electronic structures of molecules and materials but also as a semi-classical approach for studying the atomic structures of fluids, it is easy to forget what a bold hypothesis its inception required. In principle one may write the electron density n(r) of an N-electron system as the integral over space of the N-electron wavefunction, and then to use this to calculate the total energy of the system as a functional of n(r) and the potential energy v(r) of each electron interacting with all the fixed nuclei. (A functional here is a “function of a function” – the energy is a function of the function v(r), say.) Then one could do the calculation by invoking some approximation for the N-electron wavefunction. But Kohn inverted the idea: what if you didn’t start from the complicated N-body wavefunction, but just from the spatially varying electron density n(r)? That’s to say, maybe the external potential v(r), and thus the total energy (for the ground state of the system), depend only on the equilibrium n(r)? Then, that density function is all you needed to know. As Andrew Zangwill puts it in a recent commentary on Kohn’s career [2], “This was a deep question. Walter realized he wasn’t doing alloy theory any more.”
Kohn figured out a proof of this remarkable conjecture, but it seemed so simple that he couldn’t believe it hadn’t been noticed before. So he asked Hohenberg, a post-doc in Nozières’ lab, to help. Together the pair formulated a rigorous proof of the conjecture for the case of an inhomogeneous electron gas; since their 1964 paper, several other proofs have been found. That paper was formal and understated to the point of desiccation, and one needed to pay it close attention to see how remarkable the result was. The initial response was muted, and Hohenberg moved subsequently into other areas, such as hydrodynamics, phase transitions and pattern formation.
Kohn, however, went on to develop the idea into a practical method for calculating the electronic ground states of molecules and solids, working in particular with Hong Kong-born postdoc Lu-Jeu Sham. Their crucial paper3 was much more explicit about the potential of this approach as an approximation for calculating real materials properties of solids, such as cohesive energies and elastic constants, from quantum principles. It is now one of the most highly cited papers in all of physics, but was an example of a “sleeper”: still the community took some time to wake up to what was on offer. Not until the work of John Pople in the early 1990s did chemists begin to appreciate that DFT could offer a simple and convenient way to calculate electronic structures. It was that work which led to the 1998 Nobel prize in chemistry for Pople and Kohn – incongruous for someone so immersed in physics.
Zangwill argues that DFT defies the common belief that important theories reflect the Zeitgeist: it was an idea that was not in the air at all in the 1960s, and, says Zangwill, “might be unknown today if Kohn had not created it in the mid-1960s.” Clearly that’s impossible to prove. But there’s no mistaking the debt that materials and molecular sciences owe to Kohn’s insight, and so if Zangwill is right, all the more reason to ask if we still create the right sort of environments for such fertile ideas to germinate.
1. Hohenberg, P. & Kohn, W. Phys. Rev. 136, B864-871 (1964).
2. Zangwill, A., http://www.arxiv.org/abs/1403.5164 (2014).
3. Kohn, W. & Sham, L. J. Phys. Rev. 140, A1133-1138 (1965).
Wednesday, October 08, 2014
The moment of uncertainty
As part of a feature section in the October issue of La Recherche on uncertainty, I interviewed Robert Crease, historian and philosopher of science at Stony Brook University, New York, on the cultural impact of Heisenberg’s principle. It turned out that Robert had just written a book looking at this very issue – in fact, at the cultural reception of quantum theory in general. It’s called The Quantum Moment, is coauthored by Alfred Scharff Goldhaber, and is a great read – I have written a mini-review for the next (November) issue of Prospect. Here’s the interview, which otherwise appears only in French in La Recherche. Since Robert has such a great way with words, it was one of the easiest I’ve ever done.
________________________________________________________
What led Heisenberg to formulate the uncertainty principle? Was it something that fell out of the formalism in mathematical terms?
That’s a rather dramatic story. The uncertainty principle emerged in exchange of letters between Heisenberg and Pauli, and fell out of the work that Heisenberg had done on quantum theory the previous year, called matrix mechanics. In autumn 1926, he and Pauli were corresponding about how to understand its implications. Heisenberg insisted that the only way to understand it involved junking classical concepts such as position and momentum in the quantum world. In February 1927 he visited Niels Bohr in Copenhagen. Bohr usually helped Heisenberg to think, but this time the visit didn’t have the usual effect. They grew frustrated, and Bohr abandoned Heisenberg to go skiing. One night, walking by himself in the park behind Bohr’s institute, Heisenberg had an insight. He wrote to Pauli: “One will always find that all thought experiments have this property: when a quantity p is pinned down to within an accuracy characterized by the average error p, then... q can only be given at the same time to within an accuracy characterized by the average error q1 ≈ h/p1.” That’s the uncertainty principle. But like many equations, including E = mc2 and Maxwell’s equations, its first appearance is not in its now-famous form. Anyway, Heisenberg sent off a paper on his idea that was published in May.
How did Heisenberg interpret it in physical terms?
He didn’t, really; at the time he kept claiming that the uncertainty principle couldn’t be interpreted in physical terms, and simply reflected the fact that the subatomic world could not be visualized. Newtonian mechanics is visualizable: each thing in it occupies a particular place at a particular time. Heisenberg thought the attempt to construct a visualizable solution for quantum mechanics might lead to trouble, and so he advised paying attention only to the mathematics. Michael Frayn captures this side of Heisenberg well in his play Copenhagen. When the Bohr character charges that Heisenberg doesn't pay attention to the sense of what he’s doing so long as the mathematics works out, the Heisenberg character indignantly responds, "Mathematics is sense. That's what sense is".
Was Heisenberg disturbed by the implications of what he was doing?
No. Both he and Bohr were excited about what they had discovered. From the very beginning they realized that it had profound philosophical implications, and were thrilled to be able to explore them. Almost immediately both began thinking and writing about the epistemological implications of the uncertainty principle.
Was anyone besides Heisenberg and Bohr troubled?
The reaction was mixed. Arthur Eddington, an astronomer and science communicator, was thrilled, saying that the epistemological implications of the uncertainty principle heralded a new unification of science, religion, and the arts. The Harvard physicist Percy Bridgman was deeply disturbed, writing that “the bottom has dropped clean out” of the world. He was terrified about its impact on the public. Once the implications sink in, he wrote, it would “let loose a veritable intellectual spree of licentious and debauched thinking.”
Did physicists all share the same view of the epistemological implications of quantum mechanics?
No, they came up with several different ways to interpret it. As the science historian Don Howard has shown, the notion that the physics community of the day shared a common view, one they called the “Copenhagen interpretation,” is a myth promoted in the 1950s by Heisenberg for his own selfish reasons.
How much did the public pay attention to quantum theory before the uncertainty principle?
Not much. Newspapers and magazines treated it as something of interest because it excited physicists, but as far too complicated to explain to the public. Even philosophers didn’t see quantum physics as posing particularly interesting or significant philosophical problems. The uncertainty principle’s appearance in 1927 changed that. Suddenly, quantum mechanics was not just another scientific theory – it showed that the quantum world works very differently from the everyday world.
How did the uncertainty principle get communicated to a broader public?
It took about a year. In August 1927, Heisenberg, who was not yet a celebrity, gave a talk at a meeting of the British Association for the Advancement of Science, but it sailed way over the heads of journalists. The New York Times’s science reporter said trying to explain it to the public was like “trying to tell an Eskimo what the French language is like without talking French.” Then came a piece of luck. Eddington devoted a section to the uncertainty principle in his book The Nature of the Physical World, published in 1928. He was a terrific explainer, and his imagery and language were very influential.
How did the public react?
Immediately and enthusiastically. A few days after October 29, 1929, the New York Times, tongue-in-cheek, invoked the uncertainty principle as the explanation for the stock market crash.
And today?
Heisenberg and his principle still feature in popular culture. In fact, thanks to the uncertainty principle, I think I’d argue that Heisenberg has made an even greater impact on popular culture than Einstein. In the American television drama series Breaking Bad, 'Heisenberg' is the pseudonym of the protagonist, a high school chemistry teacher who manufactures and sells the illegal drug crystal methamphetamine. The religious poet Christian Wiman, in his recent book about facing cancer, writes that "to feel enduring love like a stroke of pure luck" amid "the havoc of chance" makes God "the ultimate Uncertainty Principle." In The Ascent of Man, the Polish-British scientist Jacob Bronowski calls the uncertainty principle the Principle of Tolerance. There’s even an entire genre of uncertainty principle jokes. A police officer pulls Heisenberg over and says, "Did you know that you were going 90 miles an hour?" Heisenberg says, "Thanks. Now I'm lost."
Has the uncertainty principle been used for serious philosophical purposes?
Yes. Already in 1929, John Dewey wrote about it to promote his ideas about pragmatism, and in particular his thoughts about the untenability of what he called the “spectator theory of knowledge.” The literary critic George Steiner has used the uncertainty principle to describe the process of literary criticism – how it involves transforming the “object” – that is, text – interpreted, and delivers it differently to the generation that follows. More recently, the Slovene philosopher Slavoj Žižek has devoted attention to the philosophical implications of the uncertainty principle.
Some popular culture uses of the uncertainty principle are off the wall. How do you tell meaningful uses from the bogus ones?
It’s not easy. Popular culture often uses scientific terms in ways that are pretentious, erroneous, wacky, or unverifiable. It’s nonsense to apply the uncertainty principle to medicines or self-help issues, for instance. But how is that different from Steiner using it to describe the process of literary criticism?
Outside of physics, has our knowledge that uncertainty is a feature of the subatomic world, and the uses that it has been put by writers and philosophers, helped to change our worldview in any way?
I think so. The contemporary world does not always feel smooth, continuous, and law-governed, like the Newtonian World. Our world instead often feels jittery, discontinuous, and irrational. That has sometimes prompted writers to appeal to quantum imagery and language to describe it. John Updike’s characters, for instance, sometimes appeal to the uncertainty principle, while Updike himself did so in speaking of the contemporary world as full of “gaps, inconsistencies, warps, and bubbles in the surface of circumstance.” Updike and other writers and poets have found this imagery metaphorically apt.
The historians Betty Dobbs and Margaret Jacob have remarked that the Newtonian Moment provided “the material and mental universe – industrial and scientific – in which most Westerners and some non-Westerners now live, one aptly described as modernity.” But that universe is changing. Quantum theory showed that at a more fundamental level the world is not Newtonian at all, but governed by notions such as chance, probability, and uncertainty.
Robert Crease’s book (with Alfred S. Goldhaber) The Quantum Moment: How Planck, Bohr, Einstein, and Heisenberg Taught Us to Love Uncertainty will be published by Norton in October 2014.
________________________________________________________
What led Heisenberg to formulate the uncertainty principle? Was it something that fell out of the formalism in mathematical terms?
That’s a rather dramatic story. The uncertainty principle emerged in exchange of letters between Heisenberg and Pauli, and fell out of the work that Heisenberg had done on quantum theory the previous year, called matrix mechanics. In autumn 1926, he and Pauli were corresponding about how to understand its implications. Heisenberg insisted that the only way to understand it involved junking classical concepts such as position and momentum in the quantum world. In February 1927 he visited Niels Bohr in Copenhagen. Bohr usually helped Heisenberg to think, but this time the visit didn’t have the usual effect. They grew frustrated, and Bohr abandoned Heisenberg to go skiing. One night, walking by himself in the park behind Bohr’s institute, Heisenberg had an insight. He wrote to Pauli: “One will always find that all thought experiments have this property: when a quantity p is pinned down to within an accuracy characterized by the average error p, then... q can only be given at the same time to within an accuracy characterized by the average error q1 ≈ h/p1.” That’s the uncertainty principle. But like many equations, including E = mc2 and Maxwell’s equations, its first appearance is not in its now-famous form. Anyway, Heisenberg sent off a paper on his idea that was published in May.
How did Heisenberg interpret it in physical terms?
He didn’t, really; at the time he kept claiming that the uncertainty principle couldn’t be interpreted in physical terms, and simply reflected the fact that the subatomic world could not be visualized. Newtonian mechanics is visualizable: each thing in it occupies a particular place at a particular time. Heisenberg thought the attempt to construct a visualizable solution for quantum mechanics might lead to trouble, and so he advised paying attention only to the mathematics. Michael Frayn captures this side of Heisenberg well in his play Copenhagen. When the Bohr character charges that Heisenberg doesn't pay attention to the sense of what he’s doing so long as the mathematics works out, the Heisenberg character indignantly responds, "Mathematics is sense. That's what sense is".
Was Heisenberg disturbed by the implications of what he was doing?
No. Both he and Bohr were excited about what they had discovered. From the very beginning they realized that it had profound philosophical implications, and were thrilled to be able to explore them. Almost immediately both began thinking and writing about the epistemological implications of the uncertainty principle.
Was anyone besides Heisenberg and Bohr troubled?
The reaction was mixed. Arthur Eddington, an astronomer and science communicator, was thrilled, saying that the epistemological implications of the uncertainty principle heralded a new unification of science, religion, and the arts. The Harvard physicist Percy Bridgman was deeply disturbed, writing that “the bottom has dropped clean out” of the world. He was terrified about its impact on the public. Once the implications sink in, he wrote, it would “let loose a veritable intellectual spree of licentious and debauched thinking.”
Did physicists all share the same view of the epistemological implications of quantum mechanics?
No, they came up with several different ways to interpret it. As the science historian Don Howard has shown, the notion that the physics community of the day shared a common view, one they called the “Copenhagen interpretation,” is a myth promoted in the 1950s by Heisenberg for his own selfish reasons.
How much did the public pay attention to quantum theory before the uncertainty principle?
Not much. Newspapers and magazines treated it as something of interest because it excited physicists, but as far too complicated to explain to the public. Even philosophers didn’t see quantum physics as posing particularly interesting or significant philosophical problems. The uncertainty principle’s appearance in 1927 changed that. Suddenly, quantum mechanics was not just another scientific theory – it showed that the quantum world works very differently from the everyday world.
How did the uncertainty principle get communicated to a broader public?
It took about a year. In August 1927, Heisenberg, who was not yet a celebrity, gave a talk at a meeting of the British Association for the Advancement of Science, but it sailed way over the heads of journalists. The New York Times’s science reporter said trying to explain it to the public was like “trying to tell an Eskimo what the French language is like without talking French.” Then came a piece of luck. Eddington devoted a section to the uncertainty principle in his book The Nature of the Physical World, published in 1928. He was a terrific explainer, and his imagery and language were very influential.
How did the public react?
Immediately and enthusiastically. A few days after October 29, 1929, the New York Times, tongue-in-cheek, invoked the uncertainty principle as the explanation for the stock market crash.
And today?
Heisenberg and his principle still feature in popular culture. In fact, thanks to the uncertainty principle, I think I’d argue that Heisenberg has made an even greater impact on popular culture than Einstein. In the American television drama series Breaking Bad, 'Heisenberg' is the pseudonym of the protagonist, a high school chemistry teacher who manufactures and sells the illegal drug crystal methamphetamine. The religious poet Christian Wiman, in his recent book about facing cancer, writes that "to feel enduring love like a stroke of pure luck" amid "the havoc of chance" makes God "the ultimate Uncertainty Principle." In The Ascent of Man, the Polish-British scientist Jacob Bronowski calls the uncertainty principle the Principle of Tolerance. There’s even an entire genre of uncertainty principle jokes. A police officer pulls Heisenberg over and says, "Did you know that you were going 90 miles an hour?" Heisenberg says, "Thanks. Now I'm lost."
Has the uncertainty principle been used for serious philosophical purposes?
Yes. Already in 1929, John Dewey wrote about it to promote his ideas about pragmatism, and in particular his thoughts about the untenability of what he called the “spectator theory of knowledge.” The literary critic George Steiner has used the uncertainty principle to describe the process of literary criticism – how it involves transforming the “object” – that is, text – interpreted, and delivers it differently to the generation that follows. More recently, the Slovene philosopher Slavoj Žižek has devoted attention to the philosophical implications of the uncertainty principle.
Some popular culture uses of the uncertainty principle are off the wall. How do you tell meaningful uses from the bogus ones?
It’s not easy. Popular culture often uses scientific terms in ways that are pretentious, erroneous, wacky, or unverifiable. It’s nonsense to apply the uncertainty principle to medicines or self-help issues, for instance. But how is that different from Steiner using it to describe the process of literary criticism?
Outside of physics, has our knowledge that uncertainty is a feature of the subatomic world, and the uses that it has been put by writers and philosophers, helped to change our worldview in any way?
I think so. The contemporary world does not always feel smooth, continuous, and law-governed, like the Newtonian World. Our world instead often feels jittery, discontinuous, and irrational. That has sometimes prompted writers to appeal to quantum imagery and language to describe it. John Updike’s characters, for instance, sometimes appeal to the uncertainty principle, while Updike himself did so in speaking of the contemporary world as full of “gaps, inconsistencies, warps, and bubbles in the surface of circumstance.” Updike and other writers and poets have found this imagery metaphorically apt.
The historians Betty Dobbs and Margaret Jacob have remarked that the Newtonian Moment provided “the material and mental universe – industrial and scientific – in which most Westerners and some non-Westerners now live, one aptly described as modernity.” But that universe is changing. Quantum theory showed that at a more fundamental level the world is not Newtonian at all, but governed by notions such as chance, probability, and uncertainty.
Robert Crease’s book (with Alfred S. Goldhaber) The Quantum Moment: How Planck, Bohr, Einstein, and Heisenberg Taught Us to Love Uncertainty will be published by Norton in October 2014.
Uncertain about uncertainty
This is the English version of the cover article (in French) of the latest issue of La Recherche (October). It’s accompanied by an interview that I conducted with Robert Crease about the cultural impact of the uncertainty principle, which I’ll post next.
______________________________________________________________________
If there’s one thing most people know about quantum physics, it’s that it is uncertain. There’s a fuzziness about the quantum world that prevents us from knowing everything about it with absolute detail and clarity. Almost 90 years ago, the German physicist Werner Heisenberg pointed this out in his famous Uncertainty Principle. Yet over the few years there has been heated debate among physicists about just what Heisenberg meant, and whether he was correct. The latest experiments seem to indicate that one version of the Uncertainty Principle presented by Heisenberg might be quite wrong, and that we can get a sharper picture of quantum reality than he thought.
In 1927 Heisenberg argued that we can’t measure all the attributes of a quantum particle at the same time and as accurately as we like [1]. In particular, the more we try to pin down a particle’s exact location, the less accurately we can measure its speed, and vice versa. There’s a precise limit to this certainty, Heisenberg said. If the uncertainty is position is denoted Δx, and the uncertainty in momentum (mass times velocity) is Δp, then their product ΔxΔp can be no smaller than ½h, where h [read this as h bar] is the fundamental constant called Planck’s constant, which sets the scale of the ‘granularity’ of the quantum world – the size of the ‘chunks’ into which energy is divided.
Where does this uncertainty come from? Heisenberg’s reasoning was mathematical, but he felt he needed to give some intuitive explanation too. For something as small and delicate as a quantum particle, he suggested, it is virtually impossible to make a measurement without disturbing and altering what we’re trying to measure. It we “look” at an electron by bouncing a photon of light off it in a microscope, that collision will change the path of the electron. The more we try to reduce the intrinsic inaccuracy or “error” of the measurement, say by using a brighter beam of photons, the more we create a disturbance. According to Heisenberg, error (Δe) and disturbance (Δd) are also related by an uncertainty principle in which ΔeΔd can’t be smaller than ½h.
The American physicist Earle Hesse Kennard showed very soon after Heisenberg’s original publication that in fact his thought experiment is superfluous to the issue of uncertainty in quantum theory. The restriction on precise knowledge of both speed and position is an intrinsic property of quantum particles, not a consequence of the limitations of experiments. All the same, might Heisenberg’s “experimental” version of the Uncertainty Principle – his relationship between error and disturbance – still be true?
“When we explain the Uncertainty Principle, especially to non-physicists,” says physicist Aephraim Steinberg of the University of Toronto in Canada, “we tend to describe the Heisenberg microscope thought experiment.” But he says that, while everyone agrees that measurements disturb systems, many physicists no longer think that Heisenberg’s equation relating Δe and Δd describes that process adequately.
Japanese physicist Masanao Ozawa of Nagoya University was one of the first to question Heisenberg. In 2003 he argued that it should be possible to defeat the apparent limit on error and disturbance [2]. Ozawa was motivated by a debate that began in the 1980s on the accuracy of measurements of gravity waves, the ripples in spacetime predicted by Einstein’s theory of general relativity and expected to be produced by violent astrophysical events such as those involving black holes. No one has yet detected a gravity wave, but the techniques proposed to do so entail measuring the very small distortions in space that will occur when such a wave passes by. These disturbances are so tiny – fractions of the size of atoms – that at first glance the Uncertainty Principle would seem to determine if they are feasible at all. In other words, the accuracy demanded in some modern experiments like this means that this question of how measurement disturbs the system has real, practical ramifications.
In 1983 Horace Yuen of Northwestern University in Illinois suggested that, if gravity-wave measurement were done in a way that barely disturbed the detection system at all, the apparently fundamental limit on accuracy dictated by Heisenberg’s error-disturbance relation could be beaten. Others disputed that idea, but Ozawa defended it. This led him to reconsider the general question of how experimental error is related to the degree of disturbance it involves, and in his 2003 paper he proposed a new relationship between these two quantities in which two other terms were added to the equation. In other words, ΔeΔd + A + B ≥ h/2, so that ΔeΔd itself could be smaller than h/2 without violating the limit..
Last year, Cyril Branciard of the University of Queensland in Australia (now at the CNRS Institut Néel at Grenoble) tightened up Ozawa’s new uncertainty equation [3]. “I asked whether all values of Δe and Δd that satisfy his relation are allowed, or whether there could be some values that are nevertheless still forbidden by quantum theory”, Branciard explains. “I showed that there are actually more values that are forbidden. In other words, Ozawa's relation is ‘too weak’.”
But Ozawa’s relationship had by then already been shown to give an adequate account of uncertainty for most purposes, since in 2012 it was put to the test experimentally by two teams [4,5]. Steinberg and his coworkers in Toronto figured out how to measure the quantities in Ozawa’s equation for photons of infrared laser light travelling along optical fibres and being sensed by detectors. They used a way of detecting the photons that perturbed their state as little as possible, and found that indeed they could exceed the relationship between precision and disturbance proposed by Heisenberg but not that of Ozawa. Meanwhile, Ozawa himself teamed up with a team at the Vienna University of Technology led by Yuji Hasegawa, who made measurements on the quantum properties of a beam of neutrons passing through a series of detectors. They too found that the measurements could violate the Heisenberg limit but not Ozawa’s.
Very recent experiments have confirmed that conclusion with still greater accuracy, verifying Branciard’s relationships too [6,7]. Branciard himself was a collaborator on one of those studies, and he says that “experimentally we could get very close indeed to the bounds imposed by my relations.”
Doesn’t this prove that Heisenberg was wrong about how error is connected to disturbance in experimental measurements? Not necessarily. Last year, a team of European researchers claimed to have a theoretical proof that in fact this version of Heisenberg’s Uncertainty Principle is correct after all [8]. They argued that Ozawa’s theory, and the experiments testing it, were using the wrong definitions of error. So they might be correct in their own terms, but weren’t really saying anything about Heisenberg’s error-disturbance principle. As team member Paul Busch of the University of York in England puts it, “Ozawa effectively proposed a wrong relationship between his own definitions of error and disturbance, wrongly ascribed it to Heisenberg, then showed how to fix it.”
So Heisenberg was correct after all in the limits he set on the tradeoff, argues Busch: “if the error is kept small, the disturbance must be large.”
Who is right? It seems to depend on exactly how you pose the question. What, after all, does measurement error mean? If you make a single measurement, there will be some random error that reflects the limits on the accuracy of your technique. But that’s why experimentalists typically make many measurements on the same system, so that you average out some of the randomness. Yet surely, some argue, the whole spirit of Heisenberg’s original argument was about making measurements of different properties on a particular, single quantum object, not averages for a whole bunch of such objects?
It now seems that Heisenberg’s limit on how small the combined uncertainty can be for error and disturbance holds true if you think about averages of many measurements, but that Ozawa’s smaller limit applies if you think about particular quantum states. In the first case you’re effectively measuring something like the “disturbing power” of a specific instrument; in the second case you’re quantifying how much we can know about an individual state. So whether Heisenberg was right or not depends on what you think he meant (and perhaps on whether you think he even recognized the difference).
As Steinberg explains, Busch and colleagues “are really asking how much a particular measuring apparatus is capable of disturbing a system, and they show that they get an equation that looks like the familiar Heisenberg form. We think it is also interesting to ask, as Ozawa did, how much the measuring apparatus disturbs one particular system. Then the less restrictive Ozawa-Branciard relations apply.”
Branciard agrees with Steinberg that this isn’t a question of who’s right and who’s wrong, but just a matter of how you make your definitions. “The two approaches simply address different questions. They each argue that the problem they address was probably the one Heisenberg had in mind. But Heisenberg was simply not clear enough on what he had in mind, and it is always dangerous to put words in someone else's mouth. I believe both questions are interesting and worth studying.”
There’s a broader moral to be drawn, for the debate has highlighted how quantum theory is no longer perceived to reveal an intrinsic fuzziness in the microscopic world. Rather, what the theory can tell you depends on what exactly you want to know and how you intend to find out about it. It suggests that “quantum uncertainty” isn’t some kind of resolution limit, like the point at which objects in a microscope look blurry, but is to some degree chosen by the experimenter. This fits well with the emerging view of quantum theory as, at root, a theory about information and how to access it. In fact, recent theoretical work by Ozawa and his collaborators turns the error-disturbance relationship into a question about the cost of gaining information about one property of a quantum system on the other properties of that system [9]. It’s a little like saying that you begin with a box that you know is red and think weighs one kilogram – but if you want to check that weight exactly, you weaken the link to redness, so that you can’t any longer be sure that the box you’re weighing is a red one. The weight and the colour start to become independent pieces of information about the box.
If this seems hard to intuit, that’s just a reflection of how interpretations of quantum theory are starting to change. It appears to be telling us that what we can know about the world depends on how we ask. To that extent, then, we choose what kind of a world we observe.
The issue isn’t just academic, since an approach to quantum theory in which quantum states are considered to encode information is now starting to produce useful technologies, such as quantum cryptography and the first prototype quantum computers. “Deriving uncertainty relations for error-disturbance or for joint measurement scenarios using information-theoretical definitions of errors and disturbance has a great potential to be useful for proving the security of cryptographic protocols, or other information-processing applications”, says Branciard. “This is a very interesting and timely line of research.”
References
1. W. Heisenberg, Z. Phys. 43, 172 (1927).
2. M. Ozawa, Phys. Rev. A 67, 042105 (2003).
3. C. Branciard, Proc. Natl. Acad. Sci. U.S.A. 110, 6742 (2013).
4. J. Erhart, S. Sponar, G. Sulyok, G. Badurek, M. Ozawa & Y. Hasegawa, Nat. Phys. 8, 185 (2012).
5. L. A. Rozema, A. Darabi, D. H. Mahler, A. Hayat, Y. Soudagar & A. M. Steinberg, Phys. Rev. Lett. 109, 100404 (2012).
6. F. Kandea, S.-Y. Baek, M. Ozawa & K. Edamatsu, Phys. Rev Lett. 112, 020402 (2014).
7. M. Ringbauer, D. N. Biggerstaff, M. A. Broome, A. Fedrizzi, C. Branciard & A. G. White, Phys. Rev. Lett. 112, 020401 (2014).
8. P. Busch, P. Lahti & R. F. Werner, Phys. Rev. Lett. 111, 160405 (2013).
9. F. Buscemi, M. J. W. Hall, M. Ozawa & M. W. Wilde, Phys. Rev. Lett. 112, 050401 (2014).
______________________________________________________________________
If there’s one thing most people know about quantum physics, it’s that it is uncertain. There’s a fuzziness about the quantum world that prevents us from knowing everything about it with absolute detail and clarity. Almost 90 years ago, the German physicist Werner Heisenberg pointed this out in his famous Uncertainty Principle. Yet over the few years there has been heated debate among physicists about just what Heisenberg meant, and whether he was correct. The latest experiments seem to indicate that one version of the Uncertainty Principle presented by Heisenberg might be quite wrong, and that we can get a sharper picture of quantum reality than he thought.
In 1927 Heisenberg argued that we can’t measure all the attributes of a quantum particle at the same time and as accurately as we like [1]. In particular, the more we try to pin down a particle’s exact location, the less accurately we can measure its speed, and vice versa. There’s a precise limit to this certainty, Heisenberg said. If the uncertainty is position is denoted Δx, and the uncertainty in momentum (mass times velocity) is Δp, then their product ΔxΔp can be no smaller than ½h, where h [read this as h bar] is the fundamental constant called Planck’s constant, which sets the scale of the ‘granularity’ of the quantum world – the size of the ‘chunks’ into which energy is divided.
Where does this uncertainty come from? Heisenberg’s reasoning was mathematical, but he felt he needed to give some intuitive explanation too. For something as small and delicate as a quantum particle, he suggested, it is virtually impossible to make a measurement without disturbing and altering what we’re trying to measure. It we “look” at an electron by bouncing a photon of light off it in a microscope, that collision will change the path of the electron. The more we try to reduce the intrinsic inaccuracy or “error” of the measurement, say by using a brighter beam of photons, the more we create a disturbance. According to Heisenberg, error (Δe) and disturbance (Δd) are also related by an uncertainty principle in which ΔeΔd can’t be smaller than ½h.
The American physicist Earle Hesse Kennard showed very soon after Heisenberg’s original publication that in fact his thought experiment is superfluous to the issue of uncertainty in quantum theory. The restriction on precise knowledge of both speed and position is an intrinsic property of quantum particles, not a consequence of the limitations of experiments. All the same, might Heisenberg’s “experimental” version of the Uncertainty Principle – his relationship between error and disturbance – still be true?
“When we explain the Uncertainty Principle, especially to non-physicists,” says physicist Aephraim Steinberg of the University of Toronto in Canada, “we tend to describe the Heisenberg microscope thought experiment.” But he says that, while everyone agrees that measurements disturb systems, many physicists no longer think that Heisenberg’s equation relating Δe and Δd describes that process adequately.
Japanese physicist Masanao Ozawa of Nagoya University was one of the first to question Heisenberg. In 2003 he argued that it should be possible to defeat the apparent limit on error and disturbance [2]. Ozawa was motivated by a debate that began in the 1980s on the accuracy of measurements of gravity waves, the ripples in spacetime predicted by Einstein’s theory of general relativity and expected to be produced by violent astrophysical events such as those involving black holes. No one has yet detected a gravity wave, but the techniques proposed to do so entail measuring the very small distortions in space that will occur when such a wave passes by. These disturbances are so tiny – fractions of the size of atoms – that at first glance the Uncertainty Principle would seem to determine if they are feasible at all. In other words, the accuracy demanded in some modern experiments like this means that this question of how measurement disturbs the system has real, practical ramifications.
In 1983 Horace Yuen of Northwestern University in Illinois suggested that, if gravity-wave measurement were done in a way that barely disturbed the detection system at all, the apparently fundamental limit on accuracy dictated by Heisenberg’s error-disturbance relation could be beaten. Others disputed that idea, but Ozawa defended it. This led him to reconsider the general question of how experimental error is related to the degree of disturbance it involves, and in his 2003 paper he proposed a new relationship between these two quantities in which two other terms were added to the equation. In other words, ΔeΔd + A + B ≥ h/2, so that ΔeΔd itself could be smaller than h/2 without violating the limit..
Last year, Cyril Branciard of the University of Queensland in Australia (now at the CNRS Institut Néel at Grenoble) tightened up Ozawa’s new uncertainty equation [3]. “I asked whether all values of Δe and Δd that satisfy his relation are allowed, or whether there could be some values that are nevertheless still forbidden by quantum theory”, Branciard explains. “I showed that there are actually more values that are forbidden. In other words, Ozawa's relation is ‘too weak’.”
But Ozawa’s relationship had by then already been shown to give an adequate account of uncertainty for most purposes, since in 2012 it was put to the test experimentally by two teams [4,5]. Steinberg and his coworkers in Toronto figured out how to measure the quantities in Ozawa’s equation for photons of infrared laser light travelling along optical fibres and being sensed by detectors. They used a way of detecting the photons that perturbed their state as little as possible, and found that indeed they could exceed the relationship between precision and disturbance proposed by Heisenberg but not that of Ozawa. Meanwhile, Ozawa himself teamed up with a team at the Vienna University of Technology led by Yuji Hasegawa, who made measurements on the quantum properties of a beam of neutrons passing through a series of detectors. They too found that the measurements could violate the Heisenberg limit but not Ozawa’s.
Very recent experiments have confirmed that conclusion with still greater accuracy, verifying Branciard’s relationships too [6,7]. Branciard himself was a collaborator on one of those studies, and he says that “experimentally we could get very close indeed to the bounds imposed by my relations.”
Doesn’t this prove that Heisenberg was wrong about how error is connected to disturbance in experimental measurements? Not necessarily. Last year, a team of European researchers claimed to have a theoretical proof that in fact this version of Heisenberg’s Uncertainty Principle is correct after all [8]. They argued that Ozawa’s theory, and the experiments testing it, were using the wrong definitions of error. So they might be correct in their own terms, but weren’t really saying anything about Heisenberg’s error-disturbance principle. As team member Paul Busch of the University of York in England puts it, “Ozawa effectively proposed a wrong relationship between his own definitions of error and disturbance, wrongly ascribed it to Heisenberg, then showed how to fix it.”
So Heisenberg was correct after all in the limits he set on the tradeoff, argues Busch: “if the error is kept small, the disturbance must be large.”
Who is right? It seems to depend on exactly how you pose the question. What, after all, does measurement error mean? If you make a single measurement, there will be some random error that reflects the limits on the accuracy of your technique. But that’s why experimentalists typically make many measurements on the same system, so that you average out some of the randomness. Yet surely, some argue, the whole spirit of Heisenberg’s original argument was about making measurements of different properties on a particular, single quantum object, not averages for a whole bunch of such objects?
It now seems that Heisenberg’s limit on how small the combined uncertainty can be for error and disturbance holds true if you think about averages of many measurements, but that Ozawa’s smaller limit applies if you think about particular quantum states. In the first case you’re effectively measuring something like the “disturbing power” of a specific instrument; in the second case you’re quantifying how much we can know about an individual state. So whether Heisenberg was right or not depends on what you think he meant (and perhaps on whether you think he even recognized the difference).
As Steinberg explains, Busch and colleagues “are really asking how much a particular measuring apparatus is capable of disturbing a system, and they show that they get an equation that looks like the familiar Heisenberg form. We think it is also interesting to ask, as Ozawa did, how much the measuring apparatus disturbs one particular system. Then the less restrictive Ozawa-Branciard relations apply.”
Branciard agrees with Steinberg that this isn’t a question of who’s right and who’s wrong, but just a matter of how you make your definitions. “The two approaches simply address different questions. They each argue that the problem they address was probably the one Heisenberg had in mind. But Heisenberg was simply not clear enough on what he had in mind, and it is always dangerous to put words in someone else's mouth. I believe both questions are interesting and worth studying.”
There’s a broader moral to be drawn, for the debate has highlighted how quantum theory is no longer perceived to reveal an intrinsic fuzziness in the microscopic world. Rather, what the theory can tell you depends on what exactly you want to know and how you intend to find out about it. It suggests that “quantum uncertainty” isn’t some kind of resolution limit, like the point at which objects in a microscope look blurry, but is to some degree chosen by the experimenter. This fits well with the emerging view of quantum theory as, at root, a theory about information and how to access it. In fact, recent theoretical work by Ozawa and his collaborators turns the error-disturbance relationship into a question about the cost of gaining information about one property of a quantum system on the other properties of that system [9]. It’s a little like saying that you begin with a box that you know is red and think weighs one kilogram – but if you want to check that weight exactly, you weaken the link to redness, so that you can’t any longer be sure that the box you’re weighing is a red one. The weight and the colour start to become independent pieces of information about the box.
If this seems hard to intuit, that’s just a reflection of how interpretations of quantum theory are starting to change. It appears to be telling us that what we can know about the world depends on how we ask. To that extent, then, we choose what kind of a world we observe.
The issue isn’t just academic, since an approach to quantum theory in which quantum states are considered to encode information is now starting to produce useful technologies, such as quantum cryptography and the first prototype quantum computers. “Deriving uncertainty relations for error-disturbance or for joint measurement scenarios using information-theoretical definitions of errors and disturbance has a great potential to be useful for proving the security of cryptographic protocols, or other information-processing applications”, says Branciard. “This is a very interesting and timely line of research.”
References
1. W. Heisenberg, Z. Phys. 43, 172 (1927).
2. M. Ozawa, Phys. Rev. A 67, 042105 (2003).
3. C. Branciard, Proc. Natl. Acad. Sci. U.S.A. 110, 6742 (2013).
4. J. Erhart, S. Sponar, G. Sulyok, G. Badurek, M. Ozawa & Y. Hasegawa, Nat. Phys. 8, 185 (2012).
5. L. A. Rozema, A. Darabi, D. H. Mahler, A. Hayat, Y. Soudagar & A. M. Steinberg, Phys. Rev. Lett. 109, 100404 (2012).
6. F. Kandea, S.-Y. Baek, M. Ozawa & K. Edamatsu, Phys. Rev Lett. 112, 020402 (2014).
7. M. Ringbauer, D. N. Biggerstaff, M. A. Broome, A. Fedrizzi, C. Branciard & A. G. White, Phys. Rev. Lett. 112, 020401 (2014).
8. P. Busch, P. Lahti & R. F. Werner, Phys. Rev. Lett. 111, 160405 (2013).
9. F. Buscemi, M. J. W. Hall, M. Ozawa & M. W. Wilde, Phys. Rev. Lett. 112, 050401 (2014).
Tuesday, October 07, 2014
Waiting for the green (and blue) light
This was intended as a "first response" to the Nobel announcement this morning, destined for the Prospect blog. But as it can take a little while for things to appear there, here it is anyway while the news is still ringing in the air. I'm delighted by the choice.
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Did you notice when traffic lights began to change colour? The green “go” light once was once a yellowish pea green, but today it has a turquoise hue. And whereas the lights would switch with a brief moment of fading up and down, now they blink on and off in an instant.
I will be consigning myself to the farthest reaches of geekdom by admitting this, but I used to feel a surge of excitement whenever, a decade or so ago, I noticed these new-style traffic lights. That’s because I knew I was witnessing the birth of a new age of light technology. Even if traffic lights didn’t press your buttons, the chances are that you felt the impact of the same innovations in other ways, most notably when the definition of your DVD player got a boost from the introduction of Blu-Ray technology, which happened about a decade ago. What made the difference was the development of a material that could be electrically stimulated into emitting bright blue light: the key component of blue light-emitting diodes (LEDs), used in traffic lights and other full-colour signage displays, and of lasers, which read the information on Blu-Ray DVDs.
It’s for such reasons that this year’s Nobel laureates in physics have genuinely changed the world. Japanese scientists Isamu Akasaki, Hiroshi Amano and Shuji Nakamura only perfected the art of making blue-light-emitting semiconductor devices in the 1990s, and as someone who watched that happen I still feel astonished at how quickly this research progressed from basic lab work to a huge commercial technology. By adding blue (and greenish-blue) to the spectrum of available colours, these Japanese researchers have transformed LED displays from little glowing dots that simply told you if the power was on or off to full-colour screens in which the old red-green-blue system of colour televisions, previously produced by firing electron beams at phosphor materials on the screen, can now be achieved instead with compact, low-power and ultra-bright electronics.
It’s because LEDs need much less power than conventional incandescent light bulbs that the invention of blue LEDs is ultimately so important. Sure, they also switch faster, last longer and break less easily than old-style bulbs – you’ll see fewer out-of-service traffic lights these days – but the low power requirements (partly because far less energy is wasted as heat) mean that LED light sources are also good for the environment. Now that they can produce blue light too, it’s possible to make white-light sources from a red-green-blue combination that can act as regular lighting sources for domestic and office use. What’s more, that spectral mixture can be tuned to simulate all kinds of lighting conditions, mimicking daylight, moonlight, candle-light or an ideal spectrum for plant growth in greenhouses. The recent Making Colour exhibition at the National Gallery in London featured a state-of-the-art LED lighting system to show how different the hues of a painting can seem under different lighting conditions.
As with so many technological innovations, the key was finding the right material. Light-emitting diodes are made from semiconductors that convert electrical current into light. Silicon is no good at doing this, which is why it has been necessary to search out other semiconductors that are relatively inexpensive and compatible with the silicon circuitry on which all microelectronics is based. For red and yellow-green light that didn’t prove so hard: semiconductors such as gallium arsenide and gallium aluminium arsenide have been used since the 1960s for making LEDs and semiconductor lasers for optical telecommunications. But getting blue light from a semiconductor proved much more elusive. From the available candidates around the early 1990s, both Akasaki and Amano at Nagoya University and Nakamura at the chemicals company Nichia put their faith in a material called gallium nitride. It seemed clear that this stuff could be made to emit light at blue wavelengths, but the challenge was to grow crystals of sufficient quality to do that efficiently – if there were impurities or flaws in the crystal, it wouldn’t work well enough. Challenges of this kind are typically an incremental business rather than a question of some sudden breakthrough: you have to keep plugging away and refining your techniques, improving the performance of your system little by little.
Nakamura’s case is particularly appealing because Nichia was a small, family-run company on the island of Shikoku, generally considered a rural backwater – not the kind of place you would expect to beat the giants of Silicon Valley in a race for such a lucrative goal. It was his conviction that gallium nitride really was the best material for the job that kept him going.
The Nobel committee has come up trumps here – it’s a choice that rewards genuinely innovative and important work, which no one will grumble about, and which in retrospect seems obvious. And it’s a reminder that physics is everywhere, not just in CERN and deep space.
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