In the 10 Questions for A.W.F. Edwards, a mathematical geneticist, he was asked:
Like Fisher you have worked in both statistics and genetics. How do you see the relationship between them, both in your own work and more generally?
Edwards responded in part:
Genetical statistics has changed fundamentally too: our problem was the paucity of data, especially for man, leading to an emphasis on elucidating correct principles of statistical inference. Modern practitioners have too much data and are engaged in a theory-free reduction of it under the neologism ‘bioinformatics’.

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I noticed some blogs were talking about a new Pew Political Typology, and I decided to take their survey to see where I fit in. It said I was an Upbeat, which seemed wrong to me as I’m not that partisan (I voted for Kerry though my registration is Republican). So I took the Political Compass test, and I got my usual result:
Economic Left/Right: 2.13 (I’m fiscally conservative)
Social Libertarian/Authoritarian: -3.38 (I’m socially liberal)
I’m a moderate libertarian who leans toward the slightly more liberal side. My political intensity has been decreasing over the years, and I’ve probably gotten a bit more liberal, so the non-trivially partisan “Upbeat” result took me by surprise. Anyone else have a weird result from the Pew Survey? The questions seemed a bit too black & white for me. Not a big deal, but people talk about it as if the categories are meaningful.

Below the fold, same breed, or not?

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To the right you see a habanero pepper, 100-350 K Scoville units (Jalapeno is 2.5-8 K). I can eat 2 habeneros in one sitting and enjoy it. And what does not kill you can cure cancer. Hot dog! On the other hand, if I want something which is a little less spicey and has a more tangy, aromatic flavor, I really enjoy green Thai peppers. I’m the spicey ScienceBlogger.

The New York Times has an article about a Malay woman who converted to Christianity and now wishes to marry her fiance, who is also a Christian. Her problem is the ideology promoted by the Malaysian government that by definition Malays are Muslim. Additionally, Islamic tradition reinforced by shariah imposes strong sanction, up to capital punishment, upon those who apostatize from the faith. The day to day reality of apostacy varies, there are many unbelievers within the Muslim world, but their rejection of religion is not public and they do not generally follow another religion. The woman profiled in the article not only rejected Islam, but, she converted to another religion and is making her conversion public knowledge and attempting to assert her rights to conversion through the legal system. “Moderate” Muslim nations like Malaysia are in a twilight zone, attempting to reconcile the medieval center of gravity of world normative Islam with their own acknowledgement that the “next stage” in national development requires a relaxation of the coupling between traditional norms and state sanction. The power and strength of Christianity, in particular evangelical Christianity, in concert with the the suffocating march of international liberalism is that it will confront a large number of Muslims and force them to turn away from the older norms of exclusion, domination and anti-individualism (radical Protestants also played this role in northern Europe). One of the advocates for the woman in question is himself a Muslim; in nearby Indonesia it is not unknown for nominal believers in places like East Java to transfer their religious identification to Christianity or Hinduism. A similar process of religious competition occurs in much of Africa as Muslims become Christians and Christians become Muslim. But, the unfortunate reality is that the “center” of the Muslim world, Saudi Arabia and the Arab world, represent the other antipode of fluid toleration of freedom in regards to choice of religion. For the world of Islam these are the Edgardo Mortara moments, but the outcome will not be measured via such sensational cases, but rather by the slow but inevitable wheels of liberalism grinding away at the edifice of medieval social control.

Look at this bitch. No, seriously, check it out, he has this long ass post on fossils and paleoanthropology. How the hell am I supposed blog about human evolution with some pride & self-respect if John Hawks has to cover every damn angle!!!. I know a little about fossils, words like stratigraphy don’t terrorize me, but I just don’t have all the details of every damn fossil at the Awash site or Sterkfontein in my head. Fossils make me want to tear my hair out, how the hell am I supposed to ascertain if the Hobbit is a new species or a pathology? Hawks on the other hand looks at pictures and comes up with the conclusion that they are “without a doubt” a pathology. I can look at hotcaptcha and say, “without a doubt, butt ugly,” but a bunch of bones???
1) Yes, you should make sure to read John Hawks
2) But tell him to stop giving it up for free, the town slut is making it hard for the whores to put bread on the table

Real Clear Politics has a column titled The Secular Right which reflects upon the Mac Donald vs. God affair. Interestingly, the author linked to my post where I followed the debate in The Corner. A few months ago my summary of John Derbyshire’s summary of Judith Rich Harris’ work was linked from her site. Ultimately, I think this should be a clue to NRO that they need to invest in a more robust and user friendly content management system: their archiving blows.

Check out the tour (taxonomy?) of the ScienceBlogs over at 3.14. There are promises of summaries of each SB (I assume I’ll be the handsome ScienceBlogger!).

A. W. F. (Anthony) Edwards is one of Britain’s most distinguished geneticists. He studied genetics at Cambridge as one of the last students of R. A. Fisher, and like Fisher he has contributed actively to both genetics and statistics. In genetics his work includes several influential papers on the reconstruction of phylogenies, and a widely-read recent article on ‘Lewontin’s Fallacy’. In statistics he is known especially for his development and advocacy of the concept of Likelihood as a criterion for scientific inference. He has also made a notable contribution to combinatorial mathematics by finding a method of constructing Venn diagrams for any number of sets. In addition to many scientific papers, he has written four books: Likelihood (1972; expanded edition 1992); Foundations of Mathematical Genetics (1977; 2nd edition 2000); Pascal’s Arithmetical Triangle: the Story of a Mathematical Idea (1987; expanded edition 2002); and Cogwheels of the Mind: the Story of Venn Diagrams (2004). He has written extensively on the history of genetics, mathematics, and statistics, and has co-edited (with H. A. David) Annotated Readings in the History of Statistics (2001), and (with Milo Keynes and Robert Peel) A Century of Mendelism in Human Genetics (2004). He is also a champion glider pilot.

To see his replies to our 10 Questions, click on “Read full post”.

1. You were among the last students of R. A. Fisher. Can you share with us some reminiscences of him?

I first met Fisher in the summer of 1956 and had much contact with him until his death six years later. I saw him last during the Second Human Genetics Conference in Rome in 1961 and subsequently corresponded with him. I have published quite a few of my reminiscences of those times in a number of different places. I have been fortunate in having had a lot of contact with the older generation who knew him better than I did – people like Barnard, Bartlett, Finney, Yates, Race, Ruth Sanger and Bennett – and with members of his family, especially Rose, Harry and Joan (his biographer) amongst his children. Being a fellow of the same Cambridge college (Caius) as Fisher, though not at the same time, has meant daily contact with people who knew him well. But the most important thing is his science, and there everyone can get to know him through his writings, which reveal a mind of extraordinary power and vigour. That is the Fisher whom succeeding generations should learn about and admire.

2. Like Fisher you have worked in both statistics and genetics. How do you see the relationship between them, both in your own work and more generally?

In a sense I have benefitted from being an amateur in both fields so that I see no boundary between them. Though I qualified in genetics the subject almost immediately changed so radically through advances in molecular biology that most geneticists would not now regard me as one of themselves anyway. My generation thought genetics was the study of inheritance; theirs thinks it is the study of genes. As to statistics, I attended eight lectures by Henry Daniels in Cambridge but am otherwise self-taught, being hugely influenced by Fisher’s book Statistical Methods for Research Workers which he told me to buy (and then signed for me). Genetical statistics has changed fundamentally too: our problem was the paucity of data, especially for man, leading to an emphasis on elucidating correct principles of statistical inference. Modern practitioners have too much data and are engaged in a theory-free reduction of it under the neologism ‘bioinformatics’. We had to navigate by the stars; they have GPSs.

3. Much of your early work (some of it in collaboration with L. L. Cavalli-Sforza) was on methods of inferring phylogenies. How do you assess the progress in this field since the 1960s, and how have your own methods stood up to empirical tests?

All my work was in collaboration with Luca Cavalli-Sforza. It was his idea. He hired me to join his group in Pavia in Italy, not specifically to work on phylogenies but to apply the new-fangled computers to human genetics generally. The late delivery of the Olivetti computer was a blessing in disguise because it left us time to talk about what we would do with it when it came. I was initially sceptical because I knew that linkage was statistically difficult and here was Luca proposing what looked like linkage on a tree whose very shape also required estimating!

I think progress on the theoretical side has been incredibly slow, despite the best efforts of Joe Felsenstein, the leading practitioner. In a few months in 1962 and 1963 Luca and I thought up three ways of tackling the problem: least-squares on an additive tree (his), minimum evolution or parsimony (mine) and maximum-likelihood on a stochastic model (very much a joint effort). Forty-odd years on people are still arguing about the relative merits of the descendants of our methods when all along they should have been concentrating on refining the statistical approach through maximum-likelihood, which was our real contribution. Of course, from a practical point of view the computer packages have taken over in a development parallel to that in human genetics, from shakey inferences based on too little data and doubtful logic to computer algorithms trying to digest too much.

4. Your recent article on ‘Lewontin’s Fallacy’ criticises the claim that human geographical races have no biological meaning. As the article itself points out, it could have been written at any time in the last 30 years. So why did it take so long – and have you had any reactions from Lewontin or his supporters?

I can only speak for myself as to why it took me so long. Others closer to the field will have to explain why the penny did not drop earlier, but the principal cause must be the huge gap in communication that exists between anthropology, especially social anthropology, on the one hand, and the humdrum world of population and statistical genetics on the other. When someone like Lewontin bridges the gap, bearing from genetics a message which the other side wants to hear, it spreads fast – on that side. But there was no feedback. Others might have noticed Lewontin’s 1972 paper but I had stopped working in human and population genetics in 1968 on moving to Cambridge because I could not get any support (so I settled down to writing books instead). In the 1990s I began to pick up the message about only 15% of human genetic variation being between, as opposed to within, populations with its non-sequitur that classification was nigh impossible, and started asking my population-genetics colleagues where it came from. Most had not heard of it, and those that had did not know its source. I regret now that in my paper I did not acknowledge the influence of my brother John, Professor of Genetics in Oxford, because he was independently worrying over the question, inventing the phrase ‘the death of phylogeny’ which spurred me on.

Eventually the argument turned up unchallenged in Nature and the New Scientist and I was able to locate its origin. I only started writing about it after lunch one day in Caius during which I had tried to explain the fallacy across the table to a chemist, a physicist, a physiologist and an experimental psychologist – all Fellows of the Royal Society – and found myself faltering. I like to write to clear my mind. Then I met Adam Wilkins, the editor of BioEssays, and he urged me to work my notes up into a paper.

I have had no adverse reaction to it at all, but plenty of plaudits from geneticists, many of whom told me that they too had been perplexed. Perhaps the communication gap is
still too large, or just possibly the point has been taken. After all, Fisher made it in 1925 in Statistical Methods which was written for biologists so it is hardly new.

5. You have written several articles about Fisher’s Fundamental Theorem of Natural Selection. Following a groundbreaking reinterpretation by George Price in the early 1970s, it is now generally accepted that the theorem as intended by Fisher is valid, but some biologists would still question its practical use or importance. Can you explain in non-technical terms the meaning of the theorem, how the correct interpretation differs from earlier misunderstandings of it, and your own view on its biological importance?

Oh, it’s very simple. You must first recall the precise name of Fisher’s book in which it is the centrepiece: The Genetical Theory of Natural Selection. He is studying the mechanisms of natural selection from the point of view of populations regarded as aggregates of genes. Of course he knows, and stresses, that this is not the whole story. But to him selection’s defining effect is to change gene frequencies. He sees that this will only happen if there is variability in the survival rates of different genes.

Animal breeders promote artificial selection by imposing different ‘fitnesses’ on their stock according to desirability, breeding from some and not from others. They thus raise the mean value in the population of the character desired. Fisher saw that this process implicitly relies on a correlation between the character and fitness, so that progress will depend both on the magnitude of this correlation and the extent to which the character is genetically determined. What happens, he then asked, if we designate fitness itself as the character, making the correlation perfect? The answer is that the mean fitness of the genes will increase by an amount that depends on the extent to which fitness is determined by them. This is the fundamental theorem (in a modern paraphrase): ‘The rate of increase in the mean fitness ascribable to natural selection acting through changes in gene frequencies is equal to the additive genetic variance in fitness’.

The theorem does not involve the mean genotypic fitness – that is, the weighted mean of the fitnesses of the genotypes – which is where most interpreters of it went wrong. Fisher’s repeated denials that his theorem referred to the mean genotypic fitness, itself immortalised in Sewall Wright’s ‘adaptive landscapes’, went unheeded. In 1941 Fisher even published an example in which gene frequencies were changed under natural selection but the mean genotypic fitness stayed constant. Nobody noticed.

The brilliance of the fundamental theorem is not merely that it expresses the central dogma of natural selection – the connection between genetic variability and selective change – but that it does so exactly. Fisher discovered what the rate of change was proportional to: not to the total variance in fitness of the genotypes but only to that part of it found by fitting a weighted linear regression to the genotypic fitnesses. This is the part accounted for by the regression itself, the so-called additive genetic variance. Animal breeders know it as the variance of the breeding values of the genotypes. The fundamental theorem disregards the way the genes are distributed through the population, which will depend on the amount of heterosis in fitness, the extent of assortative mating, and similar possibly transient effects. What matters to it are the changes to the mean fitness brought about by changing gene frequencies.

This, then, is the theorem whose ‘practical use or importance’ ‘some biologists would still question’. Let them ask the animal breeders if it is any ‘use’, and let them ask themselves whether they think Darwin’s theory of evolution by natural selection is of any ‘importance’. If they do, then the fundamental theorem should help them to a deeper, Mendelian, understanding of it. If, however, they hanker after a theory that can make evolutionary predictions, like Wright’s adaptive landscapes were thought to do at one time, they are crying for the moon. Possession of the fundamental theorem will no more enable you to predict the flow of evolution than possession of Newton’s law of gravitation will enable you to predict the time of high tide at London Bridge.

It should not be forgotten, however, that shorn of its genetical complexities the theorem does have predictive power, just as the law of gravitation does when applied to the celestial movements that underlie the tides. ‘In a subdivided population the rate of change of the overall growth-rate is proportional to the variance in growth rates’. The ‘populations’ could be economic sectors, for example, or even one’s own savings accounts.

6. Your career since the 1950s spans the period in which computers, and off-the-shelf programs, have become widely available. Has this been an unmixed blessing, and do you think the development of statistics or genetics would have been very different if computers had been available in, say, 1900?

A mixed blessing of course, because the existence of programs hinders the development of the underlying theory. This is particularly true in statistics where, despite assertions to the contrary by Bayesians, the underlying theory is still a matter for discussion. The phenomenon can be seen in the field of phylogenetic trees, where programs based on different methods proliferate.

1900 is a peculiarly well-chosen date on which to hang the question. Not only was it the year in which Mendel’s results became widely known but it was also the year of the publication of the second edition of Karl Pearson’s The Grammar of Science, which included chapters on biological science for the first time. The Grammar of Science was hugely influential in its day, proclaiming that the function of science was ‘not to explain, but to describe by conceptual shorthand our perceptual experience’. ‘The man who classifies facts of any kind whatever, who sees their mutual relation and describes their sequences, is applying the scientific method’. The computer implementation of this sterile philosophy would have had a devastating effect, particularly on the development of statistical theory and the acceptance of Mendelism. All Pearson’s formidable energy would have been devoted to amassing vast quantities of information to be sifted for correlations. William Bateson’s 1894 six-hundred-page Materials for the Study of Variation treated with especial regard to Discontinuity in the Origin of Species would have been digitally scanned and computer programmers urged to uncover its secrets. It doesn’t bear thinking about!

7. In statistics you are especially known for developing and advocating the concept of Likelihood and its use in scientific inference. Can you explain how Likelihood differs from probability, and why Likelihood methods are useful in evaluating hypotheses?

Likelihood compares statistical hypotheses; it has nothing to say about a hypothesis on its own, like a test of significance does. Imagine two statistical hypotheses, each of which predicts the probabilities of all the possible outcomes of an experiment – which need be no more complex than tossing a biassed coin a number of times and counting the heads. The experiment is performed, the heads counted. Given this count, was the probability of heads p1 (the first hypothesis) or p2 (the second hypothesis)?

Now imagine doing the experiment lots of times assuming the first, and then the second, hypothesis. Would you not prefer the hypothesis that had the shorter expected waiting time until the exact number of heads observed turned up? If so, you have just chosen the one with the greater likelihood. The likelihood of a hypothesis is proportional to the probability of the data given the hypothesis. Meaningless for a hypothesis by itself because of the undefined constant of proportiona
lity, with two hypotheses to be compared on the same data this constant is irrelevant, and the ratio of their likelihoods (or the difference in their log-likelihoods) becomes a measure of the support for one hypothesis versus the other.

Likelihoods therefore derive from probabilities, but unlike the latter are not additive. Whereas you can sum the probabilities of two possible outcomes of an experiment to form the probability of ‘either one or the other’, you cannot do the same for the likelihood of two hypotheses; ‘either one hypothesis or the other’ is not in itself a hypothesis enabling the probabilities of outcomes to be computed, so no likelihood for it is defined. But you can graph the likelihood as a function of p and pay special attention to its maximum, the maximum-likelihood estimate of the probability of heads.

The concept of the likelihood function is fundamental to all approaches to statistical inference, whether Bayesian, Neyman-Pearson, or Fisherian. Not everyone agrees that it is meaningful standing alone by itself, but I (and others before me) believe it is. Doubters can always fall back on the above ‘how long to wait’ argument, which I think was due to David Sprott.

8. You have written extensively on the history of genetics, statistics, and mathematics. Apart from the intrinsic interest of historical studies, how important do you think a knowledge of the history of science is for practising scientists?

I find it essential, and cannot imagine doing science without it. Much of what counts as science nowadays is rather theory-free. We don’t really have a word for it. Sequencing the human genome, for example, is a marvellous achievement relying on technical advances of great ingenuity but it did not require historical understanding. It differs intellectually from, say, the associated activity of trying to estimate linkage values between gene loci. The history of the latter, on which I have written recently, is an essential part of the study of the problem, and much modern work suffers from its neglect.

Celebrating the centenary of the publication of the Origin of Species in 1959, Fisher said:
More attention to the History of Science is needed, as much by scientists as by historians, and especially by biologists, and this should mean a deliberate attempt to understand the thoughts of the great masters of the past, to see in what circumstances or intellectual milieu their ideas were formed, where they took the wrong turning or stopped short on the right track.
I agree.

9. R. A. Fisher was a keen eugenist. What are your own views on the role (if any) of eugenics in the modern world?

Fisher’s world was so different from ours, in three ways in particular. Then (say the period between the wars) nation-states were much more independent of each other so that it was possible to discuss population matters for Britain in relative isolation; secondly, it was a time of concern about the possibility of a declining home population; and thirdly many scientists were in the first flush of enthusiasm for the application of Mendelian principles – so recently elucidated – to man. None of this is true today.

For myself, though I was once a grateful holder of a Darwin Research Fellowship of the Eugenics Society (now the Galton Institute), since boyhood I have been more concerned about the quantity of people on earth rather than their quality. In the early 1960s I was a founder-member of a body called, I think, the Conservation Society, which does not seem to exist today. Its main platform was that too large a population would be unsustainable. At the time there was much discussion about over-population which was seen as one of the greatest dangers facing mankind. Interestingly, the worse the problem gets, the less it is discussed. Yet the mounting dangers we face, such as the possibility of global warming, are all exacerbated by too high a world population, given its enthusiasm for motor-cars, aeroplanes, and environmentally-damaging activity generally. It seems that people fear the charge of racism if they comment on population growth – they intuitively understand Fisher’s fundamental theorem.

10. Like yourself, your brother, J. H. Edwards, is also a distinguished geneticist. Nature, nurture, or sibling rivalry?

Well, certainly not sibling rivalry. It is true that we have been sufficiently alike at some stages of our lives to have been mistaken for each other. At the Rome Conference of Human Genetics in 1961 we were in a lift with the Swedish geneticist Jan Lindsten when he engagingly introduced us to another participant as ‘the two most confused brothers in genetics’.

In fact I am 7 1/2 years younger than John, and due to mother’s illness, father’s war service, and wartime privations generally, I hardly encountered him until the end of the war when I was ten. We developed boyhood enthusiasms for science quite independently, he for biology, me for astronomy. But there was a common factor in our education from thirteen to eighteen. We both attended Uppingham School, though of course not at the same time, and were exceptionally well-taught in science and mathematics, in some cases by the same teachers. I cannot stress this influence too strongly. Since I only went to Uppingham because my elder brother did, is that nature or nurture?

Subsequently John’s main influence was when I was learning about likelihood (see the preface to my book Likelihood). He, being medically qualified, keeps me straight on medical matters and I try to keep him straight on things statistical. I deliberately stayed off linkage theory so as not to get too close to his interests. John was more influenced by Lancelot Hogben and J. B. S. Haldane than I was. There is a wonderful letter from Fisher to R. R. Race in 1960 in which he refers to me as ‘my Edwards from Cambridge’ and to John as ‘only one of Hogben’s [pupils]’, so at least Fisher got us straight.

And John introduced me to gliding. Though not exactly a ‘champion’, to use your word, I have enjoyed fifty years gliding and hope for a few more yet.

Within my brain, foun-tains over rugged moun-tains of my terrain, diggit I came too far to front. So I’m meditatin on how to maintain. Stepped off at City Hall into the rain… – Black Thought

That ain’t a igloo, that’s my watch. And that ain’t snow, baby that’s my chain. That’s not an ice tray, that’s my teeth. And that’s not a snowcone, that’s my ring. – Paul Wall

Two very important papers came out yesterday in Science. One (from the Bear Lab at Picower) demonstrates that inhibitory avoidance learning can induce LTP (long-term potentiation) in the hippocampus, and the other (from the Sacktor and Fenton labs at SUNY-Downstate) demonstrates that a particular variant of Protein Kinase C (PKC) known as PKM-zeta (that is necessary and sufficient for LTP maintenance) is necessary in the hippocampus for long-term maintenance of a spatial avoidance memory. Together, these papers make one much more confident about making predictions about the cellular mechanisms of memory based on electrophyz studies in the hippocampal slice. The Scientist has a nice summary of these two, and I suggest reading it. I think the two papers could be even further integrated by taking into account a recent discovery by the Malinow group concerning PKC’s role in AMPA receptor trafficking.

By the way, as I get deeper into this post I realize that it is going to make no sense if you don’t understand at least the basics of neurotransmission, so if you aren’t comfortable with that try a little of this before you read on.

Update:From Todd Sacktor in the comments:

ZIP is quite specific to reversing late-LTP. We showed in Serrano et al. and Frey’s lab showed in Sajikumar et al. (both in J. Neuroscience) that it did not affect baseline synaptic transmission or reverse early LTP. We are currently looking at other types of behavioral memory (including the inhibitory avoidance used in the Bear study).

It’s too early to say whether GluR1 phosphorylation is that important for the PKMzeta effect.

Note also that the Bear paper showed that even training had miniscule effects on field potential recordings in the hippocampus. This was consistent with our observation of no effect of ZIP on baseline field recordings. It may not be that surprising that caged animals have no or few novel events in their lives, the memories of which are worth preserving in the hippocampus. Thank you for reading our paper, Todd

If all that above seemed like an alien language, just give me a second and I’ll unpack it. First off, the behavioral paradigms. Inhibitory avoidance is sometimes known as passive avoidance. All the rat has to do to avoid a shock is to sit still, but the rat is placed on an inch-high platform in the light and the shock grid is in a dark area of the chamber. Rats would much rather be in this dark area, so they have a tendency to step down. The first time they do this, they get a mild foot-shock. Learning is measured by how long it takes them to step down a second time, but this paradigm is so widely used and consistent that we can assume the rat learned the association without even bothering with a test trial. It is not entirely clear just what it is that rats learn during inhibitory avoidance training. It seems that they should be learning an association between the stepping behavior and the shock. On the other hand, inhibitory avoidance could just be a fancy version of contextual fear conditioning (CFC). In CFC rats are simply placed in a box, given a little time to explore, and then administered foot-shock. The indication of learning is a stereotyped behavior known as freezing when they are placed in the same context. This is an adaptive response to fear for rats at least in part because predators (like hawks and whatnot) have poor foveal vision, so they do a lot better if they have a moving target. Point is, rats stand still when they are scared. So it is not clear in inhibitory avoidance whether rats are scared of the step down or are more generally afraid of the apparatus leading to freezing. The reason I’m bothering to make all this distinction is that the association between a cue and a shock has been traced to the amygdala rather than the hippocampus. The hippocampus is thought to encode the context by binding its features up as a single index cue that can be associated with shock in the amygdala. It is possible that the hippocampus constantly takes snapshots of the various aspects of the context together and that stringing these together makes up the film of vivid episodic memory that some refer to as ‘mental time travel’. This makes it curious that the LTP-like changes in the Bear Lab paper are found in the hippocampus when there are “walk-through” controls that get all the same contextual/episodic information except for the shock. My tentative take is that trained and control animals both encode the contextual information, but that shock provides a modulatory input that says, “hey, why don’t you go ahead and lay the memory of this context down a little more permanently.. i have a feeling it’s going to be important later..” This sort of input could come from the amygdala.

In the PKM-zeta study, the behavioral paradigm is Active Spatial Avoidance. The rats are placed on a slowly spinning circle. One portion of space is declared the “shock zone” and remains stationary while the rest of the world spins, so the rat has to keep moving to keep from being eventually moving into the shock zone due to the platform’s rotation. It’s like being a vampire who has to remain outdoors and near the equator. This task could again be separated into two separate types of learning. The rat needs to encode the overall spatial scheme, which is something we expect the hippocampus to be good at, and it has to associate a particular portion of the map with shock. It should be noted that use of this behavioral paradigm is not nearly so widespread as inhibitory avoidance, so less is known about the neural substrates, but the hippocampus appears to be involved. A good way to parse the various forms of learning necessary for the task would be to allow the animal access to the spatial environment without the shock reinforcer, so it can learn the spatial information first. You might expect a more rapid acquisition curve once the shock is turned on, and this improved acquisition might be affected by hippocampal manipulations. The drug manipulations in this study were in the hippocampus, and they knocked the memory out, so something that the rat needs to know to perform this task is encoded in the hippocampus. I’m just not sure if it is a cognitive map or some “episodic” memory like “Remember that time when i was in this spatial area and I got shocked? I better get outta here.” One is remembering a space and one is remembering what happened in a space.

Now let’s take it down a level or two. What is LTP? It is a model for memory at the cellular/synaptic level. A long time ago, Donald Hebb suggested that information in the nervous system was probably stored as changes in the synaptic connection between neurons. In particular, he suggested that they synaptic strength or weight would be increased when the pre-synaptic neuron and the post-synap
tic neuron fired coincidentally. I dunno if it was Hebb who came up with the paraphrase, but everyone paraphrases this principle as “Cells that fire together wire together.” In 1973, Bliss and Lomo were able to demonstrate a cellular phenomenon that did just what Hebb has imagined. They found that high-frequency stimulation of a set of synapses led to enhanced strength. The strength is ascertained by giving baseline pulses of fairly weak stimulation and measuring the post-synaptic change in electrical potential. After high-frequency (tetanic) stimulation, the electrical response to baseline stimulation is potentiated. The emerging consensus is that synaptic strength is determined by the amount of ion flow through AMPA-type glutamate receptors in response to pre-synaptic glutamate release. Thus, you could enhance synaptic strength either by making existing AMPA receptors more permeable or by putting more AMPA receptors in the synapse. This latter is known as AMPAR trafficking. Modifications to AMPA receptors accompany LTP induction and memory acquisition. In particular, one portion of the AMPA receptor (the c-terminal tail of the GluR1 subunit) has a bunch of little spots on it where it can be accessorized. It’s like, does Paul Wall really wanna roll out with his neck, wrist, and grill iced up tonite or is he far from home and might get his chain snatched if he comes too flashy? Then he might only wanna display his Balla Status with his neckpiece.

Three of these spots (S818, S831, and S845) are partially understood. The general idea is that more accesories = stronger synapses. S831 can be modified by CaMKII and PKC, but this doesn’t seem to be sufficient to drive trafficking. S845 is modified by PKA, but this isn’t enough either. In fact, it seems more like the S831 modification controls ion flow (channel conductance) more than it does trafficking. The Malinow group at Cold Spring Harbor just reported a month ago now that they had characterized S818. S818 is modified by only by PKC isoforms. There are several versions of PKC (11, I think), and they have special expression patterns and activation requirements. S818 is in a part of the AMPA receptor that is close to the cellular membrane and is packed full of positive charges. The membrane is made of lipids and may have trouble playing with charged molecules. PKC adds a bunch of negative charge to S818 and helps neutralize the membrane-proximal region of the AMPA receptor allowing the AMPA receptor to fuse into the membrane and start contributing to synaptic strength. So PKC-mediated phosphorylation of the GluR1 subunit of AMPA receptors may be a central mechanism in enhancement of synaptic strength (LTP). This was not known until a month and a half ago which explains why the Bear lab only checked on the status of S831 and S845 after inhibitory avoidance training.

The Bear lab attempted to show that learning induces LTP with four results: 1) After training, S831 is modified the same way it is after LTP. 2) After training, there are more AMPA receptor subunits in or near synapses. 3) After training, baseline stimulation of the synapses produces greater post-synaptic potentials. 4) Synapses that show this enhancement are harder to potentiate with high-frequency stimulation (i.e. the normal way you induce LTP). The third and fourth are really the money. They were made possible by the use of multielectrode recording arrays. Learning doesn’t just globally increase synaptic weights. That would be silly. The changes have to be fairly synapse-specific. So if you just stuck one recording electrode in the hippocampus you might miss the change. Bear and co were able to monitor the status of several recording sites at once. After training, some small portion of synapses were enhanced, while the others seemed to drop off slightly. This drop off is really interesting to me because it looks a lot like some sort of homeostatic signal that might keep overall excitability in the right range for a good signal-to-noise ratio. That’s the problem with just using LTP in your model. Eventually you would get everything strengthened to the max, and you couldn’t tell one piece of data from the other. The paper is more bland and probably more reasonable. “We interpret the coherent decreases in fEPSP slope as reflecting changes in the behavioral state of the animals over the duration of the recording experiments.”

There is one little disconnect in these observations though. The AMPA receptor changes are fairly short-lived. They are up a half-hour after training, but back down after 1-2 hours. The synaptic strength changes, on the other hand, can last over 3 hours, and we know that the memories last much longer than even that. The authors suggest that only a few of the initially enhanced synapses actually stick it out and contribute to the long-lasting potentiation. This would drop the number of synapses displaying the AMPAR-related biochemical markers so far down that the assays just aren’t sensitive enough to detect them anymore. Perhaps another issue is that in order to detect the changes in amount of synaptic AMPA receptors they normalize to actin levels. I haven’t had anyone explain to me yet why you would expect actin levels to remain constant during synaptic modification. Go back and read here and here. Actin is a cytoskeletal protein that is associated with dendritic spine morphology and is dynamically regulated in response to LTP induction. One could easily imagine an initial burst of AMPA receptor insertion followed by changes in the actin cytoskeleton to produce larger synapses and accomodate the new strength setpoint. The drop off of the AMPA receptor signal back to baseline could really reflect a slower rise in synaptic actin. Also, there is another potentiality that can’t explain the overall levels data but could explain the rapid fall off of the S831 modification. The S831 modification may be a simple, fast response to do the trick of enhancing synaptic responses quickly while the slower-reacting process of AMPAR insertion is taking place. S831 modification, remember, allows more ion flow, but doesn’t seem to affect receptor insertion. I could see S831 doing its duty to begin with, but then handing off responsibility to a more permanent change effected by S818 modification and an increase in total number of receptors in the synapse. So the mechanism of synaptic strength enhancement would evolve over its lifespan. There would be mechanisms for acquisition that were separate from those involved in maintenance.

Maintenance. What a memory does day-to-day when you aren’t recalling it or forgetting it. All those phone numbers you know are sitting there as configurations of synaptic weights that have to stay at the right weight as they receive noisy input and all the consituent synaptic molecules are degraded and replaced. The Sacktor lab has made a very nice case for a special role for PKM-zeta in memory maintenance. PKM-zeta is an atypical isoform of Protein Kinase C. Most PKC’s are activated in response to increases in intracellular signaling molecules (such as calcium and diacylglycerol (DAG)), but PKM-zeta doesn’t need any of that. It just goes. You make PKM-zeta and it starts doing its job. It is thus referred to as a constitutively active protein kinase. PKM-zeta isn’t required for LTP induction. It is required for LTP maintenance. In fact, just washing PKM-zeta onto a hippocampal slice will cause increases in synaptic strength. This increase is probably due to increased AMPA receptor insertion. Sacktor and co have a molecule called Zeta Inhibitor Peptide (ZIP) that specifically inhibits PKM-zeta and no other PKCs or other kinases. They showed that ZIP can return potentiated synapses to baseline even after they have been potentiated for 22 hours. So we’ve got a drug that specifically affects LTP maintenance and we think LTP = memory, so let’s put the drug in and see if it affects memory. Sho’
nuff. If you drop ZIP into the hippocampus 22 hours after active spatial avoidance training the animal drops back down to pretraining peformance levels. It forgets everything. This isn’t a temporary retrieval impairment. The memory is still gone a week later. That, my friends, is money. Some eternal sunshine type isht. The whole hippocampus isn’t messed up cos the rats can acquire new memories even under the influence of the drug. It only screws up fairly new memories that have been stored.

There are a couple of things to note about this discovery. The manipulation is still effective on month-old memories. If you’ve read any accounts of memory research you will be familiar with the case of H.M. He is commonly used to illustrate the principle of systems consolidation. Some people believe that the hippocampus is only a temporary memory storage site and that (maybe during sleep) it trains up other permanent storage sites in the neocortex. For instance, H.M. basically had his hippocampus removed, and he still seemed good at remembering stuff from his childhood (which was presumably consolidated) but wasn’t so hot at memories acquired shortly before his surgery. People have extended this observation to rats and showed that lesioning the hippocampus has less effect on month-old memories than on day-old memories. This whole area is very controversial though and there is growing support for the notion that the hippocampus never stops playing a role. This set of experiments speaks to the issue of systems consolidation by showing that month-old memories are abolished by a drug manipulation targeted only to the hippocampus. There are caveats and complexities, but it certainly looks on the surface like synaptic changes in the hippocampus are still housing the memory. But this brings me to my other point. What is really happening when they drop ZIP into the hippocampus? Is every synaptic weight getting dropped down to its lowest possible setting? Do the rats forget everything that the hippocampal memory system was responsible for? There are control experiments where ZIP is shown not to affect baseline synaptic responses, but why shouldn’t it? It seems like the rats should have some information stored in their hippocampi already. Surely some of the weights are already set at high levels. Why wouldn’t ZIP knock those off? I’ll get back to you when I figure all that out. Perhaps memories really are consolidated, but it just takes longer than a month. That doesn’t mean they have to leave the hippocampus, but perhaps the maintenance mechanism changes such that it isn’t reliant on PKM-zeta activity anymore.

I don’t know if the anyone but the Malinow lab is capable of assaying the state of S818, but I think it would be really interesting to take a look at the correspondence between PKM-zeta levels and S818 status. You could directly control the weight of a given synapse by modulating the local amount of PKM-zeta to determine what percentage of newly generated AMPA receptor subunits get modified at S818 and inserted into synapses. I should say that I am not implying that PKM-zeta is the only determinant of synaptic strength. One should be skeptical about ‘magic bullet’ hypotheses. No single molecule is going to do the trick. Also, while these studies make a strong case that LTP may be more than just a model of memory, the link still is not complete until we can perform an engineering feat using the theory. Can we actually implant a memory in an animal by inducing LTP at the proper synapses? From a 2003 paper by Richard Morris (that you can download for free if you want):

The fourth criterion, surely not yet met, is mimicry: were it feasible to alter the pattern of synaptic weights in a network in an appropriate manner, the animal should behave as if it remembered something that, in practice, had not happened. Tim Bliss calls this the ‘Marilyn Monroe’ criterion. This weakness of the available data apart, a rich array of physiological, pharmacological, molecular engineering and other techniques, allied to behavioural studies, have now tightened up the link between activity-dependent synaptic plasticity and memory to a point where it is reasonable to set aside a scientist’s natural scepticism about the central principle.