A Ghostwriter Speaks

PLoS ONE offers the confessions of a former medical ghostwriter: Being the Ghost in the Machine.





The article (which is open access and short, so well worth a read) explains how Linda Logdberg became a medical writer; what excited her about the job; what she actually did; and what made her eventually give it up.



Ghostwriting of course has a bad press at the moment and it's recently been banned by some leading research centres. Ghostwriting certainly is concerning, because of what it implies about the process leading up the publication.



However, it doesn't create bad science. A bad paper is bad because of what it says, not because of who (ghost)wrote it. Real scientists can write bad papers without a ghostwriter's help.



When pharmaceutical companies pay a ghostwriter, they are not doing this to get access to special dark arts that real scientists are innocent of. As far as I can see, it's just more efficient to use a specialist writer to do your scientific sins, when you're doing it all the time.



Rather like every evil sorcerer has an apprentice to do the day-to-day work of sacrificing animals and mixing potions.



Logdberg says:

My career came to an end over a job involving revising a manuscript supporting the use of a drug for attention deficit-hyperactivity disorder (ADHD), with a duration of action that fell between that of shorter- and longer-acting formulations.



However, I have two children with ADHD, and I failed to see the benefit of a drug that would wear off right at suppertime, rather than a few hours before or a few hours after. Suppertime is a time in ADHD households when tempers and homework arguments are often at their worst.



...Attempts to discuss my misgivings with the [medical] contact met with the curt admonition to ‘‘just write it.’’ But perhaps because this particular disorder was so close to home, I was unwilling to turn this ugly duckling of a ‘‘me-too’’ drug into a marketable swan.

Many scientists will recall being in that kind of situation, albeit in a different context.



When writing a grant application, for example, you are almost literally trying to sell your proposed research to the awarding committee, on several levels. You need to sell the importance of the scientific question; the likely practical benefits of the research; the chance of success using your methods; what makes you the right person to do this work, and so on.



Writing a paper is much the same, although in this case you're selling research you've already done, and the data you collected.



Turning ugly ducklings into fundable, or publishable, swans, is part and parcel of modern science. Of course, the ducklings are not always as ugly as in the case Logdberg describes, but they are rarely as beautiful as they eventually end up.



Logdberg, L. (2011). Being the Ghost in the Machine: A Medical Ghostwriter's Personal View PLoS Medicine, 8 (8) DOI: 10.1371/journal.pmed.1001071

A Ghostwriter Speaks

PLoS ONE offers the confessions of a former medical ghostwriter: Being the Ghost in the Machine.





The article (which is open access and short, so well worth a read) explains how Linda Logdberg became a medical writer; what excited her about the job; what she actually did; and what made her eventually give it up.



Ghostwriting of course has a bad press at the moment and it's recently been banned by some leading research centres. Ghostwriting certainly is concerning, because of what it implies about the process leading up the publication.



However, it doesn't create bad science. A bad paper is bad because of what it says, not because of who (ghost)wrote it. Real scientists can write bad papers without a ghostwriter's help.



When pharmaceutical companies pay a ghostwriter, they are not doing this to get access to special dark arts that real scientists are innocent of. As far as I can see, it's just more efficient to use a specialist writer to do your scientific sins, when you're doing it all the time.



Rather like every evil sorcerer has an apprentice to do the day-to-day work of sacrificing animals and mixing potions.



Logdberg says:

My career came to an end over a job involving revising a manuscript supporting the use of a drug for attention deficit-hyperactivity disorder (ADHD), with a duration of action that fell between that of shorter- and longer-acting formulations.



However, I have two children with ADHD, and I failed to see the benefit of a drug that would wear off right at suppertime, rather than a few hours before or a few hours after. Suppertime is a time in ADHD households when tempers and homework arguments are often at their worst.



...Attempts to discuss my misgivings with the [medical] contact met with the curt admonition to ‘‘just write it.’’ But perhaps because this particular disorder was so close to home, I was unwilling to turn this ugly duckling of a ‘‘me-too’’ drug into a marketable swan.

Many scientists will recall being in that kind of situation, albeit in a different context.



When writing a grant application, for example, you are almost literally trying to sell your proposed research to the awarding committee, on several levels. You need to sell the importance of the scientific question; the likely practical benefits of the research; the chance of success using your methods; what makes you the right person to do this work, and so on.



Writing a paper is much the same, although in this case you're selling research you've already done, and the data you collected.



Turning ugly ducklings into fundable, or publishable, swans, is part and parcel of modern science. Of course, the ducklings are not always as ugly as in the case Logdberg describes, but they are rarely as beautiful as they eventually end up.



Logdberg, L. (2011). Being the Ghost in the Machine: A Medical Ghostwriter's Personal View PLoS Medicine, 8 (8) DOI: 10.1371/journal.pmed.1001071

Debating Greenfield

British neuroscientist Susan Greenfield regrets the recent controversy over certain of her remarks, and calls for a serious debate over "mind change" -

"Mind change" is an appropriately neutral, umbrella concept encompassing the diverse issues of whether and how modern technologies may be changing the functional state of the human brain, both for good and bad.

Very well, here goes. I wonder if Greenfield will reply.



As Greenfield points out, the human brain is plastic and interacts with the environment. Indeed, this is how we are able to learn and adapt to anything. Were our brains entirely unresponsive to what happens to them we would have no memory and probably no behaviour at all.



The modern world is changing your brain, in other words.



However, the same is true of every other era. The Victorian era, the Roman Empire, the invention of agriculture - human brains were never the same after those came along.



Because the brain is where behaviour happens, any change in behaviour must be accompanied by a change in the brain. By talking about how behaviour changes, we will, implicitly, also be discussing the brain.



However it doesn't work in reverse. Changes in the brain can't be assumed to mean changes in behaviour. Greenfield cites, for example, this paper which purports to show reductions in the grey matter volume of certain areas of the brain cortex in Chinese students with internet addiction compared to those without.



The obvious comment here is that it doesn't prove causality, as it is only a correlation. Maybe the reason they got addicted was because they already had these brain changes.



However, there is a more subtle point. Even if these were a direct consequence of excessive internet use, it wouldn't mean that the internet use was changing behaviour.



We have no idea what a slight decrease in grey matter volume in the cerebellum, dorsolateral prefrontal cortex, and supplementary motor area would do to cognition and behaviour. It might not do anything.



My point here is that rather than worrying about the brain, we ought to focus on behaviour. Because that is also focussing on the brain, but it's focussing on the aspects of brain function that actually matter.



Greenfield then poses three questions.

1. Could sustained and often obsessive game-playing, in which actions have no consequences, enhance recklessness in real life?

It's possible that it could, although I don't think we do live in an especially reckless society, given that crime rates are lower now than they have been for 20 years.



However, the question assumes that game playing has no consequences. Yet in-game actions do have in-game consequences. To a non-gamer, these may seem like no consequences, because they're not real.



Yet in the game, they're perfectly real, and if you spend 12 hours a day playing that game, and all your friends do as well - you are going to care about that. Those consequences will matter, to you, and with luck, you'll learn not to be so impulsive in the future.



In World of Warcraft, for example, actions have all too many consequences. If you impulsively decide to attack an enemy in the middle of a raid, you could cause a wipe, which would, quite possibly, ruin everyone's evening and get you a reputation as an oaf.



Exactly as your reputation would suffer if you and your friends went for an evening at the opera, and you stood up in the middle and shouted a profanity. Ah, but that's real life, the response goes. Is it? Is a performance in which hundreds of people sit solemnly, while grown adults dress up and pretend to be singing gods and fairies on the instructions of a deceased anti-semite, any more real than this?

3. How can young people develop empathy if they conduct relationships via a medium which does not allow them the opportunity to gain full experience of eye contact, interpret voice tone or body language, and learn how and when to give and receive hugs?

I do not think that this accurately represents the experience of most children today. However, assuming that it were true, what would be the problem?



If everyone's relationships were conducted online, surely it would be more important to learn how to navigate the online world, than it would be to learn how to interpret body language, which (webcams aside), you would never see, or need to see.



If the brain is plastic and adapts to the environment, as Greenfield argues, then surely the fact that it is adapting to the information age is neither surprising nor concerning. If anything, we ought to be trying to help the process along, to make ourselves better adapted. It would be more worrying if it didn't adapt.



Some might be concerned by this. Surely, there is value in the old way of doing things, value that would be lost in the new era. Unless one can point to definite reasons why the new state of affairs is inherently worse than the old - not just different from it - it is hard to distinguish these concerns from the simple feeling of nostalgia over the past.



The same point could have equally well been made at any time in history. When our ancestors first settled down to farm crops, an early conservative might have lamented - "Young people today are growing up with no idea of how to stab a mammoth in the eye with a spear. All they know is how to plant, water and raise this new-fangled 'wheat'."

Debating Greenfield

British neuroscientist Susan Greenfield regrets the recent controversy over certain of her remarks, and calls for a serious debate over "mind change" -

"Mind change" is an appropriately neutral, umbrella concept encompassing the diverse issues of whether and how modern technologies may be changing the functional state of the human brain, both for good and bad.

Very well, here goes. I wonder if Greenfield will reply.



As Greenfield points out, the human brain is plastic and interacts with the environment. Indeed, this is how we are able to learn and adapt to anything. Were our brains entirely unresponsive to what happens to them we would have no memory and probably no behaviour at all.



The modern world is changing your brain, in other words.



However, the same is true of every other era. The Victorian era, the Roman Empire, the invention of agriculture - human brains were never the same after those came along.



Because the brain is where behaviour happens, any change in behaviour must be accompanied by a change in the brain. By talking about how behaviour changes, we will, implicitly, also be discussing the brain.



However it doesn't work in reverse. Changes in the brain can't be assumed to mean changes in behaviour. Greenfield cites, for example, this paper which purports to show reductions in the grey matter volume of certain areas of the brain cortex in Chinese students with internet addiction compared to those without.



The obvious comment here is that it doesn't prove causality, as it is only a correlation. Maybe the reason they got addicted was because they already had these brain changes.



However, there is a more subtle point. Even if these were a direct consequence of excessive internet use, it wouldn't mean that the internet use was changing behaviour.



We have no idea what a slight decrease in grey matter volume in the cerebellum, dorsolateral prefrontal cortex, and supplementary motor area would do to cognition and behaviour. It might not do anything.



My point here is that rather than worrying about the brain, we ought to focus on behaviour. Because that is also focussing on the brain, but it's focussing on the aspects of brain function that actually matter.



Greenfield then poses three questions.

1. Could sustained and often obsessive game-playing, in which actions have no consequences, enhance recklessness in real life?

It's possible that it could, although I don't think we do live in an especially reckless society, given that crime rates are lower now than they have been for 20 years.



However, the question assumes that game playing has no consequences. Yet in-game actions do have in-game consequences. To a non-gamer, these may seem like no consequences, because they're not real.



Yet in the game, they're perfectly real, and if you spend 12 hours a day playing that game, and all your friends do as well - you are going to care about that. Those consequences will matter, to you, and with luck, you'll learn not to be so impulsive in the future.



In World of Warcraft, for example, actions have all too many consequences. If you impulsively decide to attack an enemy in the middle of a raid, you could cause a wipe, which would, quite possibly, ruin everyone's evening and get you a reputation as an oaf.



Exactly as your reputation would suffer if you and your friends went for an evening at the opera, and you stood up in the middle and shouted a profanity. Ah, but that's real life, the response goes. Is it? Is a performance in which hundreds of people sit solemnly, while grown adults dress up and pretend to be singing gods and fairies on the instructions of a deceased anti-semite, any more real than this?

3. How can young people develop empathy if they conduct relationships via a medium which does not allow them the opportunity to gain full experience of eye contact, interpret voice tone or body language, and learn how and when to give and receive hugs?

I do not think that this accurately represents the experience of most children today. However, assuming that it were true, what would be the problem?



If everyone's relationships were conducted online, surely it would be more important to learn how to navigate the online world, than it would be to learn how to interpret body language, which (webcams aside), you would never see, or need to see.



If the brain is plastic and adapts to the environment, as Greenfield argues, then surely the fact that it is adapting to the information age is neither surprising nor concerning. If anything, we ought to be trying to help the process along, to make ourselves better adapted. It would be more worrying if it didn't adapt.



Some might be concerned by this. Surely, there is value in the old way of doing things, value that would be lost in the new era. Unless one can point to definite reasons why the new state of affairs is inherently worse than the old - not just different from it - it is hard to distinguish these concerns from the simple feeling of nostalgia over the past.



The same point could have equally well been made at any time in history. When our ancestors first settled down to farm crops, an early conservative might have lamented - "Young people today are growing up with no idea of how to stab a mammoth in the eye with a spear. All they know is how to plant, water and raise this new-fangled 'wheat'."

Science Without Method

Everyone knows that The Scientific Method is the key to doing science. No-one's quite sure what it is, but they know it's there, and it's something rather special.


It's not. When scientists sit down to work, we don't use "the scientific method" to make discoveries. We use microscopes, brain scanners, telescopes and particle detectors, all of which are just ways of looking at things. They're special in terms of what they let you look at, but that's it. Science is looking.

It's true that in order to do good science, you need to be careful. You need to avoid falling into various traps that lead to misleading data and false conclusions. You could call the care taken over scientific observations "The Scientific Method", and some people do, but that's misleading, because none of it is specific to science.

One of the most important considerations in science is making make sure that you have a proper control condition. This sounds technical, but all it really means is that you need to make sure that you really are looking at what you set out to observe.

To discover the effect of a drug on people, say, you just give them the drug and look to see what happens, using the appropriaye equipment. However, you need to compare this to an appropriate control, such as a placebo pill, because if you don't, you're not just seeing the effect of the drug, many other things as well, such as the placebo effect, the passage of time, random events.

In the same way, if you wanted to find out what happens when you push that little button on your TV remote, you wouldn't mash five other buttons at the same time. To discover what was in the top drawer of your dresser, you'd look there, not in the bottom drawer.

That's really all there is to it. It can be complicated to do this in practice, but the principle is that simple: you take care to look at what you're interested in.

It's said that part of the "Scientific Method" is forming hypotheses, or theories. Scientists do that, but so do we all, all the time. You might have a theory that your boss is an alcoholic, or that your husband is cheating on you, or that your car's spark plug is bust.

You might call these ideas, notions, hunches, suspicions, thoughts, fears, but they're still hypotheses about the world. Indeed, scientists often use those words too. One word is as good as another.

If your boss was an alcoholic, the way to prove it might be to somehow give him a breathalizer test after lunch, or sneak a peek at his credit card bill and see how much he spends on booze. That would be an observation to test your hypothesis, or in other words, an experiment (another formal word that scientists don't always use).

That's all science is. Looking at things carefully, getting ideas, and checking them out.

I said this in my last post, but it bears repeating: this is why most objections to, or concerns about, "science" or worse "modern science", fail. Any given scientist, or any given scientific theory, may be wrong, just like anyone or anything else. Yet to say that "Science can't" do something is saying that looking and thinking can't do it. To blame "Science" for something is to blame the human mind.

Note: This post is a follow-up to Science Doesn't Say, and the second in a three-part series.

Science Without Method

Everyone knows that The Scientific Method is the key to doing science. No-one's quite sure what it is, but they know it's there, and it's something rather special.


It's not. When scientists sit down to work, we don't use "the scientific method" to make discoveries. We use microscopes, brain scanners, telescopes and particle detectors, all of which are just ways of looking at things. They're special in terms of what they let you look at, but that's it. Science is looking.

It's true that in order to do good science, you need to be careful. You need to avoid falling into various traps that lead to misleading data and false conclusions. You could call the care taken over scientific observations "The Scientific Method", and some people do, but that's misleading, because none of it is specific to science.

One of the most important considerations in science is making make sure that you have a proper control condition. This sounds technical, but all it really means is that you need to make sure that you really are looking at what you set out to observe.

To discover the effect of a drug on people, say, you just give them the drug and look to see what happens, using the appropriaye equipment. However, you need to compare this to an appropriate control, such as a placebo pill, because if you don't, you're not just seeing the effect of the drug, many other things as well, such as the placebo effect, the passage of time, random events.

In the same way, if you wanted to find out what happens when you push that little button on your TV remote, you wouldn't mash five other buttons at the same time. To discover what was in the top drawer of your dresser, you'd look there, not in the bottom drawer.

That's really all there is to it. It can be complicated to do this in practice, but the principle is that simple: you take care to look at what you're interested in.

It's said that part of the "Scientific Method" is forming hypotheses, or theories. Scientists do that, but so do we all, all the time. You might have a theory that your boss is an alcoholic, or that your husband is cheating on you, or that your car's spark plug is bust.

You might call these ideas, notions, hunches, suspicions, thoughts, fears, but they're still hypotheses about the world. Indeed, scientists often use those words too. One word is as good as another.

If your boss was an alcoholic, the way to prove it might be to somehow give him a breathalizer test after lunch, or sneak a peek at his credit card bill and see how much he spends on booze. That would be an observation to test your hypothesis, or in other words, an experiment (another formal word that scientists don't always use).

That's all science is. Looking at things carefully, getting ideas, and checking them out.

I said this in my last post, but it bears repeating: this is why most objections to, or concerns about, "science" or worse "modern science", fail. Any given scientist, or any given scientific theory, may be wrong, just like anyone or anything else. Yet to say that "Science can't" do something is saying that looking and thinking can't do it. To blame "Science" for something is to blame the human mind.

Note: This post is a follow-up to Science Doesn't Say, and the second in a three-part series.

Science Doesn't Say

How many times have you heard someone say that "science tells us" - or that it shows, reveals, says, proves, or makes clear?


It's very common. But it's misleading.

Scientists never talk like this while they're doing science, which suggests that there's something wrong with it. Rather, we say: "Our experiment was inspired by the fact that X, which was shown last year by Y et al".

Y et al aren't just some bunch of famous smart guys who came up with an idea and told everyone, and everyone believed them, because scientists respect authority - which is what "Science Says" means.

No, Y et al is a paper, or other report, and when we say that it shows something, we mean it quite literally. Scientific data is like a photograph or, more accurately perhaps, a window, through which we can just see X.

'Science' is nothing special. It's just looking at stuff.

Indeed, there are scientific papers where the key result is literally a photo, usually taken down a microscope or through a telescope, but still. This paper is a great example. The key result was that the little yellow thing in the third image grew some extra sprouts from day 0 to day 1. It takes some knowledge of the context to understand why that's so interesting, but the actual result is right there.

However, even where the result isn't literally a picture, it is still a window.

This line shows the chemical composition of a particular part of someone's brain. Each of the peaks on the curve corresponds to a particular chemical, and the height of the peak tells us how much of that chemical there is.

There's nothing mysterious about why particular chemicals cause particular peaks. It's well understood. (Conceptually, it's like each molecule is a bell, of a particular size and shape, and they make different sounds when you shake them around. The line is what you get when you shake the piece of brain up, and record how much of each sound you hear back.)

Getting this data is a high tech process requiring special equipment, but all that's just background detail when you actually come to do it. Just as a photographer doesn't need to worry about the mechanics of their camera, and you don't need to worry about how your eye gathers and focusses light as you're reading this.

There is an element of authority and trust in science, but not in any special sense. To take published evidence at face value, you do need to trust that the authors haven't manipulated it, and to trust that they gathered it in the way they described.

But the same goes for any other kind of evidence. Any photograph could be Photoshopped, or the caption could be misleading. Anything you read could be made up. In everyday life, we don't worry about this unless there's a particular reason to.

A scientific journal is just a newspaper with access to better equipment.

There's a view in which "Science" is a kind of oracle that hands down judgements from on high, with scientists as priests who record and proclaim the revelations. This leads to no end of problems.

It easily leads to the view that science is somehow especially hard to understand, or even that we can't understand it, so there's no point in trying. It can lead to the idea that science can't be very interesting compared to the real world. It leads to questions what good it can do, or whether science can ever answer 'the big issues'.

When you realize that science is just looking at stuff, you see that those concerns, far from being valid, don't even make sense.

Science Doesn't Say

How many times have you heard someone say that "science tells us" - or that it shows, reveals, says, proves, or makes clear?


It's very common. But it's misleading.

Scientists never talk like this while they're doing science, which suggests that there's something wrong with it. Rather, we say: "Our experiment was inspired by the fact that X, which was shown last year by Y et al".

Y et al aren't just some bunch of famous smart guys who came up with an idea and told everyone, and everyone believed them, because scientists respect authority - which is what "Science Says" means.

No, Y et al is a paper, or other report, and when we say that it shows something, we mean it quite literally. Scientific data is like a photograph or, more accurately perhaps, a window, through which we can just see X.

'Science' is nothing special. It's just looking at stuff.

Indeed, there are scientific papers where the key result is literally a photo, usually taken down a microscope or through a telescope, but still. This paper is a great example. The key result was that the little yellow thing in the third image grew some extra sprouts from day 0 to day 1. It takes some knowledge of the context to understand why that's so interesting, but the actual result is right there.

However, even where the result isn't literally a picture, it is still a window.

This line shows the chemical composition of a particular part of someone's brain. Each of the peaks on the curve corresponds to a particular chemical, and the height of the peak tells us how much of that chemical there is.

There's nothing mysterious about why particular chemicals cause particular peaks. It's well understood. (Conceptually, it's like each molecule is a bell, of a particular size and shape, and they make different sounds when you shake them around. The line is what you get when you shake the piece of brain up, and record how much of each sound you hear back.)

Getting this data is a high tech process requiring special equipment, but all that's just background detail when you actually come to do it. Just as a photographer doesn't need to worry about the mechanics of their camera, and you don't need to worry about how your eye gathers and focusses light as you're reading this.

There is an element of authority and trust in science, but not in any special sense. To take published evidence at face value, you do need to trust that the authors haven't manipulated it, and to trust that they gathered it in the way they described.

But the same goes for any other kind of evidence. Any photograph could be Photoshopped, or the caption could be misleading. Anything you read could be made up. In everyday life, we don't worry about this unless there's a particular reason to.

A scientific journal is just a newspaper with access to better equipment.

There's a view in which "Science" is a kind of oracle that hands down judgements from on high, with scientists as priests who record and proclaim the revelations. This leads to no end of problems.

It easily leads to the view that science is somehow especially hard to understand, or even that we can't understand it, so there's no point in trying. It can lead to the idea that science can't be very interesting compared to the real world. It leads to questions what good it can do, or whether science can ever answer 'the big issues'.

When you realize that science is just looking at stuff, you see that those concerns, far from being valid, don't even make sense.

What Did Marc Hauser Do?

Marc Hauser, the cognitive psychologist who's been under scrutiny over a case of scientific misconduct since August last year (see past posts), has resigned from Harvard University.


He'd already been suspended from teaching, but until this announcement, it looked as though he might be able to hang on and resume his research, which focussed on the evolution of language and morality. Not any more. Hauser says he's quitting the field that made him famous:

“While on leave over the past year, I have begun doing some extremely interesting and rewarding work focusing on the educational needs of at-risk teenagers. I have also been offered some exciting opportunities in the private sector,” Hauser wrote in a resignation letter to the dean, dated July 7. “While I may return to teaching and research in the years to come, I look forward to focusing my energies in the coming year on these new and interesting challenges.”

So that's the end of the Hauser controversy, then?

Not really. The problem is, we still don't know what actually happened. It's hard for anyone to draw a line under this and move on, as Hauser seems to be doing.

Harvard have been reluctant to reveal any more than the barest details of the case. When the allegations first appeared, they set up an internal investigation. In August 2010 this concluded that Hauser was "soley responsible" for 8 cases of scientific misconduct.

But no-one - outside Harvard's investigative committee - knows what they were. He's been found guilty, and he's been punished, but no-one knows the crimes or the evidence against him.

Am I alone in finding this situation unsatisfactory?

Marc Hauser has published hundreds of scientific papers as well as various books. Only a small number of papers were implicated in the misconduct allegations. But to scientifically evaluate the rest of Hauser's work, we need to know what happened - and how easy the misconduct was to detect.

It makes a big difference, for example, whether the misconduct was the kind of thing that could have been going on, leaving no trace, for many years prior to this.

The lack of firm facts has led to discussion of the case being dominated by rumours and speculation. In October last year, for example, a newspaper published an article claiming that the case against Hauser might not be as strong as it first seemed.

This led to a rebuttal by Gerry Altman, then Editor of Cognition, a journal from which Hauser retracted a paper. Altman said that based on the information he had, Hauser was indeed guilty. But he admitted that he was going on what the Harvard investigation told him; he had not had access to the full data.

When Harvard found Hauser guilty, the Dean of his Faculty justified their secrecy:

The work of the investigating committee as well as its final report are considered confidential to protect both the individuals who made the allegations and those who assisted in the investigation.

Our investigative process will not succeed if individuals do not have complete confidence that their identities can be protected throughout the process and after the findings are reported to the appropriate agencies.

Furthermore, when the allegations concern research involving federal funding, funding agency regulations govern our processes ... For example, federal regulations impose an ongoing obligation to protect the identities of those who provided assistance to the investigation.

However, while this is certainly important, I don't see why it would prevent Harvard from releasing the conclusions of the report. They don't need to name the people who gave evidence against Hauser - but they do need to spell out what he did, and what they think he didn't do, so that the scientific community can come to their own conclusions as to the validity of the rest of Hauser's work.

In his letter, the Dean closed by saying that Harvard were going to

form a faculty committee this fall to reaffirm or recommend changes to the communication and confidentiality practices associated with the conclusion of cases involving allegations of professional misconduct.

I hope so.

What Did Marc Hauser Do?

Marc Hauser, the cognitive psychologist who's been under scrutiny over a case of scientific misconduct since August last year (see past posts), has resigned from Harvard University.


He'd already been suspended from teaching, but until this announcement, it looked as though he might be able to hang on and resume his research, which focussed on the evolution of language and morality. Not any more. Hauser says he's quitting the field that made him famous:

“While on leave over the past year, I have begun doing some extremely interesting and rewarding work focusing on the educational needs of at-risk teenagers. I have also been offered some exciting opportunities in the private sector,” Hauser wrote in a resignation letter to the dean, dated July 7. “While I may return to teaching and research in the years to come, I look forward to focusing my energies in the coming year on these new and interesting challenges.”

So that's the end of the Hauser controversy, then?

Not really. The problem is, we still don't know what actually happened. It's hard for anyone to draw a line under this and move on, as Hauser seems to be doing.

Harvard have been reluctant to reveal any more than the barest details of the case. When the allegations first appeared, they set up an internal investigation. In August 2010 this concluded that Hauser was "soley responsible" for 8 cases of scientific misconduct.

But no-one - outside Harvard's investigative committee - knows what they were. He's been found guilty, and he's been punished, but no-one knows the crimes or the evidence against him.

Am I alone in finding this situation unsatisfactory?

Marc Hauser has published hundreds of scientific papers as well as various books. Only a small number of papers were implicated in the misconduct allegations. But to scientifically evaluate the rest of Hauser's work, we need to know what happened - and how easy the misconduct was to detect.

It makes a big difference, for example, whether the misconduct was the kind of thing that could have been going on, leaving no trace, for many years prior to this.

The lack of firm facts has led to discussion of the case being dominated by rumours and speculation. In October last year, for example, a newspaper published an article claiming that the case against Hauser might not be as strong as it first seemed.

This led to a rebuttal by Gerry Altman, then Editor of Cognition, a journal from which Hauser retracted a paper. Altman said that based on the information he had, Hauser was indeed guilty. But he admitted that he was going on what the Harvard investigation told him; he had not had access to the full data.

When Harvard found Hauser guilty, the Dean of his Faculty justified their secrecy:

The work of the investigating committee as well as its final report are considered confidential to protect both the individuals who made the allegations and those who assisted in the investigation.

Our investigative process will not succeed if individuals do not have complete confidence that their identities can be protected throughout the process and after the findings are reported to the appropriate agencies.

Furthermore, when the allegations concern research involving federal funding, funding agency regulations govern our processes ... For example, federal regulations impose an ongoing obligation to protect the identities of those who provided assistance to the investigation.

However, while this is certainly important, I don't see why it would prevent Harvard from releasing the conclusions of the report. They don't need to name the people who gave evidence against Hauser - but they do need to spell out what he did, and what they think he didn't do, so that the scientific community can come to their own conclusions as to the validity of the rest of Hauser's work.

In his letter, the Dean closed by saying that Harvard were going to

form a faculty committee this fall to reaffirm or recommend changes to the communication and confidentiality practices associated with the conclusion of cases involving allegations of professional misconduct.

I hope so.

Eagle-Eyed Autism? No.

An interesting and refreshing paper from Simon Baron-Cohen's autism group from Cambridge. The results themselves are pretty boring - they found that people with autism have normal visual acuity.


But the story behind it is rather spicy.

Back in 2009, a Cambridge group - different authors, but led by "SBC", published a report claiming that people with autism have exceptionally acute vision. Their average visual acuity was claimed to be 2.8

On this scale, 1.0 is defined as normal, and a sharp-eyed young adult with excellent eyesight would get about 1.5. 2.8 means nearly three times as good. Which is, literally, superhuman - a bird of prey would be happy with that. The paper was titled "Eagle-Eyed Visual Acuity In Autism".

However, what followed was straight out of the Book of Obadiah - "Though you soar like the eagle ... from there I will bring you down, sayeth the Lord". Or in this case, sayeth two experts in visual acuity research, Bach and Dakin, whose qualifications included the fact that they wrote the software used in the original study, which is online here.

They wrote a knock-down critique, arguing that the results were a result of using the wrong settings, which meant that the task was extremely easy. In fact, even perfect performance would only correspond to an acuity of less than 1.

You could never make a test so hard that it would require an acuity of 3.0 on a standard computer. Pixels are just too big. A single pixel is easy to spot, for someone of normal-ish vision. The only way to make it harder would be to use a special, extremely high-res monitor, or to get people to sit a long way from the screen.

So how did a result of nearly 3.0 come out? Because they also turned on data extrapolation, basically saying that if you really aced the easy task, you'd probably do quite well on a harder one. This might be sensible in some situations, but it breaks down when the task was so easy. The autistics seemed to have super vision because they got, say, 99% right, as opposed to 98%.

Yet the present paper represents a happy ending as it's written by a combined team of Cambridge people, and Bach and Dakin as well, although the lead authors of the original weren't on it. This time, they used appropriate methods - they got people to sit 4 meters from the screen. To be extra sure, they also gave everyone an eye exam before testing.

And they found no difference at all. The present paper is heartening - rather than grimly sticking to their guns, they admitted their error.


This story should however serve as a cautionary tale; I previously wrote about the fact that in science, a little mistake can cause a lot of problems. This is one of those cases, although arguably there were two seperate mistakes, but one, the extrapolation, was only a problem because of the main mistake, the big pixels.

Tavassoli T, Latham K, Bach M, Dakin SC, & Baron-Cohen S (2011). Psychophysical measures of visual acuity in autism spectrum conditions. Vision research PMID: 21704058

Eagle-Eyed Autism? No.

An interesting and refreshing paper from Simon Baron-Cohen's autism group from Cambridge. The results themselves are pretty boring - they found that people with autism have normal visual acuity.


But the story behind it is rather spicy.

Back in 2009, a Cambridge group - different authors, but led by "SBC", published a report claiming that people with autism have exceptionally acute vision. Their average visual acuity was claimed to be 2.8

On this scale, 1.0 is defined as normal, and a sharp-eyed young adult with excellent eyesight would get about 1.5. 2.8 means nearly three times as good. Which is, literally, superhuman - a bird of prey would be happy with that. The paper was titled "Eagle-Eyed Visual Acuity In Autism".

However, what followed was straight out of the Book of Obadiah - "Though you soar like the eagle ... from there I will bring you down, sayeth the Lord". Or in this case, sayeth two experts in visual acuity research, Bach and Dakin, whose qualifications included the fact that they wrote the software used in the original study, which is online here.

They wrote a knock-down critique, arguing that the results were a result of using the wrong settings, which meant that the task was extremely easy. In fact, even perfect performance would only correspond to an acuity of less than 1.

You could never make a test so hard that it would require an acuity of 3.0 on a standard computer. Pixels are just too big. A single pixel is easy to spot, for someone of normal-ish vision. The only way to make it harder would be to use a special, extremely high-res monitor, or to get people to sit a long way from the screen.

So how did a result of nearly 3.0 come out? Because they also turned on data extrapolation, basically saying that if you really aced the easy task, you'd probably do quite well on a harder one. This might be sensible in some situations, but it breaks down when the task was so easy. The autistics seemed to have super vision because they got, say, 99% right, as opposed to 98%.

Yet the present paper represents a happy ending as it's written by a combined team of Cambridge people, and Bach and Dakin as well, although the lead authors of the original weren't on it. This time, they used appropriate methods - they got people to sit 4 meters from the screen. To be extra sure, they also gave everyone an eye exam before testing.

And they found no difference at all. The present paper is heartening - rather than grimly sticking to their guns, they admitted their error.


This story should however serve as a cautionary tale; I previously wrote about the fact that in science, a little mistake can cause a lot of problems. This is one of those cases, although arguably there were two seperate mistakes, but one, the extrapolation, was only a problem because of the main mistake, the big pixels.

Tavassoli T, Latham K, Bach M, Dakin SC, & Baron-Cohen S (2011). Psychophysical measures of visual acuity in autism spectrum conditions. Vision research PMID: 21704058

The Brain Is Not Made Of Soup

A critical article about psychiatry has been doing the rounds. Regular Neuroskeptic readers will be all too familiar with the issues here, but to many people they're news.

Here's an article summarizing the original piece. The author's the head of a British think tank, but not a specialist in mental health, so he's probably a good example of the ''intelligent layman":

Neither – in relation to the fastest rising [mental health] diagnoses – is there any evidence of chemical imbalances in the brains of patients. In other words, the problem the [psychiatric] drugs are supposed to solve is an illusion.

There's no evidence of fairies in my garden, either. The concept of a 'chemical imbalance' in the human brain is one of the most fantastic oversimplifications in science, and one of the worst legacies of the modern pharmaceutical industry.

A bowl of soup could have a chemical imbalance. If you're making a chicken broth and you accidentally put in an extra spoonful of coriander, it'll taste horrible. Not enough salt, and it'll be bland. A soup is simple: too much or too little of one thing, and it comes out wrong.

Or...does it? Actually, flavour isn't just the sum of the ingredients. You might put in some extra coriander, and also put in some chilli powder, and that would end up delicious whereas if you left the coriander the same, it would be overwhelmed by the chilli. But you'll need to rethink the paprika as well...

Soups are pretty complicated.

The brain is a restaurant with a hundred billion tables. At each table sits a food critic. An army of chefs prepares an infinity of soups - no two are the same, although some areas of the restaurant tend to get certain kinds - and a legion of waiters serves them up, collects the old bowls and takes them to the kitchen to be washed and refilled.

Each critic has his own preferences. If she gets the right soup, she'll be happy. One soup will be great for one critic, disgusting to another. Some critics demand an ever-changing series of courses, others want the same thing day in day out.

Whether the restaurant gets a good review will depend on the composition of the soups, of course, but on so much else as well: are they delivered on time? Do the waiters collect the empty bowls quickly enough - or do they do it too fast, snatching soup away before it's been eaten? Who are the critics, anyhow?

This is still far too simple. In fact, the waiters and the chefs and the dishwashers are the critics, and how they do their job depends on what soup they're getting. That depends on how they've done their jobs in the past... and everyone's also a musician, playing their part in a symphony that we can't hear and couldn't begin to understand if we did.

Our technology for investigating the chemistry of the brain is comically crude. We can't even take a sample of all of the soups in the whole restaurant, mix them all up and measure their average ingredients. You can do that in animals, but for ethical reasons, not in humans. No-one has ever measured the chemical composition of a living human brain.

We can approximately measure a few very common ingredients. After death we can measure a few more. We can also do a kind of straw poll of critics to see what they like, but we don't know which particular critics answer it, or what soups they are in fact being served. Every month, someone discovers a whole new ingredient.

We can sneak into the kitchen and chuck some spice into the pots, to see what kind of noise the critics make. We can't hear what they're saying, we can only measure the volume from different parts of the restaurant. Some of the most informative studies come from measuring the composition of the waste that gets thrown out in the bins every night.

So next time someone confidently tells you that mental illness either is, or isn't, a chemical imbalance, ask them - which one?

The Brain Is Not Made Of Soup

A critical article about psychiatry has been doing the rounds. Regular Neuroskeptic readers will be all too familiar with the issues here, but to many people they're news.

Here's an article summarizing the original piece. The author's the head of a British think tank, but not a specialist in mental health, so he's probably a good example of the ''intelligent layman":

Neither – in relation to the fastest rising [mental health] diagnoses – is there any evidence of chemical imbalances in the brains of patients. In other words, the problem the [psychiatric] drugs are supposed to solve is an illusion.

There's no evidence of fairies in my garden, either. The concept of a 'chemical imbalance' in the human brain is one of the most fantastic oversimplifications in science, and one of the worst legacies of the modern pharmaceutical industry.

A bowl of soup could have a chemical imbalance. If you're making a chicken broth and you accidentally put in an extra spoonful of coriander, it'll taste horrible. Not enough salt, and it'll be bland. A soup is simple: too much or too little of one thing, and it comes out wrong.

Or...does it? Actually, flavour isn't just the sum of the ingredients. You might put in some extra coriander, and also put in some chilli powder, and that would end up delicious whereas if you left the coriander the same, it would be overwhelmed by the chilli. But you'll need to rethink the paprika as well...

Soups are pretty complicated.

The brain is a restaurant with a hundred billion tables. At each table sits a food critic. An army of chefs prepares an infinity of soups - no two are the same, although some areas of the restaurant tend to get certain kinds - and a legion of waiters serves them up, collects the old bowls and takes them to the kitchen to be washed and refilled.

Each critic has his own preferences. If she gets the right soup, she'll be happy. One soup will be great for one critic, disgusting to another. Some critics demand an ever-changing series of courses, others want the same thing day in day out.

Whether the restaurant gets a good review will depend on the composition of the soups, of course, but on so much else as well: are they delivered on time? Do the waiters collect the empty bowls quickly enough - or do they do it too fast, snatching soup away before it's been eaten? Who are the critics, anyhow?

This is still far too simple. In fact, the waiters and the chefs and the dishwashers are the critics, and how they do their job depends on what soup they're getting. That depends on how they've done their jobs in the past... and everyone's also a musician, playing their part in a symphony that we can't hear and couldn't begin to understand if we did.

Our technology for investigating the chemistry of the brain is comically crude. We can't even take a sample of all of the soups in the whole restaurant, mix them all up and measure their average ingredients. You can do that in animals, but for ethical reasons, not in humans. No-one has ever measured the chemical composition of a living human brain.

We can approximately measure a few very common ingredients. After death we can measure a few more. We can also do a kind of straw poll of critics to see what they like, but we don't know which particular critics answer it, or what soups they are in fact being served. Every month, someone discovers a whole new ingredient.

We can sneak into the kitchen and chuck some spice into the pots, to see what kind of noise the critics make. We can't hear what they're saying, we can only measure the volume from different parts of the restaurant. Some of the most informative studies come from measuring the composition of the waste that gets thrown out in the bins every night.

So next time someone confidently tells you that mental illness either is, or isn't, a chemical imbalance, ask them - which one?

How To Fix Science

Over at Bad Science, Ben Goldacre discusses a big problem with modern science - the published literature is all very well and good, but we don't know what people are finding that goes unpublished:

The scale of the academic universe is dizzying, after all. Our most recent estimate is that there are over 24,000 academic journals in existence, 1.3 million academic papers published every year, and over 50 million papers published since scholarship began.

And for every one of these 50 million papers there will be unknowable quantities of blind alleys, abandoned experiments, conference presentations, work in progress seminars, and more. Look at the vast number of undergraduate and masters dissertations that had an interesting finding, and got turned into finished academic papers: and then think about the even vaster number that don’t...

We are living in the age of information, and vast tracts of data are being generated around the world on every continent and every question. A £200 laptop will let you run endless statistical analyses. The most interesting questions aren’t around individual nuggets of data, but rather how we can corral it to create an information architecture which serves up the whole picture.

I agree with all of this. It is a problem. In fact I'd say it's the single biggest problem with science today. Scientists are required to publish ever-increasing numbers of high-impact papers, in order to get grants and promotions, with the "best" papers, usually meaning the ones with the most interesting positive results, being favored.

Findings that show that nothing especially interesting is going on here all too often get swept under the carpet or re-re-analyzed until a positive result falls out. If you do a study of a certain gene and its association to brain function, say, and find it has no association: that's bad news for you. That will make a low-impact paper, if it makes a paper at all. But maybe it has an association with brain structure? Or personality?

Anyway, that's the problem. What to do about it? Goldacre notes that in medicine, there are mechanisms in place to deal with this:

In medicine, where the stakes are tangible, systems have grown up to try and cope with this problem: trials are supposed registered before they begin, so we can notice the results that get left unpublished. But even here, the systems are imperfect; and pre-registration is very rarely done, even in medical research, for anything other than trials.

Clinical trial pre-registration is a fantastic idea. The systems are certainly imperfect, but they're getting better, and they're much better than nothing. Back in 2008 I proposed that all scientific studies, not just clinical trials, should be publically pre-registered. That way everyone could know what science was going unpublished and could tell when authors were doing analyzes they hadn't originally planned to do (which is fine, so long as you admit to it.)

I still think that would be a good idea. But how would it work in practice? Here's what I've come up with:

Scientific papers should be submitted to journals for publication before the research has started. The Introduction and the Methods section, detailing what you plan to do and why, would then get peer reviewed. The rest of the paper would obviously be a blank at this stage. Anonymous experts would have a chance to critique the methods and rationale.

If the paper's accepted, you then do the research, get the results, and write the Results and Discussion section of the paper. The journal is then required to publish the final paper, assuming that you kept to the original plan. The Introducion and primary Methods would be fixed - you can't change them once the data come in.

You can do additional stuff and run additional analyses all you like, but they'll be marked as secondary, which of course is what they are. Publication would therefore be based on the scientific merits of the experiment, the importance of the question and the quality of the methods, not the "interestingness" of the results. If you want a paper in Nature, it needs to be a great idea, not a lucky shot.

This would be a radical change from the current system. Too radical, almost certainly, to ever happen in one go. So here's another idea as to a kind of stepping-stone on the way:

Already, scientists have to spell out their original rationale and original methods before they do any work - when they apply for funding from a grant awarding body. These grant applications are often very detailed, but at the moment, they're private. And people don't always stick to them.

Why not make the full publication of the grant application a condition of being awarded the money? This would be rather like preregistration of the Introduction and Methods, although less elegant, but it would do the job. And given that most grants consist of public cash, the public really have a right to know this. These applications are usually just PDF files. It would be trivial to put them online - after redacting personal information like applicant résumés, if desired.

How To Fix Science

Over at Bad Science, Ben Goldacre discusses a big problem with modern science - the published literature is all very well and good, but we don't know what people are finding that goes unpublished:

The scale of the academic universe is dizzying, after all. Our most recent estimate is that there are over 24,000 academic journals in existence, 1.3 million academic papers published every year, and over 50 million papers published since scholarship began.

And for every one of these 50 million papers there will be unknowable quantities of blind alleys, abandoned experiments, conference presentations, work in progress seminars, and more. Look at the vast number of undergraduate and masters dissertations that had an interesting finding, and got turned into finished academic papers: and then think about the even vaster number that don’t...

We are living in the age of information, and vast tracts of data are being generated around the world on every continent and every question. A £200 laptop will let you run endless statistical analyses. The most interesting questions aren’t around individual nuggets of data, but rather how we can corral it to create an information architecture which serves up the whole picture.

I agree with all of this. It is a problem. In fact I'd say it's the single biggest problem with science today. Scientists are required to publish ever-increasing numbers of high-impact papers, in order to get grants and promotions, with the "best" papers, usually meaning the ones with the most interesting positive results, being favored.

Findings that show that nothing especially interesting is going on here all too often get swept under the carpet or re-re-analyzed until a positive result falls out. If you do a study of a certain gene and its association to brain function, say, and find it has no association: that's bad news for you. That will make a low-impact paper, if it makes a paper at all. But maybe it has an association with brain structure? Or personality?

Anyway, that's the problem. What to do about it? Goldacre notes that in medicine, there are mechanisms in place to deal with this:

In medicine, where the stakes are tangible, systems have grown up to try and cope with this problem: trials are supposed registered before they begin, so we can notice the results that get left unpublished. But even here, the systems are imperfect; and pre-registration is very rarely done, even in medical research, for anything other than trials.

Clinical trial pre-registration is a fantastic idea. The systems are certainly imperfect, but they're getting better, and they're much better than nothing. Back in 2008 I proposed that all scientific studies, not just clinical trials, should be publically pre-registered. That way everyone could know what science was going unpublished and could tell when authors were doing analyzes they hadn't originally planned to do (which is fine, so long as you admit to it.)

I still think that would be a good idea. But how would it work in practice? Here's what I've come up with:

Scientific papers should be submitted to journals for publication before the research has started. The Introduction and the Methods section, detailing what you plan to do and why, would then get peer reviewed. The rest of the paper would obviously be a blank at this stage. Anonymous experts would have a chance to critique the methods and rationale.

If the paper's accepted, you then do the research, get the results, and write the Results and Discussion section of the paper. The journal is then required to publish the final paper, assuming that you kept to the original plan. The Introducion and primary Methods would be fixed - you can't change them once the data come in.

You can do additional stuff and run additional analyses all you like, but they'll be marked as secondary, which of course is what they are. Publication would therefore be based on the scientific merits of the experiment, the importance of the question and the quality of the methods, not the "interestingness" of the results. If you want a paper in Nature, it needs to be a great idea, not a lucky shot.

This would be a radical change from the current system. Too radical, almost certainly, to ever happen in one go. So here's another idea as to a kind of stepping-stone on the way:

Already, scientists have to spell out their original rationale and original methods before they do any work - when they apply for funding from a grant awarding body. These grant applications are often very detailed, but at the moment, they're private. And people don't always stick to them.

Why not make the full publication of the grant application a condition of being awarded the money? This would be rather like preregistration of the Introduction and Methods, although less elegant, but it would do the job. And given that most grants consist of public cash, the public really have a right to know this. These applications are usually just PDF files. It would be trivial to put them online - after redacting personal information like applicant résumés, if desired.

The Neuro-Recession

Everyone's favourite British psychopharmacologist David "Ecstasy Vs Horseriding" Nutt joins four other leading neuroscientists to discuss the impact of the financial crisis on neuroscience, in an article over at NR:N: Neuroscience in recession?

It's interesting to get an international perspective. Susan Amara, President of the Society for Neuroscience, says that American scientists were encouraged by the surprise $10bn boost to NIH funds that made it into the 2009 economic stimulus package. But these funds are due to run out in 2012.

Meanwhile, in Europe, some countries have slashed funding as part of their austerity programmes - Greece most of all - while the larger and richer nations like France and Germany have protected science. Japan has also opted against major cuts, so far, but with a massive deficit, researchers fear that the axe will fall in coming years.

A repeated complaint is that biomedical research has faced a rate of inflation much higher than the rate experienced by the economy as a whole. Nutt says that if the overall inflation rate is 4% per year, the rate paid by scientists is more like 10%. As a result, even if nominal budgets are protected, the real budget will fall. The current British government has decided to keep nominal science funding flat, while cutting pretty much everything else, which is nice, but it still means falling real investment.

So everyone pretty much agrees that there are cuts, and cuts are bad. OK. Where things get more interesting is in the debate over what this means for individual scientists. Susan Amara says that she fears that investigator-initiated "R01" grants are in danger. These are when a scientist gets an idea, writes it up as a proposal and says "Isn't this cool? Can we have some money to do it?"

Amara warns that this kind of thing seems to be getting harder, while established, ongoing research programmes are being protected. But Tom Insel, head of the NIMH and, therefore, the guy with ultimate responsibility for these R01 grants, says the exact opposite. Insel claims that R01s are being protected in favour of the big programmes! "Where have we cut back in order to preserve R01 grants? ... We have reduced the budget of our intramural research programme."

Who's right on this point? I'm not sure. Maybe US readers might be able to comment.

The authors express particular worry that young neuroscientists (postdocs and PhD students) will suffer, either directly, as a result of not being able to find money, or indirectly in terms of poor morale and a sense that their talents might be better rewarded outside of science - leading to long-term harm to the next generation of neuroscientists.

They offer some words of encouragement, though, saying that the pendulum will swing back towards more investment in the future. Until then, hang on as best you can, even if it means being willing to move to find work with a supervisor, or in a country, which does have good funding prospects...

Amara SG, Grillner S, Insel T, Nutt D, & Tsumoto T (2011). Neuroscience in recession? Nature reviews. Neuroscience, 12 (5), 297-302 PMID: 21505517