Language That Is Person-First

An editorial in the Canadian Medical Association Journal by Roger Collier highlights the problem of Person-first language: Laudable cause, horrible prose

Person-first language (or language that is person-first, as it prefers to be known) is the nice idea that rather than calling someone, say, "blind", we should call them "a person who is blind", so as to remind everyone that they're not defined by their blindness but are a person first... clever, eh?

No. For one thing, it's just bad English. As Collier puts it: "There’s a reason Ernest Hemingway didn’t call his novel The Person Who Was Male and Advanced in Years and the Sea."

He goes on to quote linguist Helena Halmari who highlights a number of problems with the approach:

In English, emphasis naturally occurs at the end of sentences... so by pushing mention of a disability or disease deeper into a sentence, adherents to person-first language may actually be adding stress to those words. “What you have at the end of a sentence is the new information that gets the most attention,” says Halmari.

Worse yet...

Tucking the disability behind the noun may contribute to stigma rather than reduce it. After all, most adjectives with positive connotations precede nouns. We do not typically say a “person who is beautiful,” for instance, or a “person who is intelligent.” Sticking a word in the shadow of a noun can create the impression that there is something inherently wrong with it - that it should be hidden.

As a 'person with mental illness', I entirely agree. I am a man, a neuroscientist, a blogger; I'm not ashamed of those things, so I don't feel the need to erect linguistic fences between them and my person. I am also a psychiatric patient, a depressive, mentally ill; I'm not ashamed of that, either, and I resent the implication - however well-intentioned - that I should.

To me that's the really troubling part of this: the should aspect. The only reason you should not call someone something, is because they ask you not to.

Person-first advocates claim to be speaking on behalf of the 'group' who are harmed and offended by the current use of language - but who gave them that right? They don't speak for me, or anyone but themselves. I don't see 'the mentally ill' as a group at all, but even if it is one, they're certainly not our  elected representatives.

So non-person-first language doesn't offend me. In fact, I'm more worried by the idea that people will assume that, because I'm mentally ill, I want them to use person-first language. Now that's offensive.

Another Scuffle In The Coma Ward

It's not been a good few weeks for Adrian Owen and his team of Canadian neurologists.

Over the past few years, Owen's made numerous waves, thanks to his claim that some patients thought to be in a vegetative state may, in fact, be at least somewhat conscious, and able to respond to commands. Remarkable if true, but not everyone's convinced.

A few weeks ago, Owen et al were criticized over their appearance in a British TV program about their use of fMRI to measure brain activity in coma patients. Now, they're under fire from a second group of critics over a different project.

The new bone of contention is a paper published in 2011 called Bedside detection of awareness in the vegetative state. In this report, Owen and colleagues presented EEG results that, they said, show that some vegetative patients are able to understand speech.

In this study, healthy controls and patients were asked to imagine performing two different actions: moving their hand, or their toe. Owen et al found that it was possible to distinguish between the 'hand' and 'toe'-related patterns of brain electrical activity. This was true of most healthy control subjects, as expected, but also of some - not all - patients in a 'vegetative' state.

The skeptics aren't convinced, however. They reanalyzed the raw EEG data and claim that it just doesn't prove anything.

This image shows that in a healthy control, EEG activity was "clean" and generally normal. However in the coma patient, the data's a mess. It's dominated by large slow delta waves - in healthy people, you only see those during deep sleep - and there's also a lot of muscle artefacts which can be seen as 'thickening' of the lines.

These don't come from the brain at all, they're just muscle twitches. Crucially, the location and power of these twitches varied over time (as muscle spikes often do).

This wouldn't necessarily be a problem, the critics say, except that the statistics used by Owen et al didn't control for slow variations over time i.e. of correlations between consecutive trials (non-independence). If you do take account of these, there's no statistically significant evidence that you can distinguish the EEG associated with 'hand' vs 'toe' in any patients.

However, in their reply, Owen's team say that:

their reanalysis only pushes two of our three positive patients to just beyond the widely accepted p=0.05 threshold for significance - to p=0.06 and p=0·09, respectively. To dismiss the third patient, whose data remain significant, they state that the statistical threshold for accepting command-following should be adjusted for multiple comparisons... but we know of no groups in this field who routinely use such a conservative correction with patient data, including the critics themselves.

I have to say that, statistical arguments aside, the EEGs from the patients just don't look very reliable, largely because of those pesky muscle spikes. A new method for removing these annoyances has just been proposed... I wonder if that could help settle this?

Goldfine, A., Bardin, J., Noirhomme, Q., Fins, J., Schiff, N., and Victor, J. (2013). Reanalysis of "Bedside detection of awareness in the vegetative state: a cohort study" The Lancet, 381 (9863), 289-291 DOI: 10.1016/S0140-6736(13)60125-7

Is This How Memory Works?

We know quite a bit about how long-term memory is formed in the brain - it's all about strengthening of synaptic connections between neurons. But what about remembering something over the course of just a few seconds? Like how you (hopefully) still recall what that last sentence as about?

Short-term memory is formed and lost far too quickly for it to be explained by any (known) kind of synaptic plasticity. So how does it work? British mathematicians Samuel Johnson and colleagues say they have the answer: Robust Short-Term Memory without Synaptic Learning.

They write:

The mechanism, which we call Cluster Reverberation (CR), is very simple. If neurons in a group are more densely connected to each other than to the rest of the network, either because they form a module or because the network is significantly clustered, they will tend to retain the activity of the group: when they are all initially firing, they each continue to receive many action potentials and so go on firing.

The idea is that a neural network will naturally exhibit short-term memory - i.e. a pattern of electrical activity will tend to be maintained over time - so long as neurons are wired up in the form of clusters of cells mostly connected to their neighbours:

The cells within a cluster (or module) are all connected to each other, so once a module becomes active, it will stay active as the cells stimulate each other.

Why, you might ask, are the clusters necessary? Couldn't each individual cell have a memory - a tendency for its activity level to be 'sticky' over time, so that it kept firing even after it had stopped receiving input?

The authors say that even 'sticky' cells couldn't store memory effectively, because we know that the firing pattern of any individual cell is subject to a lot of random variation. If all of the cells were interconnected, this noise would quickly erase the signal. Clustering overcomes this problem.

But how could a neural clustering system develop in the first place? And how would the brain ensure that the clusters were 'useful' groups, rather than just being a bunch of different neurons doing entirely different things? Here's the clever bit:

If an initially homogeneous (i.e., neither modular nor clustered) area of brain tissue were repeatedly stimulated with different patterns... then synaptic plasticity mechanisms might be expected to alter the network structure in such a way that synapses within each of the imposed modules would all tend to become strengthened.

In other words, even if the brain started out life with a random pattern of connections, everyday experience (e.g. sensory input) could create a modular structure of just the right kind to allow short-term memory. Incidentally, such a 'modular' network would also be one of those famous small-world networks.

It strikes me as a very elegant model. But it is just a model, and neuroscience has a lot of those; as always, it awaits experimental proof.

One possible implication of this idea, it seems to me, is that short-term memory ought to be pretty conservative, in the sense that it could only store reactivations of existing neural circuits, rather than entirely new patterns of activity. Might it be possible to test that...?

Johnson S, Marro J, and Torres JJ (2013). Robust Short-Term Memory without Synaptic Learning. PloS ONE, 8 (1) PMID: 23349664

Is Medical Science Really 86% True?

The idea that Most Published Research Findings Are False rocked the world of science when it was proposed in 2005. Since then, however, it's become widely accepted - at least with respect to many kinds of studies in biology, genetics, medicine and psychology.

Now, however, a new analysis from Jager and Leek says things are nowhere near as bad after all: only 14% of the medical literature is wrong, not half of it. Phew!

But is this conclusion... falsely positive?

I'm skeptical of this result for two separate reasons. First off, I have problems with the sample of the literature they used: it seems likely to contain only the 'best' results. This is because the authors:

• only considered the creme-de-la-creme of top-ranked medical journals, which may be more reliable than others.
• only looked at the Abstracts of the papers, which generally contain the best results in the paper.
• only included the just over 5000 statistically significant p-values present in the 75,000 Abstracts published. Those papers that put their p-values up front might be more reliable than those that bury them deep in the Results.

In other words, even if it's true that only 14% of the results in these Abstracts were false, the proportion in the medical literature as a whole might be much higher.

Secondly, I have doubts about the statistics. Jager and Leek estimated the proportion of false positive p values, by assuming that true p-values tend to be low: not just below the arbitrary 0.05 cutoff, but well below it.

It turns out that p-values in these Abstracts strongly cluster around 0, and the conclusion is that most of them are real:

But this depends on the crucial assumption that false-positive p values are different from real ones, and equally likely to be anywhere from 0 to 0.05.

"if we consider only the P-­values that are less than 0.05, the P-­values for false positives must be distributed uniformly between 0 and 0.05."

The statement is true in theory - by definition, p values should behave in that way assuming the null hypothesis is true. In theory.

But... we have no way of knowing if it's true in practice. It might well not be.

For example, authors tend to put their best p-values in the Abstract. If they have several significant findings below 0.05, they'll likely put the lowest one up front. This works for both true and false positives: if you get p=0.01 and p=0.05, you'll probably highlight the 0.01. Therefore, false positive p values in Abstracts might cluster low, just like true positives.

Alternatively, false p's could also cluster the other way, just below 0.05. This is because running lots of independent comparisons is not the only way to generate false positives. You can also take almost-significant p's and fudge them downwards, for example by excluding 'outliers', or running slightly different statistical tests. You won't get p=0.06 down to p=0.001 by doing that, but you can get it down to p=0.04.

In this dataset, there's no evidence that p's just below 0.05 were more common. However, in many other sets of scientific papers, clear evidence of such "p hacking" has been found. That reinforces my suspicion that this is an especially 'good' sample.

Anyway, those are just two examples of why false p's might be unevenly distributed; there are plenty of others: 'there are more bad scientific practices in heaven and earth, Horatio, than are dreamt of in your model...'

In summary, although I think the idea of modelling the distribution of true and false findings, and using these models to estimate the proportions of each in a sample, is promising, I think a lot more work is needed before we can be confident in the results of the approach.

How To Respond to Criticism

People argue. On the internet, especially. Here's some tips on how best to respond to criticism of your ideas or writing - in my experience (the fact that I've often failed to follow these rules myself is part of that experience.)

Be Nice

Aggressive and insulting responses are a sign of weakness, and readers know it. If you're confident in your position, you can afford to be nice, and it makes your whole case look more convincing. Quite apart from the fact that it's just, well, nice.

Don't call out people for not being nice, though. The Three V's - "vitriolic", "virulent" and "violent" - seem to be especially common complaints. The trouble is that just as remarking on someone's faux pas is, itself, a faux pas, proclaiming that your opponent is using nasty language lowers the tone of your response.

It's natural to feel hurt by insults, but keep your feelings to yourself. Even if the criticism really is appallingly vicious, let it speak for itself: just slip a quote of the worst bits into your response, by way of making a separate point, and don't lower yourself by commenting on it.

Complimenting critics shows strength. It shows that you're confident that, despite the praise you're heaping on them, you're still right. So be generous. It only works if it seems sincere, though, so no outright brown-nosing.

Be Fresh

Don't just defend the ground you've already occupied - take the offensive (without being offensive). Bring new arguments to the table. New facts are always good - if a critic tries to debunk an example you used to prove a point, don't bother to quibble with them: produce three more.

Make your response readable. A reply is a piece of writing like any other, and it should be as concise and as clear as possible. Exhaustive replies are counterproductive; they're unlikely to be read. Just identify the key criticisms, and respond to those.

Stick to the point. Readers want you to engage with the issues. You may feel that you know all about your detractors' beliefs, character, motives and so forth, and that these are interesting. They rarely are.

Be Right

Often forgotten, this one.

If you're not sure whether you're right, find out. Take your time. If you have to say something right now, say you're working on it. Better a late reply than a bad reply.

If you're wrong, admit it. People will forgive an honest mistake, if you hold up your hands and ask them to. A reputation for admitting your mistakes and correcting your views is actually a point in your favor

If you've done something wrong, apologize. And nothing more. Don't try and justify yourself; it never works. Don't try and get people to pity you; it'll ensure no-one does. Just say sorry, and then keep quiet until the whole thing cools down.