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This Is Your Brain On Magnets — Or Maybe Not

Soulskill posted more than 5 years ago | from the it's-going-south dept.

Medicine 59

conspirator23 writes "Jon Hamilton of National Public Radio brings us a story about 'voodoo correlations' in fMRI studies that seek to learn more about emotional states, personality, and social cognition in the human brain. Many of us outside the scientific community have been treated to fascinating images of brain activity and corresponding explanations about how the images reveal which portions of the brain are engaged in certain kinds of thinking. But these images are not actual snapshots; they are visualizations of data generated by repeated scans during experiments. Flaws in the statistical methods used by researchers can result in false images with a variety of inaccuracies. Yet the images produced are so vivid and engaging that even other neuroscientists can be misled by them."

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Voodoo + brains = (1)

PhilHibbs (4537) | more than 5 years ago | (#28623109)

There's a "zombies" joke in there somewhere.

Re:Voodoo + brains = (-1, Flamebait)

Anonymous Coward | more than 5 years ago | (#28623209)

NPR Listeners == Fags

Re:Voodoo + brains = (-1, Flamebait)

Anonymous Coward | more than 5 years ago | (#28624703)

FOX News Viewers == Fags

Re:Voodoo + brains = (0, Troll)

dzfoo (772245) | more than 5 years ago | (#28626819)

Anonymous Coward Replying to Fag Joke = Fag

      Oh wait!
        -dZ.

Re:Voodoo + brains = (1)

db32 (862117) | more than 5 years ago | (#28626973)

Don't worry. It has been buried.

These beautiful visualizations (0)

Anonymous Coward | more than 5 years ago | (#28623169)

REALLY?

*clicks link to look at pictures*

*curses internet*

Pretty Familiar to Me (2, Interesting)

eldavojohn (898314) | more than 5 years ago | (#28623223)

These sort of images are pretty familiar to me and I must admit I was never skeptical of research showing that you could classify brain patterns based on the object they were looking at or how they were feeling. I had thought this had gone so far as to be used to classify terrorists and used in trials (which is quite unnerving)! Well, it saddens me to say this but in a field where we normally take two steps forward today, we are taking one giant step back. The brain is such a complex thing to study concerning biology, chemistry, electromagnetic physics, psychiatry and psychology. The line where the physical sciences stop and the psychological science starts is so blurred and confusing, it's a shame that one of the few tools used to determine the hows and whys of it is being called into question. I think a lot of us hoped there was some hard scientific way to unravel this mystery of cognizance and conscience. After reading the article, it's a good thing this happened but a shame for quite a bit of research out there that must now be re-examined.

Re:Pretty Familiar to Me (3, Interesting)

jstults (1406161) | more than 5 years ago | (#28623497)

These sort of images are pretty familiar to me and I must admit I was never skeptical of research [...] it's a shame that one of the few tools used to determine the hows and whys of it is being called into question.

I don't think this 'uncertainty' is anything new. Computing a tomographic reconstruction is an ill-posed problem, you can do least squares, you can be a Bayesian, but in the end you have to introduce information or assumptions to fill out the "null space" of your measurements.

I think there's been a lack of understanding on the part of many folks in the medical community about just what kinds of assumptions go into making those pretty CT and MRI results. Treating spurious features in reconstructions due to the measurement and regularization technique was an intense area of early research in this field.

Computed Tomography [wikipedia.org]

Tomographic Reconstruction [wikipedia.org]

Re:Pretty Familiar to Me (1)

Rei (128717) | more than 5 years ago | (#28624597)

I work in the field, and the field is *all about* trying to figure out what is signal and what is noise. We have this massive multi-site study wrapping up involving scanning the same subjects at different sites all over the country, on multiple days for each site, in the same conditions in each scan and each site, and seeing what sort of artifacts show up. And they're significant -- even the scans on the same hardware at the same site on different days, but even moreso for different hardware. But that was known, was expected, and is the reason we have so many analysts studying the data to find algorithmic ways to cancel out the variation and find the true signal.

MRI does not use reconstruction (1)

calidoscope (312571) | more than 5 years ago | (#28624689)

A fundamental difference between MRI and CT is that computing the MRI image involves (at least in some cases) a 2-D FFT. While signal to noise ratio is an issue, the processing is not an ill-posed problem.

It doesn't? (1)

jeffb (2.718) (1189693) | more than 5 years ago | (#28624815)

A fundamental difference between MRI and CT is that computing the MRI image involves (at least in some cases) a 2-D FFT. While signal to noise ratio is an issue, the processing is not an ill-posed problem.

Hmm. My group definitely calls the process of moving from k-space to image space "reconstruction". There are good reasons for doing more than a simple 2D FFT (most of which, I'll admit, are over my head).

Re:MRI does not use reconstruction (1)

jstults (1406161) | more than 5 years ago | (#28624857)

The assumptions underlying the choice of forward model and measurement process that allow you to use the FFT approach turn an ill-posed problem into a well-posed one, true.

Making different assumptions leads to different reconstruction techniques. *Any* scan like this (CT, MRI, ultrasound, infrared, microwave) involves dealing with an ill-posed problem in some way. It may be dealt with before any of the researchers in question touch the machine or the subjects, but it was dealt with by someone at some point.

Really Useful? (2, Interesting)

squoozer (730327) | more than 5 years ago | (#28623229)

I've always wondered how useful these images really are. Perhaps to the trained eye they can reveal a lot about how a persons brain works but they have always struck me as being too abstract. We can point at a portion of the image and say that bit controls movement, for example, but if anything goes wrong we are stuck because at a fundamental level we don't understand how it controls movement. I suppose it's a bit like looking at a block diagram for a CPU and not understanding how each bit works.

It will be interesting to see how we achieve the next level of understanding of the brains functioning. I can't see that we will ever get there with MRI or electrode probes because, I think, they are simply too large to get a true understanding of what is going on. I suspect we will gain our understanding through modelling but I'm not sure I'll be around when we do.

Re:Really Useful? (1)

ColdWetDog (752185) | more than 5 years ago | (#28623407)

I suppose it's a bit like looking at a block diagram for a CPU and not understanding how each bit works.

Worse. It's more like taking a voltmeter and checking the voltages on the PSU pins to try to figure out how the CPU works. All you're doing in fMRI is trying to measure differential oxygen uptake.

Aside from it being technically very difficult to do, it's not clear how far oxygen uptake maps to brain function. It's a crude, clumsy process. But heck, it's science. Rinse, lather, repeat - hopefully with a better shampoo. The biggest issue are the idiots who think it's advanced enough to do things like anti terrorist mapping but I rather suspect even these folks know better, they're just trolling for dollars.

Re:Really Useful? (1)

nobdoor (1496229) | more than 5 years ago | (#28623661)

To my understanding, it's not measuring 'differential oxygen uptake' like you explain. It's measuring an impulse response through the axon/neuron/dendrite, which is an electro-chemical signal derived from potassium and some other compound. Correct me if I'm wrong, but I don't think it's oxygen that gives neurons their charge.

Re:Really Useful? (4, Informative)

Metasquares (555685) | more than 5 years ago | (#28623975)

The GP is correct... functional MRI measures blood oxygenation level dependent (BOLD) response - that is, the change in paramagnetism induced by oxygenated hemoglobin. Active neurons require more oxygen than inactive neurons, so oxygenated blood is delivered to them more rapidly (the hemodynamic response). This induces a local shift in magnetic permeability (from paramagnetic to diamagnetic) which can be picked up by the scanner.

Whether the BOLD signal truly correlates well with neural activity is still a matter of contention within the medical community.

Re:Really Useful? (2, Insightful)

klazek (1134141) | more than 5 years ago | (#28624719)

Whether the BOLD signal truly correlates well with neural activity is still a matter of contention within the medical community

True, and we should mention that the time resolution on fMRI is on the order of a second or two. This suggests also some significant time walk or smearing in the signal. The point is that minimum brain response time is quite a bit faster than this (a few tens of ms), and this is smaller than the resolution of fMRI.

That being said, if you don't have brain pictures in your grant proposal, your chances of getting a cognitive science grant are greatly diminished. So everyone tries to find some way to use it, whether it makes sense or not.

Re:Really Useful? (1)

idontgno (624372) | more than 5 years ago | (#28625067)

Whoa. fMRI is just measuring "current flow" across coarsely-defined regions of the "CPU"? And not instantaneous measurements, but time-integrated ones? And with only a fairly crude map of CPU area->function, trying to deduce exactly what instructions and data the CPU is processing?

Does this sound...unreliable...to anyone else?

Re:Really Useful? (1)

ColdWetDog (752185) | more than 5 years ago | (#28626267)

Don't get too wound up about that analogy - it's fairly weak. My point being that the brain is really the ultimate 'black box' and our attempts to divine what is going on up there (or down there depending on whether or not we're talking about politicians, but I digress) are fairly crude at present. Functional MRI is interesting - there is undoubtedly a correlation between oxygen uptake and brain function, but I don't think we really know how strong that correlation is or what it really signifies.

Personally, I think that trying to analogize a brain to a silicon CPU creates more problems than it solves. The brain is vastly different in overall architecture compared with even highly networked silicon von Neumann machines. I think that the person(s) that solve how the mammalian brain is organized will come from a very different set of assumptions. But who knows? Stay tuned, YouTube video at 11.

Re:Really Useful? (0)

Anonymous Coward | more than 5 years ago | (#28632155)

No matter how many "cores" you ponder, the brain is not wired that way --- it's massively and dynamically parallel.

Modelling fMRI signals is non-trivial. One is trying to pull a few pct signal out of a background that has few pct or higher noise. Moreover, the issue of multiple comparisons is huge (homage to Keith Worsely who recently died -- the brain mapping community still mourns his loss). Morover, most maps are not the "strength" of the correlation but rather the statistical significance of the correlation -- strength of correlation is confounded by the vasculature.

And to boot, in the olden days people typically did studies where a stimulus is applied to the human subject and the search was for response that lined up with the stimulus after folding in the hemodynamic response function. Now all the rage is to look for large-scale correlations between parts of the brain --- and the length of the acquisitions (minutes) are at the Nyquist limits for the correlations being found. If you thought that conventional stimulus/response was voodoo --- think about these studies which are pulling signals out of nowhere with nasty blind source separation techniques.

Re:Really Useful? (0)

Anonymous Coward | more than 5 years ago | (#28627441)

An important, unresolved question is: How uniform is the relationship between BOLD and neural activity across different parts of the brain?

Within cortex, the relationship may be reasonably uniform. Across other, deep brain regions, however, the relationship is unlikely to be consistent. For this reason, comparing fMRI BOLD signals between regions of cortex may make sense, but comparing BOLD across other regions seems tricky, at best.

Another confounding factor is that many fMRI studies perform analysis in terms of "Regions of Interest", aka ROI. I think this means first identifying an ROI, and then looking at that region's BOLD signal under various conditions. The way in which an ROI is identified may, in some cases, be suspect. I think often a "threshold" is applied to the whole data set. Someone care to clarify?

Re:Really Useful? (0)

Anonymous Coward | more than 5 years ago | (#28630085)

It is definitely not measuring differential oxygen uptake. It has been known for quite a while that the paramagnetic/dimagnetic effect of oxygen binding is overwhelmed by changes in blood flow. There is some argument whether oxygen binding is responsible for a initial decrease in BOLD signal, but even the existence of the undershoot is controversial. The BOLD signal comes overwhelmingly from oxygenated blood. The lack of coupling of blood flow and blood oxygenation to oxygen consumption is one of the big mysteries of the brain. Some (Buxton) suggest that maybe what's going on is that the partial pressure of oxygen is being maintained at a constant level.

Re:Really Useful? (1)

msparker (449164) | more than 5 years ago | (#28623635)

I suspect we will gain our understanding through modelling but I'm not sure I'll be around when we do.

I agree. I've always thought that one of Edelman's conscious artifacts, http://www.21stcentury.co.uk/robotics/nomad.asp [21stcentury.co.uk] , would be the way in to a better understanding of the brain, but I haven't kept up with their progress. I'm still hoping they'll find some answers while I'm around.

I have seen this before... (-1, Troll)

Anonymous Coward | more than 5 years ago | (#28623241)

"Flaws in the statistical methods used by researchers can result in false images with a variety of inaccuracies. Yet the images produced are so vivid and engaging that even other neuroscientists can be misled by them."

Looks just like Climate Science then...

MAGNETS! (-1, Offtopic)

Anonymous Coward | more than 5 years ago | (#28623291)

I for one welcome our new magnetic overlords.

Well, what is the noise level? (1)

Khashishi (775369) | more than 5 years ago | (#28623399)

It's easy to dismiss the results as noise, but any decent researcher will estimate her or his error bars, and show that the signal measured is, indeed, small or comparable to the error bars. The way the article is written, it just sounds like they just totally ignored the results because they don't like them or something. To be fair, the paper itself probably does a better job of defending its position, but I don't have time to understand all its details.

Re:Well, what is the noise level? (1)

jstults (1406161) | more than 5 years ago | (#28623709)

I think (based on the admittedly slim article) their criticism is based on many researchers not properly accounting for pseudoreplication [wikipedia.org] , which tends to be a problem when you have tons and tons of data like in an fMRI scan, but it is only on a few individuals, or it is on one individual measured a couple different times. The way to properly treat this is with split-plot or mixed effects models, this is a bit harder to get right than just fitting a linear model and looking at error bars.

The compounding problem with any sort of CT scan is that you have to make assumptions / regularizations to create the image from the measurements in the first place, so the bias introduced by this process is probably not treated well either (it's not easy).

Re:Well, what is the noise level? (1)

Hatta (162192) | more than 5 years ago | (#28625785)

It's not the noise that's the problem. It's the control. Ideally you'd have a blank slate as a control, then do an activity, and measure the difference. The problem is, the brain is always doing something, so it's really hard to make a controlled experiment. It doesn't matter how tight your error bars are if you're not comparing your data to a valid, standard, control.

I actually DO fMRI research (3, Informative)

AtomicDevice (926814) | more than 5 years ago | (#28623767)

I will say, it would be easy to make wild claims about what areas of the brain "do" things just by looking at a scan and showing a pretty picture.

That said, consider these things:
While non-peer-reviewed publications often publish exciting results, the scientific community typically does not accept brain regions without corroboration from many different studies with different stimuli, often including monkey studies where real electrodes and not just low-res fMRI can be used
It is difficult to get the numbers of subject that would be considered standard in other studies for fMRI studies. First off you actually need subjects who will do the assigned task, then you need them to do it perfectly still, for anywhere between 20 minutes to several hours (usually in no more than 1-hour segments). So the likelihood that just one study could prove something is quite small.
In many (perhaps most) studies, all the subjects brains are averaged together for data analysis, there are several different ways of doing this, none of them particularly accurate. This again calls attention to the need for multiple studies

It's also important to actually know what you're looking at when you see pictures of "brain activity", usually you are looking at the averaged activity of many subjects, after it has been run through (most likely) some form of general linear model or event-related analysis. Both of these methods estimate and fit a hemodynamic response function (the pattern of brain response to a stimulus), and what you're actually looking at is the fit or perhaps t-values (roughly fit/std. deviation) for each voxel.

Also note, that for almost any study, I could pick some random brain areas that are "lighting up" and claim a response, but they would almost certainly be shot down with more subjects, another study, etc.

bottom line, responsible investigators can make good sense out of fMRI data, but doing one experiment and claiming you "found the love [or insert whatever emotion/though] center is irresponsible and should be correlated with other studies and hopefully monkey studies as well.

Re:I actually DO fMRI research (1)

lomedhi (801451) | more than 5 years ago | (#28627695)

doing one experiment and claiming you "found the love [or insert whatever emotion/though] center is irresponsible and should be correlated with other studies and hopefully monkey studies as well.

This would also allow us to use the term "monkey love" in a future Slashdot headline.

The data is a useful starting point.. (1)

wanax (46819) | more than 5 years ago | (#28623799)

I think most people in the neuroscience community are aware of the limits of current fMRI approaches. The general linear model, which is used to compute blood flow, is rightly under considerable attack from a number of directions (it assumes, among other things, that all measured hemodynamic response is the result of changes in underlying neural activity, and there is now quite a bit of evidence that this is not the case). And the basic paradigm for most fMRI experiments, especially ones examining 'higher cognition' and emotion is the deeply limited subtractive inference (which was once described to me as "You show somebody a picture of their ass, and you show them a picture of a hole in the ground, subtract the two responses, and claim you've figured out the area responsible for discerning your asshole from a hole in the ground). The 'double dipping' described in the article is actually quite a minor concern compared with the above, although certainly a real one.

But the real value of fMRI, regardless of the deeply flawed current methodologies, is that it does give us a very good idea what areas of the brain we should be looking at with other experimental techniques, such as various types of electrophysiology, anatomical tracing, inactivation etc... And the good news is that there are fMRI methods being developed which are much more robust and will be able to tell us a great deal more about what's going on in the entire brain over various tasks, such as multispectral MRI and attempts to use stronger magnets to directly measure currents, rather than blood flow. So while I certainly agree that there is an 'Oooh! Shiny!' element to a lot of current fMRI research on higher cognition, and one should be deeply skeptical about many of the assertions made on the basis of such data, that doesn't mean fMRI is not an incredibly useful research method, and is likely to become even more so.

No good neuroscientist is going purely off fMRI (1)

LockeOnLogic (723968) | more than 5 years ago | (#28624041)

fMRI is one of many imaging techniques which continue to evolve and give us more and more amazing data about the brain. But its just data, and subject to the limitations of its tech. Any neuroscientist worth their salt knows the limitations of their technology. The problem desribed in the article is something people have been dicussing as a valid methodological criticism of some studies, not all fMRI data. The summary is misleading, basically its saying a tool used incorrectly results in bad data. Duh.

fMRI has great spatial but bad temporal resolution
EEG and MEG and great temporal resolution but bad spatial
PET has amazing metabolic resoultion but fuzzy temporal and spatial resolution

These are a few examples. The media and bad researchers can't get past the pretty visualization but fit into a proper theoretical model of exploration it still remains one of the most amazing tools of brain exploration thus far.

Lucky nobody's getting carried away with this (1)

wjousts (1529427) | more than 5 years ago | (#28624055)

Oh wait yes they are! [nytimes.com]

Old news... (0)

Anonymous Coward | more than 5 years ago | (#28624107)

These issues were explored several years ago in a book by Joseph Dumit, _Picturing Personhood_, which covers both the problems in constructing these images, and the way that these images are taken up as facts by courts, the news, etc.

Can I get High with Magnets???? (1)

jameskojiro (705701) | more than 5 years ago | (#28624173)

If I buy some of those powerful Neodymium magnets and move them over my head can I get high that way?

I would like to know because that would same me a lot of money, or would I have to keep buying more and more powerful magnets to keep achieving the same "high" effect?

Re:Can I get High with Magnets???? (1)

treeves (963993) | more than 5 years ago | (#28627465)

Sure, that'll work, but you've got to remove your tinfoil hat first.

"These images are not snapshots"? No kidding. (4, Informative)

jeffb (2.718) (1189693) | more than 5 years ago | (#28624723)

I've been lucky enough to work with MR and CT imaging researchers for a while now. One of the benefits of this job is that I've gotten to learn a lot about how these images are acquired and reconstructed. It's not quite as bad as making sausage, but it's a lot more involved than a "snapshot".

For CT, we acquire a bunch of 2D images through you from different angles, then do a lot of number crunching to generate a 3D volume. The problem is that you don't hold still while we're doing it. You can try; you can even hold your breath, but you can't "hold your heart". As your organs move between views, we get motion artifacts -- shape distortion, bright or dark areas, even "things" that aren't really there.

For MR, it's even worse. I can barely tread water in the physics of it, but we're effectively capturing a line at a time in 3D space. (We're actually acquiring data in "k-space", then running it through a Fourier transform to make it spatial.) Not only is it subject to motion artifacts, it's also subject to susceptibility artifacts (distortions because of the magnetic properties of certain materials), flow artifacts (blood moves through vessels between the time that we apply a magnetic pulse and the time that we read back emitted signals), and lots of other things.

fMRI is just adding yet another layer of aggregation and interpretation on top of all this. Sure, it's a "visualization of data generated by repeated scans", but so is every CT or MRI image.

3D imaging, especially MRI, is hideously complicated and indirect. It's almost inconceivable that it could yield results with any physical significance.

...and yet, it does. It's become so routine, so reliable, so well-understood and well-controlled, that doctors and researchers know they can rely on it as a matter of course. They still have to be aware of the errors and distortions that can arise, but that's true of every imaging or monitoring system, all the way down to the stethoscope and the fever thermometer.

Re:"These images are not snapshots"? No kidding. (1)

jstults (1406161) | more than 5 years ago | (#28625187)

Mod parent up.

3D imaging, especially MRI, is hideously complicated and indirect. It's almost inconceivable that it could yield results with any physical significance.

...and yet, it does. It's become so routine, so reliable, so well-understood and well-controlled, that doctors and researchers know they can rely on it as a matter of course. They still have to be aware of the errors and distortions that can arise, but that's true of every imaging or monitoring system, all the way down to the stethoscope and the fever thermometer.

Modelling the measurement is fundamental to physical science, even something as simple as measuring the temperature of air, and these are much more complex measurements to model.

Re:"These images are not snapshots"? No kidding. (1)

Illserve (56215) | more than 5 years ago | (#28627223)

...and yet, it does. It's become so routine, so reliable, so well-understood and well-controlled, that doctors and researchers know they can rely on it as a matter of course. They still have to be aware of the errors and distortions that can arise, but that's true of every imaging or monitoring system, all the way down to the stethoscope and the fever thermometer.

The problem with the activation maps is precisely that one is NOT looking at an image, so there's no way to fine tune the algorithms. Therefore, fMRI is NOT well understood in the way that CT or MRI are.

Consider that in imaging, you have the luxury of comparing the output of a brain scan to the known physical structure of the brain. Is there a hippocampus? No? Well then it didn't work, go back and fiddle until you can show me a hippocampus.

In fMRI, apart from low level sensory corticies (where visual field mapping techniques can reproduce broad level retinotopic maps), researchers are operating in a vacuum in which there is no hard and fast error signal to fine tune the methods.

Science has to proceed very cautiously in such a situation. This is particularly true when one has hundreds of thousands of voxels to sift through because it's easy to find any pattern in noise, if you have enough noise.

So I would argue that fMRI offers a very different set of challenges compared to MRI and CT scans, and therefore it's very important to keep a sharp, critical eye on the statistics used, as these authors are doing.

To illustrate this point further, here is a link to a poster in which someone put a dead salmon into a magnet and found that (in the absence of proper statistical controls) its decomposing brain was apparently reacting to the emotional content of pictures:

http://prefrontal.org/files/posters/Bennett-Salmon-2009.pdf [prefrontal.org]

Re:"These images are not snapshots"? No kidding. (0)

Anonymous Coward | more than 5 years ago | (#28630387)

> http://prefrontal.org/files/posters/Bennett-Salmon-2009.pdf [prefrontal.org]
> We further argue that the vast majority of fMRI studies should be utilizing multiple comparisons correction as standard practice in the computation of their statistics.

Oh, wow. An abstract from HBM 2009 where the authors have "discovered" the multiple-comparison problem and conclude that one should control the family-wise error rate using methods that have been known to fMRI analysis for at least a decade. The subtitle is "An argument for multiple comparisons correction" as if anyone working in the field would accept results otherwise. Impressive work. Their references consist of two seminal articles from 1994 and 1996 addressing the same problem, solutions of which have all been implemented in all widely used analysis packages for ages. There must be a lot of idiots that get abstracts accepted to HBM.

Re:"These images are not snapshots"? No kidding. (1)

Agripa (139780) | more than 5 years ago | (#28635377)

Couldn't the image sampling be done synchronously with the heart beat for instance or is the integration time too long?

Re:"These images are not snapshots"? No kidding. (1)

jeffb (2.718) (1189693) | more than 5 years ago | (#28636277)

That's exactly what you have to do, and assume (usually safely) that every heart cycle is pretty much identical. We call it "cardiac gating". You can either do it "prospectively", which means triggering acquisition at a particular point in the cardiac cycle, or "retrospectively", where you acquire freely and then go back and pick out the acquisitions that happened at the cardiac phase you want.

It's still tricky, though, particularly for MRI, where you're generating a lot of electrical noise -- electrical monitoring (conventional ECG) just won't work. We use optical sensors. Of course, we're imaging mice with 600bpm pulse rates, which makes it trickier still.

For CT, I think each "exposure" we do is typically 10ms or less, which lets us get multiple phases even in a mouse. For MR, well, remember when I said the physics is over my head? Yeah, that. But I know we can routinely split the mouse cardiac cycle into 8 phases, and sometimes more. You're imaging for a pretty long time to do that, though -- collect views through many cardiac cycles at 0ms offset, then at 10ms offset, then 20, then...

Re:"These images are not snapshots"? No kidding. (1)

Ihlosi (895663) | more than 5 years ago | (#28635931)

For CT, we acquire a bunch of 2D images through you from different angles,

Wasn't that "a whole bunch of 1D images, which are then computed into 2D-slices, which are then assembled into 3D volume representations"?

Last time I checked, CTs acquired one-dimensional images. However, it's been a while, and I work in a different field of biomedical engineering, so I haven't really kept up with more recent developments.

Re:"These images are not snapshots"? No kidding. (1)

jeffb (2.718) (1189693) | more than 5 years ago | (#28636635)

Good catch. "We" (well, our actual researchers, not me) built a small-animal CT system that captures 2D images, rotating the animal instead of the gantry between views. That's very different from a clinical CT system.

However, those clinical scanners are getting wider. You can now get scanners that acquire 64 slices at a time -- instead of an N-pixel linear sensor, they use an N x 64-pixel sensor, and scan in a helical pattern. It's all about speed in the clinical arena.

Re:"These images are not snapshots"? No kidding. (1)

Ihlosi (895663) | more than 5 years ago | (#28647627)

Good catch. "We" (well, our actual researchers, not me) built a small-animal CT system that captures 2D images, rotating the animal instead of the gantry between views. That's very different from a clinical CT system.

Thinking about it - using a 2D-sensor is a logical evolution to get faster and better pictures. I mean, the very first generation didn't even use a linear sensor array, they used a single sensor that was moved in order to get the measurements at different points in space.

Then again, my last practical experience (as a patient) with a CT system was in the early 80s, when the whole procedure still took half an hour or more (at the same time, getting some MRI scans to three-and-a-half frickin' hours). Now, we're down to seconds for the CT and half an hours for the MRI.

Correlation is not Causation? (4, Insightful)

nerdup (523587) | more than 5 years ago | (#28625149)

Whoever tagged this story 'correlationisnotcausation' is a fucking idiot. You're not as smart as you think you are.

Re:Correlation is not Causation? (1)

jstults (1406161) | more than 5 years ago | (#28625245)

Especially since the topic is a controlled experiment, where it is actually possible (and proper) to infer a causal relationship. This isn't survey data on browsers, f'in slashtards.

Re:Correlation is not Causation? (0)

Anonymous Coward | more than 5 years ago | (#28636175)

Wrong. It is never possible to infer causation from correlation. Correlation can be due to a number of things -- one thing driving another directly or through an intermediary, both things being driven by something else, or possibly just coincidence (though statistical significance testing makes this more unlikely). Causation requires more, at the very least a timed relationship -- event A happens then event B happens, though this alone is still not enough to infer causation. True causation would require an experiment set up with a control, in one case trigger event A and see if event B happens and in the other case don't trigger A and see if event B happens, and then repeat many times to see if A really causes B.

Lite-Brite Phrenology (0)

Anonymous Coward | more than 5 years ago | (#28625639)

Just wanted to mention my favorite diss of fMRI - Lite-Brite Phrenology.

the pretty-picture effect (0)

Anonymous Coward | more than 5 years ago | (#28626521)

I suspect the pretty-picture effect is likely to generalize to just about any science, though I am only aware of this having been directly tested and confirmed in neuroscience (e.g. McCabe & Castel, 2007; Cognition). Although the philosophy behind peer review is sound, it still suffers from the fact that our peers are humans - encumbered by all manner of flawed reasoning. Unfortunately, one of those flaws is that we are easily compelled by impressive looking pictures - regardless of our expertise. Perhaps this is because we implcitly assume that impressive tools and impressive research are necessarily correlated. Sadly, they are not, and we are left with islands of extremely valuable fMRI (and equally EEG / ERP, MEG, DTI - what have you) research, floating amidst a host of absolute rubbish.

MRI is one huge ass magnet (1)

syousef (465911) | more than 5 years ago | (#28628301)

If little magnets were going to affect your brain, wouldn't anyone who'd had a brain scan end up a vegetable?

Of course it pays to sell idiots little magnets and claim all sorts of health benefits. Some may even benefit from a placebo effect. (It doesn't pay to try to sell them MRI machines...there are so few idiots THAT rich).

I think i'll remain skeptical unless more solid evidence turns up.

Re:MRI is one huge ass magnet (1)

DynaSoar (714234) | more than 5 years ago | (#28630575)

If little magnets were going to affect your brain, wouldn't anyone who'd had a brain scan end up a vegetable?

Of course it pays to sell idiots little magnets and claim all sorts of health benefits. Some may even benefit from a placebo effect. (It doesn't pay to try to sell them MRI machines...there are so few idiots THAT rich).

I think i'll remain skeptical unless more solid evidence turns up.

You're confusing sterngth with field density. An MRI is indeed huge assed, 0.5 to several tesla. But within any given cubic millimeter there's precious little power. In transcranial magnetic stimulation, there's modest power, but it's focused in a very small area.

These facts didn;t keep California from upholding a lawsuit by an "ex-psychic" against a hospital. She clails she lost her psychic ability to a MRI.

Re:MRI is one huge ass magnet (1)

jeffb (2.718) (1189693) | more than 5 years ago | (#28636791)

Well, sort of. The tesla is a measure of field intensity, and if you've got a 1.5T magnet, every cubic millimeter inside the bore experiences that same field intensity, and the same "energy density". (It's not like a small-bore 1.5T system has a "more concentrated" field than a wide-bore 1.5T system.) But it's a static field, and (to a first but very accurate approximation) static fields don't do much to living systems.

(As long as you hold still, that is. If you're in a very high-field magnet, you need to move carefully -- moving through a static field is equivalent to sitting still in a dynamic field, and moving your head too quickly in a 7T or 9T field can do some pretty weird things.)

The gradients in an MRI scanner do generate dynamic fields, and in fact there are software restrictions to keep you from changing those fields quickly enough to cause neurological problems. In normal operation, though, they don't produce any perceptible effects in the patient.

TMS imposes much higher deltas over a small area -- it's a fairly strong field that changes very quickly.

Contrasts and Multiple Subjects (1)

bmacs27 (1314285) | more than 5 years ago | (#28629709)

Disclaimer: I'm a neuroscientist/psychophysicist that studies vision. Traditionally, those that study vision or motor control have the lowest tolerance for squishiness. This is because what attracts us to the field is the fact that we can correlate human behavior with objective measurements such as joint angles, eye movements, and luminance.

fMRI, like all scientific tools comes with its caveats. First, as has been mentioned, it isn't measuring current at all, but rather oxygenation of blood. I disagree with the previous poster however that claims this has not been demonstrated to correlate with spiking behavior. That relationship has been shown, however there is a variable lag between spiking activity and the BOLD response.

Second, as you might imagine, just about your entire brain is involved with any task tested in the magnet. To get around this they use the concept of "contrasts". In other words, the subject performs two tasks: one baseline task which is designed to involve every part of the brain in the test condition, other than the psychological process of interest. For instance, if one were interested in speech areas you might have the subject report the category of object presented in an image. The baseline task, in that case, would be to passively view the same images. This allows you to subtract the activity, revealing areas that are more or less active in the test condition than during the baseline task. This is all well and good in the sorts of task my colleagues do, as it is fairly straightforward what the brain is doing when a light is flickering in a particular part of the visual field. When one is more interested in complicated social behavior, or emotional regulation, it is much more difficult and all the more necessary to careful validate your choice of conditions to contrast.

Third, as was mentioned earlier, for statistical or logistical reasons often the data must be averaged across subjects. IMHO this is BAD, like very bad. In vision typically we analyze the data independently for each subject, map their individual brains, and report both within subject and collapsed across subject data for activity in area X. In fields such as social neuroscience it is often the standard to effectively blur and distort the data to fit a "brain template" as the individual differences between convolutions in the brain are enormous. They are then in a position to average the contrasts for each of the subjects together in order to get an area that becomes significant. My largest problem with such a technique is that quite often they get a maximally significant between subjects area that is hardly at all active in any individual subject. To me, that screams "you're doing it wrong."

But, like I said, those of us in vision are often thought of hard scientists, but with unrealistic expectations of the rigor that should be employed in the rest of the brain sciences. It's a complicated problem, and to be fair many of these questions can't be answered in any other way. Vision and motor control are lucky that animal models such as the rhesus macaque are extremely similar to humans within those areas. The same can not be said for frontal cortex, for instance. We've also got about a 100 year head start on most of the rest of neuroscience.

In soviet russia... (0)

Anonymous Coward | more than 5 years ago | (#28629753)

MRI f you!

I said it, I did (1)

DynaSoar (714234) | more than 5 years ago | (#28630533)

Most of my psychology colleagues have no idea what they're looking at in fMRI. They assume if it lights up, it's making something go. They may know full well that neural activation can be excitatory or inhibitory, but fail to make the connection and figure out that what's lighting up may be de-activation. Both the gas pedal and the brakes appear the same to fMRI and nobody can tell which is which with this technology alone.

Even fewer even bother to try to grasp the math behind the analysis technique, statistical probability mapping. Every cubic pixel ("voxel") has to be compared to every one of its neighbors across the multiple data collections in each condition, and a T test applied. In order to prevent artifactual results due to this massive amount of statistical testing an error correcting normalization is applied. Statistical results of 0.05 or 5% are considered the limit for acceptable results. With the correction factor applied, each voxel that lights up is passing a statistical test with anywhere up to 22 digits below the zero that I've seen myself. Their lighting-up numbers are more far fetched than being hit by a falling meteor.

They almost invariably fail to mention areas that work with an area of their interest but fail to light up when their target does.

The problem extends beyond just the researchers. A recent article in the Proceedings of the National Academy was filled with these errors yet has become a part of a well respected body of works, poisoning it and giving others cause to continue believing their fallacies and compounding them with works justified by this one.

Response paper to Voodoo Correlations (1)

daenris (892027) | more than 5 years ago | (#28636295)

Anyone who is actually interested may want to check out one response paper to the Vul Voodoo Correlations paper which points out a number of problems that Vul himself has in his analysis. http://www.scn.ucla.edu/pdf/LiebermanBerkmanWager(invitedreply).pdf [ucla.edu]

Re: (1)

clint999 (1277046) | more than 5 years ago | (#28732173)

If little magnets were going to affect your brain, wouldn't anyone who'd had a brain scan end up a vegetable?Of course it pays to sell idiots little magnets and claim all sorts of health benefits. Some may even benefit from a placebo effect. (It doesn't pay to try to sell them MRI machines...there are so few idiots THAT rich).I think i'll remain skeptical unless more solid evidence turns up.

Re: (1)

clint999 (1277046) | more than 5 years ago | (#28734569)

If little magnets were going to affect your brain, wouldn't anyone who'd had a brain scan end up a vegetable?Of course it pays to sell idiots little magnets and claim all sorts of health benefits. Some may even benefit from a placebo effect. (It doesn't pay to try to sell them MRI machines...there are so few idiots THAT rich).I think i'll remain skeptical unless more solid evidence turns up.
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