When Blind People Do Algebra, the Brain's Visual Areas Light Up (npr.org)

People born without sight appear to solve math problems using visual areas of the brain. NPR has a fascinating report on this: A functional MRI study of 17 people blind since birth found that areas of visual cortex became active when the participants were asked to solve algebra problems, a team from Johns Hopkins reports in the Proceedings of the National Academy of Sciences. "And as the equations get harder and harder, activity in these areas goes up in a blind person," says Marina Bedny, an author of the study and an assistant professor in the department of psychological and brain sciences at Johns Hopkins University. In 19 sighted people doing the same problems, visual areas of the brain showed no increase in activity. "That really suggests that yes, blind individuals appear to be doing math with their visual cortex," Bedny says. The findings, published online Friday, challenge the idea that brain tissue intended for one function is limited to tasks that are closely related.

Comments

GPU acceleration

[Anonymous Coward]

So they're using their GPU to accelerate math processing?
Do they support CUDA or OpenCL?

Re:GPU acceleration

[fulldecent]

> Do they support CUDA or OpenCL?

Is a question with serious ethical implications.

Re:GPU acceleration

[Rosco P. Coltrane]

More importantly, can you stick a bunch of blind people in a room and get them to mine bitcoins?

Re: GPU acceleration

[Anonymous Coward]

I think this is actually a good analogy.

Graphics processors can be used to do math, it makes sense that the brain would repurpose nonfunctional areas for other things.

Think about it, the brain has all these neurons capable of doing all these calculations to recognize objects rotated at various angles... It would make sense to repurpose them for something else if they aren't being used, for example because your optic nerve is fried and no visualnsensory input is coming to your brain.

It's clear that the brain has this capability.

Needs to be Debugged

[Roger W Moore]

So they're using their GPU to accelerate math processing?

Perhaps, or perhaps not. Given the usual submission to publication lead times on journals I suspect they have some debugging to do.

Re:Perhaps...

[jellomizer]

I am curious if you compared with normal population. Determine if they are Visual, Auditory, Tactile learners, Have them do the work, and see what parts of the brain they use, and compare that against the blind person.

Just because they are blind, it doesn't mean that they cannot be a Visual Learner. It is just harder for them because they don't get the visual stimula.

Re:Bullshit

[mark-t]

No, it has not. It was shown fairly recently that a certain fairly common statistical error in the software could mislocate whet activity is occurring and perhaps as much as 10% of the some 40,000 or so research papers in existence that use results from fmri as the basis for a conclusion may in fact be faulty. However, the premise behind fmri is still entirely valid, and software bugs notwithstanding is continually getting better.

Re:Perhaps...

[Bengie]

I visualize all kinds of logical problems, which conflicts with my navigational abilities. I have a hard time thinking and walking. Sometimes my balance is thrown off because what I'm "seeing" and what I'm feeling don't match. I would not describe what I see as normal 3d images. I see "n dimensional" images where "n" is the number of variables.

If I'm thinking really hard, even my hearing and touch gets hijacked and I can experience strange sensations. An example would be when thinking about how network flows interfere with each other. The rate of packets being sent can be thought of as "sound", then all of the "sound frequencies" of the network flows converge on a single point, and then I visualize the resulting sound of these overlapping frequencies and can "see" where peaks get too spiky, resulting in jitter or packetloss. I've done this several times when trying to visualize why I was getting incredibly rare transient packetloss. Effectively microbusts of roughly synchronized senders. Where the "n" dimensional comes in is I can see multiple versions of these at the same time, like many steady flows, many starting flows, etc etc. I can think of the corner cases ahead of time and see all of these cases concurrently without having to rethink of the issue for each case.

I just used networking as an example, but i'm a programmer and do this same thing to pretty much all problems.

Re:That's not the surprise

[omnichad]

They're not saying it's not lighting up for everyone. They're saying that there's no increase in visual cortex activity. I find that if I'm sitting and thinking about a complex math or visual-spatial problem, I stop seeing somewhat. I'm just unable to notice what's going on around me. It's likely that sighted people are just reducing their real-world visual processing to make way for the other computation.

Re:Bullshit

[mark-t]

No worries... I realized as soon as I as your lmgtfy link what the misunderstanding was.

The report by the PNAS that said that fmri reports are invalidwas actually retracted shortly thereafter as they realized that the flaw was within a software bug that would not affect all of the results in the same way:

However, there is one number I regret [announcing publicy]: 40,000. In trying to refer to the importance of the fMRI discipline, we used an estimate of the entire fMRI literature as number of studies impinged by our findings. In our defense, we found problems with cluster size inference in general (severe for P=0.01 CDT, biased for P=0.001), the dominant inference method, suggesting the majority of the literature was affected. The number in the impact statement, however, has been picked up by popular press and fed a small twitterstorm. Hence, I feel it's my duty to make at least a rough estimate of "How many articles does our work affect?". I'm not a bibliometrician, and this really a rough-and-ready exercise, but it hopefully gives a sense of the order of magnitude of the problem.

The analysis code (in Matlab) is laid out below, but here is the skinny: Based on some reasonable probabilistic computations, but perhaps fragile samples of the literature, I estimate about 15,000 papers use cluster size inference with correction for multiple testing; of these, around 3,500 use a CDT of P=0.01. 3,500 is about 9% of the entire literature, or perhaps more usefully, 11% of papers containing original data. (Of course some of these 15,000 or 3,500 might use nonparametric inference, but it's unfortunately rare for fMRI -- in contrast, it's the default inference tool for structural VBM/DTI analyses in FSL).

I frankly thought this number would be higher, but didn't realise the large proportion of studies that never used any sort of multiple testing correction. (Can't have inflated corrected significances if you don't correct!). These calculations suggest 13,000 papers used no multiple testing correction. Of course some of these may be using regions of interest or sub-volume analyses, but it's a scant few (i.e. clinical trial style outcome) that have absolutely no multiplicity at all. Our paper isn't directly about this group, but for publications that used the folk multiple testing correction, P10, our paper shows this approach has familywise error rates well in excess of 50%.

So, are we saying 3,500 papers are "wrong"? It depends. Our results suggest CDT P=0.01 results have inflated P-values, but each study must be examined... if the effects are really strong, it likely doesn't matter if the P-values are biased, and the scientific inference will remain unchanged. But if the effects are really weak, then the results might indeed be consistent with noise. And, what about those 13,000 papers with no correction, especially common in the earlier literature? No, they shouldn't be discarded out of hand either, but a particularly jaded eye is needed for those works, especially when comparing them to new references with improved methodological standards.

So in fact, all that the study that found the software bug proved is that we need to double-check findings when they are made by a computer.... it doesn't mean that the findings are wrong, only that we should be rightly skeptical. Further, it means that fmri studies done *since* this discovery are actually more likely to have correct conclusions than ever before.

Unsurprising

[maiden_taiwan]

Neuroscientists have known for years that the brain has few "dedicated" areas for any particular function, such as math. Instead, many collections of neurons can accomplish the same function. This is called degeneracy. (Terrible name, I know... let the jokes about degenerate mathematicians begin....)

Also, the brain doesn't "light up" as if were sitting around idle and suddenly leaps into action. The whole brain is active all the time. This is called intrinsic brain activity.

Anyone who talks about brain areas "lighting up," or believes that each region of the brain has a dedicated function, is at least a decade behind modern neuroscience.