Wednesday, January 17, 2007

3D Brain

I recently wanted to see where acetylcholinesterase (AChE), the enzyme that breaks down the neurotransmitter acetylcholine, is located in the brain. And specifically, I wanted to see the distribution of AChE in 3D. This data is available online (for the mouse brain) at both the Allen Brain Atlas and BrainMaps.org, so I went to both sites to see the AChE distribution in 3D. Here I was veritably shocked by the comparison. First, let's look at the Allen Brain Atlas 3D file for AChE, which is the big yellow amorphous blob shown on the right


Then I went to BrainMaps.org and obtained the 3D file for the AChE distribution in the mouse brain, and this is what it looks like in the figure to the right. Note that in both of these figures, the viewpoint is oblique lateral, with anterior pointing to the left and spinal cord on the right.

Understandably, I was shocked by the difference in quality between the two 3D distributions. First off, I have difficulty interpreting the first figure (from the Allen Brain Atlas) because it is just a big amorphous blob of yellow spots.

Secondly, and more troublesome, is that the first figure (from the Allen Brain Atlas) is just plain incorrect. The distribution of AChE, in 2D, looks like the figure at the right. Here we see that AChE is located primarily in the striatum (the dark red color). The striatum is clearly discernible in the second figure (from BrainMaps.org) but is not visible at all in the first figure (from the Allen Brain Atlas).

And here's the kicker: it's not just AChE where the Allen Brain Atlas data is completely wrong!   Nonetheless, it's not the objective of this article to be critical of the Allen Brain Atlas since I have done this elsewhere. I will only note that $40 million should have resulted in decent 3D reconstructions, and better quality in situ data. The fact that so much money was poured into this project and it just produced a pile of crap still astounds me, since it goes against the GIGO (garbage in, garbage out) rule, or at least requires a modification, courtesy of Paul Allen: "$40 million in, garbage out". Granted, it's not as euphonious as GIGO, but it works.

In any event, the objective of this article is to consider 3D brains and how to render 3D brain structures and distributions. We have polygonal modeling, which is currently employed at brainmaps.org, but this has the drawback that surfaces need to be defined, which may not be practical for continuous distributions. Surfaces may be considered "isosurfaces" of a continuous distribution, but what if we want to view the complete distribution in 3D? Then we're talking about volumetric visualization and not surface visualization (unless you're talking about isosurfaces of a volume).

Surfels are one possibility too, but suffer from poor rendering and performance issues. So what we are left with, apparently, is polygons as the best way to visualize the brain in 3D.

The 3D brains used in the figures above, and more, are located at the 3D Brain Objects Database at BrainMaps.org. Note that you can view the 3D brains directly in your browser!

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3 Comments:

Blogger Albert said...

I agree on "polygons", or meshes, being about the best means to represent brain anatomy. And so do most of my colleagues. But beware: [1] segmentation, a prerequisite to 3D modeling with meshes, is in the eye of the beholder (or the parameters of his algorithm); and [2] most publications don't specify how many rounds of decimation+subsurfacing were applied to the presented models until they looked "right". Most 3D modeling out there are, simply put, fake.

There is yet another big unsolved problem: there are neither proper nor standard (as a lesser evil) comparator algorithms for 3D structures. Much less for averaging several 3D structures. On the other hand, for voxel clouds (or image stacks, as opposed to 3D meshes), there are numerous registration techniques which kind of work.

Such comparator algorithms are very useful not really for creating averaged brains (I never saw value in them, they are just combined noise), but rather for structure identification: given any two brains, identify and classify the same brain volumes.

9:52 AM  
Blogger neubrain said...

Segmentation is definitely a big problem, particularly when fuzzy or ambiguous boundaries are involved. I have the same issue with point clouds as you do, and also they are much harder to visually appreciate, compared to surfaces. I'm not sure what the best solution is.

6:42 PM  
Blogger Belladonna said...

Thanks for the heads up about the weaknesses of the Allen Brain Atlas and getting me pointed in some new directions.

I suspect there are plenty of people outside of the loop of serious brain study who simply would not be able to make the distinction.

I have a question for you - are you familiar with any specific research on brains of patients with disassociative disorders?

I used to work community mental health and have seen plenty of stuff on schizophrenia and other psychotic disorders, but now I'm trying to add to my files with stuff on PTSD / DID.

12:16 PM  

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