What is a Brain Area?

What is a "brain area"? More recently, I have become aware of the inadequateness of the concept of "brain area", or at any rate, to call into question the basis for such a concept. This basis is three-fold, as noted by Felleman/van Essen: cortical areas (or in general, brain areas) are defined by 1) connectivity, 2) functional maps, and 3) chemical or architectonic signatures. However, for the most part, parcellations of the primate (and non-primate) brain have been based on studies using Nissl- or myelin-stained material that are over a century old, and investigators have come up with widely different parcellation schemes for the brain, which in my opinion, is a prominent warning sign that the notion of "cortical area" is ill-defined. Further anatomical studies of the brain have confirmed this point to me. And so, while I recognize the utility to conventionally naming different brain areas on the basis of Nissl-stained material or otherwise, I do not believe we currently possess an adequate conceptual understanding of what really constitutes a "brain area". In early sensori-motor areas, this concept seems applicable since we are talking about mappings from sensory receptor sheets onto the cortex, which get mapped onto well-defined areas of the brain, but other areas of the brain are not like this, and there is no reason a priori to expect that these association and limbic parts of the brain should be nicely parcellated into anything like discrete non-overlapping brain areas.

Part of the problem involves considering useful alteratives to this notion of discrete non-overlapping brain areas which is prevalent in the neuroscience community, and which heavily biases interpretions of experiments. It is largely a conceptual problem, but I am confident that a revolution in our notion of "brain area" will be forthcoming in the near future. Such an overhaul in this precious concept is requisite to a better understanding of the brain.

What I find amusing is that neuroscience textbooks never address this conceptual issue, though it is widely recognized by many prominent neuroscientists as a central problem. This has the peculiar effect that students of neuroscience often learn about their subject, thinking that all of the fundamental conceptual issues have been worked out and that the field of neuroscience rests on a firm foundation. This is not the case, and I would not be surprised if this shaky foundation crumbles, and that many of the "mysteries" of the brain's organization and function, when viewed in a new light and a new foundation, do not seem that mysterious after all, but rather obey a very precise and well-defined logic and reason.

The observation that the concept of "brain area" is ill-defined means, in part, that current attempts to analyze whole-brain connectivity using graph theory are based on incorrect data and incorrect assumptions, since we may legitimately question whether the nodes in the graph have any real meaning. So claims like "the brain is a small-world network" purported by some are empty, and are merely the consequence of following the recent fad in "network science", where anyone and everyone attempts to show that their favorite system is a so-called small-world network. How unoriginal and blase! If only these people could think for themselves instead of parroting the latest fad. The worst part of it is when these people actually publish such nonsense since it misleads other people (usually laymen, but also some neuroscientists) who don't know any better.

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!