Brain connectivity levels are equal in all mammals, including humans: study
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I wouldn’t be surprised if a dead salmon also has “equal” connectivity: https://www.wired.com/2009/09/fmrisalmon/
Your criticism reads like someone accusing economists of being outrageously misleading when they don't sample individual households but measure macro indicators. It's like saying Ramon y cajal was ridiculous because he couldn't image the neuropil effectively. Or like saying early optogenetics experiments were ridiculous because who knows if you're stimulating a neuron in a realistic manner?
And in any case, it's true that synapses are comically small relative to voxel size, but we also have some reasonable information about projection patterns and synapse number from various tracer or rabies studies with which you are no doubt familiar.
I haven't read the nature paper the press release is about and I'm not a huge fan of many d/fMRI practices or derived claims. And I've worked with enough mammalian dwi data to be skeptical of specific connection claims. But this strikes me as a rather interesting result even if you can't measure all the synapses at the right resolution: either the tractography method has connectivity conservation artifacts baked in, or there's something interesting going on.
> When comparing and contrasting these devices it is important to look at the temporal resolution, spatial resolution, and the degree of immobility.
This statement is outrageous, and an example of how some scientists gain the ire of their colleagues by exaggerating their findings and misleading the press.
I thought this was a little over the top. Its nothing like, say, the laws of gravitation. Its a regularity observed between species in a specific taxon on a specific planet at a specific time. And it was just one study.
Still, I think the research is really cool. And I wonder whether this is an emergent property of how mammalian brains develop, or whether the regularity is the result of evolutionary pressure (because, i.e. there is selection for a specific connectivity profile).
https://en.wikipedia.org/wiki/Corpus_callosum
This seems to put into question their statement about "all mammals", but I haven't read the article, so maybe they actually mean placental mammals only.
Monotreme mammals don't have nipples.
I've read almost all her books and papers and she is awesome! Such an inspiring quality of thought and writing. And the way she deals with critics on her site is exemplary.
Waylon Smithers : Uh, Sir? Phrenology was dismissed as quackery 160 years ago.
Mr. Burns : Of course you'd say that... you have the brainpan of a stagecoach tilter!
This seems consistent with how my mind works. It takes an extra tax of effort for me to remember things with "emotional" or sentimental components to them, but I'll be a walking encyclopedia of knowledge with the necessary critical thinking capabilities to apply what I know.
Would be interesting if brain scans yielded similar patterns between the two of us. Wouldn't be a surprise either.
The data from large samples points the other way here. Every measurable trait that you might describe as smart (like ability in math, or music, or languages, or remembering cards) correlates positively with the others.
The brain already has a large metabolic cost, even dominating the total metabolic needs of the body during early development (https://www.pnas.org/content/111/36/13010).
I've long held a suspicion that the main reason IQ has a normal distribution is not anything to do with brain architecture per se (i.e. it's not a polygenetic trait that builds some brains out of better or worse genes than others) but rather that the brain is limited in its ability to become more complex by a proportional need for metabolic energy; and that the metabolic efficiency of human bodies is a polygenetic trait, such that the body systems required for metabolism are built from better or worse genes, that will thus get energy to the brain more or less efficiently. (This would explain why the brains of higher-IQ people don't look any different under histological analysis—there's nothing genetically or epigenetically different in them, in terms of what proteins are being expressed. Brains are brains. The differences that determine brain complexity would be elsewhere, in their bodies!)
This also, in my thinking, explains the Flynn effect: anything that we as a civilization do to get rid of an obstacle in the way of our metabolism—e.g. decreasing parasite load, stopping exposure to environmental toxins like lead or pollution, fortifying foods with vitamins, etc.—should bring the average human living within civilization ever closer to "peak performance" of the human body's metabolic system, and thus give the brain more "headroom" [hah!] to become more complex.
Of course, the Flynn effect says that this only happens to new generations (who grow up with such advances in place); not to older people (who don't grow up with such advances, but are exposed to them later in life.) I would suppose we just have some epigenetic triggers that "give up" on brain complexification after a certain point in life, probably assuming that whatever equilibrium the brain has reached between growth and apoptosis-through-energy-starvation by that point, is the final limit.
Alternately, as proposed here (https://en.wikipedia.org/wiki/Synaptic_pruning#Energy_saving...), the body might do well-enough to feed the brain when that's the body's only job; but not well-enough to feed the brain when both the brain and the sexual organs (and all descendent demands, e.g. pregnancy) are fighting over metabolic energy. So the "throttle" on the brain's complexification becomes "choked off" during puberty, such that the resultant metabolic energy can be reserved for reproduction. (Under that hypothesis, preventing puberty might result in higher-IQ people. It apparently worked in rats!)
[1] https://www.researchgate.net/publication/342022024_Conservat...
[0] https://drops.dagstuhl.de/opus/volltexte/2019/10358/pdf/dagr...
Is MRI really that high-resolution now?
There's a lot of interesting stuff to read about Connectomes[0] on wikipedia if you're curious about the mapping thing. I don't think they have an actual network map there, but in the initial pages of the paper they describe using MRI measurements to assess 200 areas they split the brain into ("normalized to 200 voxels per brain"), and they test their MRI methods by re-creating two tangentially related measurements which attach importance to geometric constraints of the brain.
They mention: "Note that, as tractography does not actually measure axons but rather axonal bundles and fascicles, our length estimate reflects the wiring length of the macro-scale network." So it's more akin to getting a mapping of Earths (as in, each animal is one) and splitting it into 200 voxels, then looking at the density of fiber optic cables laid out, for many types of "Earths". So they don't see each strand but the bundles, which could mean that they don't know how much "data" actually goes through but they do know what bundles go where, which is more the point of connectivity.
Then they go on to notice that there's overall little change of density across the measurements (40% maximum over 4 orders of magnitude of volumes) even though there are different structures (some might have only one one dominating continent while others have two, for example), and that within each "family" of measurements there's consistency in measured density across their samples.
They also mention: "Results suggest that intra-hemispheric connectivity compensates for poorer inter-hemispheric connectivity, maintaining the overall connectivity." Which I think is something that at least from a functional standpoint has started to be looked at for humans (in studies like this[1]) but I don't know if any other study has done such an analysis as systematically as these guys, and I don't think ANY other study has done so across so many species and orders of magnitude of brain volumes.
(I am happy to be corrected by any actually-knowledgeable person passing by, if they are so kind as to strike down any mistake)
[0] https://en.wikipedia.org/wiki/Connectome
[1] https://www.sciencedaily.com/releases/2019/11/191120070710.h...