"We discovered that brain connectivity — namely the efficiency of information transfer through the neural network — does not depend on either the size or structure of any specific brain. In other words, the brains of all mammals, from tiny mice through humans to large bulls and dolphins, exhibit equal connectivity, and information travels with the same efficiency within them."
I find this quote as important as yours:
"This mechanism ensures that high connectivity in a specific area of the brain, possibly manifested through some special talent (e.g. sports or music) is always countered by relatively low connectivity in another part of the brain"
I’m surprised that an MRI scan can allow a synapse-level reconstruction. So surprised that I suspect I’ve misunderstood (I can’t read the original paper — I probably wouldn’t understand it even if it wasn’t paywalled).
They did diffusion tensor imaging. What this does, using MRI, is determine the local anisotropy of water flow in each voxel. You assume that this anisotropy aligns with with the axis of axons, since they limit the diffusion of water across their axis (water diffuses along them). You can then use the principal directions of the diffusion tensor to estimate in what direction the water, i.e. the axons are "flowing" giving you an approximate picture of how axons connect different parts of the brain.
MRI is ~5 orders of magnitude less precise than EM. Not even close to cellular resolution, let along single axon resolution. You can only see axon tracts, where thousands of axons may make up one pixel.
It's a bit of a tough read for outsiders (which I am), but with some basic understanding of the brain and a few lookups I think the paper is actually pretty readable in the end, so I'm attempting a quick explanation.
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)
MRI can’t do imaging at synapse level, even high powered on small animals. This has nothing to do with connectivity between neurons. It is more like they do correlations on correlations, and find mammals share some basic connection pattern (by correlation measurements). It might surprise those who don’t believe in evolution
I found this interesting: "Our study revealed a universal law: Conservation of Brain Connectivity," Prof. Assaf concludes. "This law denotes that the efficiency of information transfer in the brain's neural network is equal in all mammals, including humans. We also discovered a compensation mechanism which balances the connectivity in every mammalian brain. This mechanism ensures that high connectivity in a specific area of the brain, possibly manifested through some special talent (e.g. sports or music) is always countered by relatively low connectivity in another part of the brain. In future projects we will investigate how the brain compensates for the enhanced connectivity associated with specific capabilities and learning processes."
There is also the, rather terrifying, concept of focus from Vernon Vinge's Deepness in the Sky where brains are modified to turn people into intelligent single-purpose appliances/microservices:
Small sample size, but this is consistent with what I've observed in some specialized people... For example, I have an uncle that is absolutely brilliant. He's an excellent lawyer and can remember any fact that even slightly interests him. He's simultaneously the most absentminded person I've ever met - he forgets meetings, is always mindlessly snacking (despite being on a diet for pre-diabetes) and generally forgetting things that he doesn't deem to be important. It always feels like he traded something that "normal" humans have for his smarts. It might just be mild autism, but it seems to me like savant autism is an extreme example of this effect.
> Small sample size, but this is consistent with what I've observed in some specialized people... For example, I have an uncle that is absolutely brilliant. He's an excellent lawyer and can remember any fact that even slightly interests him. He's simultaneously the most absentminded person I've ever met - he forgets meetings, is always mindlessly snacking (despite being on a diet for pre-diabetes) and generally forgetting things that he doesn't deem to be important. It always feels like he traded something that "normal" humans have for his smarts. It might just be mild autism, but it seems to me like savant autism is an extreme example of this effect.
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.
> Small sample size, but this is consistent with what I've observed in some specialized people
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.
I wonder whether said balancing mechanism can be bypassed to achieve broader connectivity, and if so, what the consequences of that are. Sounds like they do not know the specific mechanism yet.
I would guess one change would be a higher metabolic demand on glucose + oxygen, beyond that which the body can supply. Like a CPU that requires more peak power than its motherboard VRMs + PSU are capable of drawing.
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!)
It's a bit of a tortured metaphor, but I think RPG stats are a fairly good analogy. Most people or characters get their stats distributed fairly evenly, and get about the same amount of points to distribute, whereas some people get their stats distributed unevenly or have more or less points to distribute. Someone with a high number of points also distributed unevenly enough to excel in one area would be a genius.
"Our study revealed a universal law: Conservation of Brain Connectivity," Prof. Assaf concludes. "This law denotes that the efficiency of information transfer in the brain's neural network is equal in all mammals, including humans."
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).
If someone gets split brain surgery, does this law mean they stop being a mammal? Personally I think you should get your nipples removed if you want to stop being a mammal.
It's a good question, but the article claims there's a compensation: "when connectivity between the hemispheres is high, connectivity within each hemisphere is relatively low, and vice versa". There's no reason that couldn't apply to someone with a split brain or a single hemisphere, at least after given time to adapt to the surgery.
Marsupials and monotremes lack the corpus callosum that facilities communication between left and right brain in placental mammal, so it is as if they already had this surgery.
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.
Most laws in biology or evolutionary theory are proposed by philosophers of science or by scientists trying to impress philosophers of science. But in this matter I am deeply influenced by Elizabeth Lloyd's book "The Structure and Confirmation of Evolutionary Theory" (https://press.princeton.edu/books/paperback/9780691000466/th...)
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.
This is outrageously misleading. To make a claim about the number of synapses between neurons based on MRI data is completely unwarranted. Voxel size (single volumetric pixel) in MRI is approximately 1mm, while synapse size is way less than a micron. You need resolution per pixel on the order of 10s of nanometers to identify synapses.
And when you put the brain size into consideration, the results for some mammals might not too far a way from a fuzzy mosaic while human’s like a 10 k pixels image
Would it be fair to say that the conclusions were that "large scale processing blocks have similar connection complexity across mammals, regardless of brain size?" -- obviously including that the complexity and/or function of the regions may be wildly different.
Yes, their statements should be about “large scale processing blocks,“ to make claims to the public about the number of synapses between neurons being conserved is really unfortunate and cannot be assessed in their data
Surely there's something to learn here though. I haven't read the original paper but a quantity that's preserved across brain scales is either an artifact or a neat insight.
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.
OP suggests that the spatial resolution of existing MRI neuroimaging capabilities is insufficient to observe or so characterize or so generalize about neuronal activity in mammalian species. fNIRS (functional near-infrared spectroscopy) is one alternative neuroimaging capability that we could compare fMRI with according to the criteria for comparison suggested in the cited Wikipedia article: "temporal resolution, spatial resolution, and the degree of immobility".
Thanks for the thoughtful reply. I’m highly concerned that there are artifacts baked in. I’ll readily admit that I’m a systems neuroscientist and am skeptical of DWI in general. I appreciate that they included Supp. Fig 13, with a comparison of DWI findings to cellular-level resolution projectome tracing from Allen Institute. Supp Fig 13 does not inspire confidence.
“In other words, information travels from one location to another through the same number of synapses.” —-Yaniv Assaf
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.
Talking about brain connectivity being equal in all mammals using MRI? This is a joke! The resolution of MRI is too big to map the connectivity at the level of single synapses. Only Electron Microscopes are known to achieve that resolution and so far mapping a mammalian brain with Electron Microscope is very much impossible because of several reasons [0]
56 comments
[ 3.5 ms ] story [ 128 ms ] threadIs 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...
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!
https://en.wikipedia.org/wiki/A_Deepness_in_the_Sky
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...
[2] https://www.nature.com/articles/s41593-020-0641-7
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/Split-brain
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.
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.
[0] https://drops.dagstuhl.de/opus/volltexte/2019/10358/pdf/dagr...