Neural networks: Why larger brains are more susceptible to mental illnesses

July 21, 2016
Macaque brain showing the inter-areal network. Nodes roughly correspond to actual areas, thickness of lines proportional to the logarithm of the numbers of axons. Credit: Szabolcs Horvát

In humans and other mammals, the cerebral cortex is responsible for sensory, motor, and cognitive functions. Understanding the organization of the neuronal networks in the cortex should provide insights into the computations that they carry out. A study publishing on July 21st in open access journal PLOS Biology shows that the global architecture of the cortical networks in primates (with large brains) and rodents (with small brains) is organized by common principles. Despite the overall network invariances, primate brains have much weaker long-distance connections, which could explain why large brains are more susceptible to certain mental illnesses such as schizophrenia and Alzheimer disease.

In earlier work, Zoltán Toroczkai, from the University of Notre-Dame, USA, Mária Ercsey-Ravasz, from Babes-Bolyai University, Romania and Henry Kennedy, from the University Lyon, France, and colleagues combined tracing studies in macaques, which visualize connections in the , with network theory to show that the cortical network structure in this primate is governed by the so-called exponential distance rule (EDR).

The EDR describes a consistent relationship between distances and connection strength. Consistent with the tracing results, the EDR predicts that there are many fewer long-range axons (nerve fibers that function as transmission lines of the nervous system) than short ones, and this can be quantified by a mathematical equation. At the level of cortical areas (such as visual or ) examined by the tracing studies, this means the closer two areas are to each other, the more connections exist between them.

In this study, the researchers compare the features of the cortical networks in the macaque - a mammal with a large cortex - with those in the mouse, with its much smaller cortex. They used detailed tracing data to quantify connections between functional areas, and those formed the basis for the analysis. Despite the substantial differences in the cortex size between the species and other apparent differences in cortex organization, they found that the fundamental statistical features of all networks followed the EDR.

Based on these results, the researchers hypothesize that the EDR describes an effective design principle that remains constant during the evolution of mammalian brains of different sizes. They present mathematical arguments that support the universal applicability of the EDR as a governing principle of cortical connectivity, as well as further experimental support from high-resolution tracer experiments in small brain areas from macaque, mouse, and mouse lemur (a primate with a very small brain).

Their results, the researchers conclude, "suggest that the EDR plays a key role across the mammalian order to optimize the layout of the inter-areal cortical network allowing larger-brained animals to maintain communication efficiencies combined with increased neuron numbers".

As the EDR predicts and the tracing data here confirm, neuronal connections weaken exponentially with distance. Assuming the EDR can be applied to all mammalian brains, this suggests that long-distance connections could be quite weak in the human cortex, which is approximately five times larger than that of the macaque. If true, the researchers say, one could speculate that the low weight of human long-range connections may contribute to an increased susceptibility to disconnection syndromes, such as have been proposed for Alzheimer disease and schizophrenia".

Explore further: New research reveals brain network connections

More information: Horvát S, Gamanut R, Ercsey-Ravasz M, Magrou L, Gamanut B, Van Essen DC, et al. (2016) Spatial Embedding and Wiring Cost Constrain the Functional Layout of the Cortical Network of Rodents and Primates. PLoS Biol 14(7): e1002512. DOI: 10.1371/journal.pbio.1002512

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SoylentGrin
5 / 5 (4) Jul 21, 2016
I wonder, if an AI emerged from a global-sized network, does the exponential distance rule mean that the entity would be insane from the start?
TheGhostofOtto1923
1 / 5 (1) Jul 21, 2016
This is more evidence that our brains are unnaturally large, and that dysfunction is more endemic and more problematic than realized.

What would society be like if genetic deformity could be corrected and damage could be prevented when brains are most vulnerable, ie when they are still in the womb?

Reproduction should be a priviledge not a right. Women should prove they are responsible enough before they are given the ability to potentially ruin the entire lifetime of another person because they cant refrain from smoking, drinking, or doing drugs while pregnant.

We now have the ability to monitor the health of a fetus remotely, in realtime. And we can immediately detect whether an expectant mother is damaging it.

And we can immediately arrest these women and keep them in a clinic until they give birth.
TheGhostofOtto1923
3 / 5 (2) Jul 21, 2016
an AI emerged from a global-sized network, does the exponential distance rule mean that the entity would be insane from the start?
Why are you assuming that we are designing AI brains with all the structural defects that human brains have?

We design our machines to compensate and enhance our limitations. AI brains are designed from scratch to be more robust, more dependable, and far more capable.

And unlike our brains we can incorporate inprovements from lessons learned. This is intelligent evolution, much superior to the natural kind.
Edenlegaia
3.5 / 5 (2) Jul 22, 2016
We design our machines to compensate and enhance our limitations. AI brains are designed from scratch to be more robust, more dependable, and far more capable.

And unlike our brains we can incorporate inprovements from lessons learned. This is intelligent evolution, much superior to the natural kind.


Beware the intelligent evolution and his so called superiority though. Many simulations, many experiments and so on will have to be done before claiming such thing with certainty. I mean....we still have many things to learn from Nature and how it designed itself the way it did.....entirely.
That "intelligent evolution" is just our way to do things outside of the natural road. A Superior Brain born from Intelligent Evolution exploding after 36000 hours of use would hardly be a good thing.......and would need more work. No doubt.
antialias_physorg
3 / 5 (3) Jul 22, 2016
mean....we still have many things to learn from Nature and how it designed itself the way it did.....entirely.

We should keep in mind that nature does not 'design' on the basis making stuff the best possible but on the basis of making it barely good enough (e.g.. if a plant is 0.002% efficient at doing X and all competing plants are only 0.001% efficient then all evolutionary pressure ceases for that plant until one of the others catches up.)

So while there is still a lot left to learn nature by no means is the 'ultimate designer'.

A Superior Brain born from Intelligent Evolution exploding after 36000 hours of use would hardly be a good thing

If it's cheap enough and serves its purpose before the time is up then it's good enough.
TheGhostofOtto1923
3.7 / 5 (3) Jul 22, 2016
That "intelligent evolution" is just our way to do things outside of the natural road. A Superior Brain born from Intelligent Evolution exploding after 36000 hours of use would hardly be a good thing
Human brains begin to deterioriate shortly after adolescence. They forget, they get confused and distracted, they are subject to damage and addiction.

They have made themselves obsolete which is why they are busy figuring out ways of replacing themselves.
If it's cheap enough and serves its purpose before the time is up then it's good enough
Hey just like people, right aa?

Right?
winthrom
5 / 5 (1) Jul 24, 2016
What about whales and elephants. Do they have susceptibilities we missed?
epoxy
Jul 24, 2016
This comment has been removed by a moderator.
epoxy
Jul 24, 2016
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