Maturation proceeds inside out with the regions closest to the world (lower sensory/motor) maturing first, proceeding up the processing hierarchy, and ending with maturation of the highest levels (some prefrontal, associative etc) around age ~20.
The human brain’s most prized intellectual capabilities are constrained (but not fully determined) mostly by the upper brain regions. Having larger V1 synaptic capacity may make for a better fighter pilot through greater visual acuity, but STEM capability is mostly determined by capacity & efficiency of upper brain regions (prefrontal, associative, etc and their cerebellar partners).
I say constrains rather than determines because training data quantity/quality also obviously constrains. Genius level STEM capability requires not only winning the genetic lottery, but also winning the training run lottery.
Brain size only correlates with intelligence at 0.3-0.4.
IQ itself only correlates with STEM potential (and less so as you move away from the mean) but sure there are many ways to make a brain larger that do not specifically increase synaptic capacity&efficiency of the specific brain regions most important for STEM capability. Making neurons larger, increasing the space between them, increasing glial size or counts, etc. But some brain size increase methods will increase the size of STEM linked brain regions, so 0.3-0.4 seems about right.
The capacity&efficiency of the most important brain regions is mostly determined by genes effecting the earliest stage 1 - the architectural prior. These regions won’t fully be used until ~20 years later due to how the brain trains/matures modules over time, but most of the genetic influence is in stage 1 - i’d guess 75%.
I’d guess the next 20% of genetic influence is on stage 2 factors that effect synaptic efficiency and learning efficiency, and only 5% influence on 3 via fully mature/trained modules.
Yes a few brain regions (hippocampus, BG, etc) need to maintain high plasticity (with some neurogenesis) even well in to adulthood—they never fully mature to stage 3. But that is the exception, not the rule.
Brains are constantly evolving and adapting throughout the lifespan.
Not really—See above. At 45 most of my brain potential is now fully spent. I’m very unlikely to ever be a highly successful chess player or physicist or poet etc. Even learning a new human language is very slow and ineffective compared to a child. It’s all about depletion of synaptic learning potential reserves.
The colloquial use of the word ‘learning’ as in ‘learning’ new factual information is not at all what I mean and is not relevant to STEM capability. I am using ‘learning’ in the more deep learning sense of learning deep complex circuits important for algorithmic creativity, etc.
As a concrete specific example, most humans learn to multiply large numbers by memorizing lookup tables for multiplication of individual digits and memorizing a slow serial mental program built on that. But that isn’t the only way! It is possible to learn more complex circuits which actually do larger sum addition&multiplication directly—and some mentats/savants do acquire these circuits (with JVN being a famous likely example).
STEM capability is determined by deep learning many such circuits, not ‘learning’ factual knowledge.
Now it is likely that one of the key factors for high intelligence is a slower and more efficient maturation cycle that maintains greater synaptic learning reserves far into adulthood—ala enhanced neotany, but that is also an example of genetic influence that only matters in stage 1 and 2. Maturation is largely irreversible—once most connections are pruned and the few survivors are strengthened/myelinated you can’t go back to the earlier immature state of high potential.
But it ultimately doesn’t matter, because the brain just learns too slowly. We are now soon past the point at which human learning matters much.
If this was actually the case then none of the stuff people are doing in AI safety or anything else would matter.
Huh? Oh—by learning there I meant full learning in the training sense—stages 1 and 2. Of course things adults do now matter, they just don’t matter through the process of training new improved human brains.
We can roughly bin brain tissue into 3 developmental states:
juvenile: macro structure formation—brain expanding, neural tissue morphogenesis, migration, etc
maturing: micro synaptic structure formation, irreversible pruning and myelination
mature: fully myelinated, limited remaining plasticity
Maturation proceeds inside out with the regions closest to the world (lower sensory/motor) maturing first, proceeding up the processing hierarchy, and ending with maturation of the highest levels (some prefrontal, associative etc) around age ~20.
The human brain’s most prized intellectual capabilities are constrained (but not fully determined) mostly by the upper brain regions. Having larger V1 synaptic capacity may make for a better fighter pilot through greater visual acuity, but STEM capability is mostly determined by capacity & efficiency of upper brain regions (prefrontal, associative, etc and their cerebellar partners).
I say constrains rather than determines because training data quantity/quality also obviously constrains. Genius level STEM capability requires not only winning the genetic lottery, but also winning the training run lottery.
IQ itself only correlates with STEM potential (and less so as you move away from the mean) but sure there are many ways to make a brain larger that do not specifically increase synaptic capacity&efficiency of the specific brain regions most important for STEM capability. Making neurons larger, increasing the space between them, increasing glial size or counts, etc. But some brain size increase methods will increase the size of STEM linked brain regions, so 0.3-0.4 seems about right.
The capacity&efficiency of the most important brain regions is mostly determined by genes effecting the earliest stage 1 - the architectural prior. These regions won’t fully be used until ~20 years later due to how the brain trains/matures modules over time, but most of the genetic influence is in stage 1 - i’d guess 75%.
I’d guess the next 20% of genetic influence is on stage 2 factors that effect synaptic efficiency and learning efficiency, and only 5% influence on 3 via fully mature/trained modules.
Yes a few brain regions (hippocampus, BG, etc) need to maintain high plasticity (with some neurogenesis) even well in to adulthood—they never fully mature to stage 3. But that is the exception, not the rule.
Not really—See above. At 45 most of my brain potential is now fully spent. I’m very unlikely to ever be a highly successful chess player or physicist or poet etc. Even learning a new human language is very slow and ineffective compared to a child. It’s all about depletion of synaptic learning potential reserves.
The colloquial use of the word ‘learning’ as in ‘learning’ new factual information is not at all what I mean and is not relevant to STEM capability. I am using ‘learning’ in the more deep learning sense of learning deep complex circuits important for algorithmic creativity, etc.
As a concrete specific example, most humans learn to multiply large numbers by memorizing lookup tables for multiplication of individual digits and memorizing a slow serial mental program built on that. But that isn’t the only way! It is possible to learn more complex circuits which actually do larger sum addition&multiplication directly—and some mentats/savants do acquire these circuits (with JVN being a famous likely example).
STEM capability is determined by deep learning many such circuits, not ‘learning’ factual knowledge.
Now it is likely that one of the key factors for high intelligence is a slower and more efficient maturation cycle that maintains greater synaptic learning reserves far into adulthood—ala enhanced neotany, but that is also an example of genetic influence that only matters in stage 1 and 2. Maturation is largely irreversible—once most connections are pruned and the few survivors are strengthened/myelinated you can’t go back to the earlier immature state of high potential.
Huh? Oh—by learning there I meant full learning in the training sense—stages 1 and 2. Of course things adults do now matter, they just don’t matter through the process of training new improved human brains.