I wonder to what extent intelligence is just brute arithmetic and not sophisticated interconnections. Our neurons and cortical structure are really good at packing as many neurons as possible into a skull and training them on living experience as early as possible relative to the developmental timeline of the brain.
Former neuroscientist here. There's certainly brute arithmetic going on. At a crude level, most individual neurons can be thought of as "voltage < threshold ? fire() : noop()".
But like individual transistors, the overall pattern is what determines its functionality. My former field was in consciousness, and one of the interesting puzzles was the cerebellum. The cerebellum contains 3x the number of neurons in the neocortex, but in cases where it's been removed (resection for epilepsy or cancer), people have fine-motor control issues, but not much more. By contrast, removing a much smaller area like visual area V1 will wipe out your visual experience and leave you blind!
So, what explains the opposite interaction between size and effect? Structure. The cerebellum is highly regular, like a GPU designed for repetitive graphics operations. The rest of the brain is more like, uh, an FPGA.
Cool! I think i take issue with "fine motor control issues, but not much more", though. Fine motor control's a really important feature of human intelligence, don't you think? Do you think the cerebellum isn't as efficient as it could be or that the number of neurons dedicated to the task reflects how computationally intensive motor control is?
I suppose a possible investigation of that question would be, say, comparing our cerebellum to that of another animal with extremely good fine motor control, like the cephalopods.
Depends on what one means by intelligence. People with cerebellectomy have difficulty with balance, but it doesn't really interfere with their general intelligence or their sensory experience.
I think the cerebellum is no more or less efficient than other areas, and I don't know if "computationally intensive" is the right way to look at it. The cerebellum really is similar to GPUs. GPUs use a lot of silicon to do constrained, repetitive tasks efficiently, but they don't support general processing models outside their narrow domain.
It's hard to compare with cephalopods, though they're very interesting, because their neural architecture is so radically different from ours. For starters, ganglia in their arms allow each arm a certain measure of independent activity. E.g., arms that get severed can try to "feed" the mouth for up to an hour after detachment.
> are really good at packing as many neurons as possible into a skull
the packing here is more about neurons connections (100T) than just about pure neurons number (100B) - high connectivity requires kind of spherical geometry with folds/ridges.
