http://h01-dot-neuroglancer-demo.appspot.com/#!gs://h01-rele...
To think that’s one single millimeter of our brain and look at all those connections.
Now I understand why crows can be so smart walnut sized brain be damned.
What an amazing thing brains are.
Possibly the most complex things in the universe.
Is it complex enough to understand itself though? Is that logically even possible?
If someone did this experiment with a crow brain I imagine it would look “twice as complex” (whatever that might mean). 250 million years of evolution separates mammals from birds.
We have more detail than this about the C. elegans nematode brain, yet we still no clue how nematode intelligence actually works.
The human 'spoken data rate' is likely due to average processing rates in our common hardware. Birds have a different architecture.
So one would just need to pick that little cube out of our cerebellum, to have that 'twice as complexity'.
I'm saying we will probably discover that the "overall performance" of different vertebrate neural setups are clustered pretty closely, even when the neurons are arranged rather differently.
Human speech is just an example of another kind of performance-clustering, which occurs for similar metaphysical reasons between competing, evolving, related alternatives.
Almost every other cell in the worm can be simulated with known biophysics. But we don't have a clue how any individual nematode neuron actually works. I don't have the link but there are a few teams in China working on visualizing brain activity in living C. elegans, but it's difficult to get good measurements without affecting the behavior of the worm (e.g. reacting to the dye).
the sheer number of things that work in co-ordination to make biology work!
In-f*king-credible !
Human brains might not be all that efficient; for example, if the competitive edge for primate brains is distinct enough, they'll get big before they get efficient. And humans are a pretty 'young' species. (Look at how machine learning models are built for comparison... you have absolute monsters which become significantly more efficient as they are actually adopted.)
By contrast, birds are under extreme size constraints, and have had millions of years to specialize (ie, speciate) and refine their architectures accordingly. So they may be exceedingly efficient, but have no way to scale up due to the 'need to fly' constraint.
I haven’t heard of a clocking mechanism in brains, but signals propagate much slower and a walnut / crow brain is much larger than a cpu die.
Brain waves (partially). They aren't exactly like a cpu clock, but they do coordinate activity of cells in space and time.
There are different frequencies that are involved in different types of activity. Lower frequencies synchronize across larger areas (can be entire brain) and higher frequencies across smaller local areas.
There is coupling between different types of waves (i.e. slow wave phase coupled to fast waves amplitude) and some researchers (Miller) thinks the slow wave is managing memory access and the fast wave is managing cognition/computation (utilizing the retrieved memory).
By and large It’s not direct competition but we are stamping our species at an alarming rate and birds are taking a hammering.
Nerve signals are both chemical reactions and electrical impulses like metal wire. Electrical impulses are sent along the fat layer by ions Potassium , Calcium, Sodium etc.
Twitch responses are actually done in spinal cord. The signals are short circuited all along the spine and return back to muscle without touching the brain ever.
There was a short series filmed, that I enjoyed, but definitely not strong.
There's too many confounding factors to say that the human brain architecture is actually 'better' based on the outcomes of natural selection. And if we kill all the birds, we will lose the chance to find out as we develop techniques to better compare the trade-offs of the different architectures.
LLMs that work at a very crude level of string tokens and emit probabilities.
Summary (my paraphrasing):
They partially figured out how two neurons (AVA, AVB) control forward and backward movement, previous theories assumed one neuron controlled forward and one controlled backward, but that didn't correctly model actual movement.
They found that AVA+AVB combine in a complex mechanism with two different signaling/control methods acting at different timescales to produce a graded shifting between forward+backward when switching directions, as opposed to an on/off type switch (that previous models used but didn't match actual movements).
Interesting learnings from this paper (at least for me):
1-Most neurons in worm are non-spiking (I had no idea, I've read about this stuff a lot and wasn't aware)
2-Non-spiking neurons can have multiple resting states at different voltages
3-Neurons AVA and AVB are different, they each have different resting state characteristics and respond differently to inputs