zlacker

>>geox+(OP)
The interactive visualization is pretty great. Try zooming in on the slices and then scrolling up or down through the layers. Also try zooming in on the 3D model. Notice how hovering over any part of a neuron highlights all parts of that neuron:

http://h01-dot-neuroglancer-demo.appspot.com/#!gs://h01-rele...

>>teuobk+c4
My god. That is stunning.

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?

>>jamiek+R6
Crow/parrot brains are tiny but in terms of neuron count they are twice as dense as primate brains (including ours): https://www.sciencedirect.com/science/article/pii/S096098221...

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.

>>nickle+q8
I expect we'll find that it's all a matter of tradeoffs in terms of count vs size/complexity... kind of like how the "spoken data rate" of various human languages seems to be the same even though some have complicated big words versus more smaller ones etc.

>>Terr_+cc
Birds are under a different set of constraints than non-bat mammals, of course... They're very different. Songbirds have ~4x finer time Perception of audio than humans do, for example, which is exemplified by taking complex sparrow songs and showing them down until you can actually hear the fine structure.

The human 'spoken data rate' is likely due to average processing rates in our common hardware. Birds have a different architecture.

>>sdento+1p
You misunderstand, I'm not making any kind of direct connection between human speech and bird song.

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.

>>Terr_+jz
Humans are an n=1 example, is my point. And there's no direct competition between bird brain architecture and mammalian brain architecture, so there's no reason for one architecture to 'win' over the other - they may both be interesting local maxima, which we have no ability to directly compare.

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.