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Map of an Insect’s Brain

smithsonianmag.com

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Re: Map of an Insect’s Brain

#111

Post by wizofaus »

otabdeveloper4 wrote: post #42
wizofaus wrote: post #25

Earlier quoted context omitted.

Is there convincing evidence actual insects have "awareness"?

What is "awareness"? The only objective, measurable quantity is information complexity. (And yes, insects have it.)

Subjective experience of the world around us. The one thing I'm 100% sure I do have, and it would require very special pleading (or solipsism) to insist other humans are anything other than almost certain to share that trait. My suspicion is that there is some threshold of cerebral complexity required for it to occur, and is pretty unlikely to apply to all animals with central nervous systems. Whether insect brains are sufficiently complex I really couldn't say, nor am I sure what test could be done to determine it (though one day we may have enough understanding to do such a test).

Re: Map of an Insect’s Brain

#112

Post by causality0 »

moonbreams wrote: post #94
causality0 wrote: post #7

With 3,016 neurons and 548,000 connections, called synapses, the result is by far the most complex map of a whole brain ever made. It's an impressive achievement but I'm not sure I'd call that a whole brain. It's a larval proto-brain with less than 4% the neurons of an adult fly.

larvae behave, they learn, they forage, they do have a brain.

Do they learn? What behaviors make a fruit fly larva more intelligent than a jellyfish?

Re: Map of an Insect’s Brain

#113

Post by cutemonster »

tsimionescu wrote: post #82
cyberax wrote: post #74

Earlier quoted context omitted.

OpenWorm is a bad model. To give a computer analogy, you're simulating highly optimized low-level code for Apple ][. That uses all the little hardware-specific tricks and timings to work. A fruit fly brain is a better model to simulate in this regard. It's much more "generic", so there's a hope that we can recapture high-level behavior from it more easily.

> A fruit fly brain is a better model to simulate in this regard. It's much more "generic", so there's a hope that we can recapture high-level behavior from it more easily. This is a completely baseless assumption. It is also moot, since simulating even 300 neurons is beyond our current computational power; simulating 3000 is not going to be possible in the foreseeable future.

What makes stimulating 300 that computationally heavy?

(Doesn't sound like many?, but I've read that one single neuron needed 100 or so nodes in a deep neural net to simulate. But 300*100 also doesn't sound like many (nodes)?)

Edit: some explanations here: https://news.ycombinator.com/item?id=35113498 (in this discussion)

Re: Map of an Insect’s Brain

#114

Post by Groxx »

cutemonster wrote: post #113
tsimionescu wrote: post #82

Earlier quoted context omitted.

> A fruit fly brain is a better model to simulate in this regard. It's much more "generic", so there's a hope that we can recapture high-level behavior from it more easily. This is a completely baseless assumption. It is also moot, since simulating even 300 neurons is beyond our current computational power; simulating 3000 is not going to be possible in the foreseeable future.

What makes stimulating 300 that computationally heavy? (Doesn't sound like many?, but I've read that one single neuron needed 100 or so nodes in a deep neural net to simulate. But 300*100 also doesn't sound like many (nodes)?) Edit: some explanations here: https://news.ycombinator.com/item?id=35113498 (in this discussion)

Yep, pretty much that thread.

Massively simplified models exist, and yeah - we have artificial neutral networks FAR larger than that and they run just fine. But they're so over-simplified that it's fair to call them something else entirely, not a simulation. You can use them to create similar behavior, but they're just following the basic concept of a brain, not how they actually work. Inspired by a real thing, not actually mimicking a real thing.

Kinda like how a door hinge is not your knee, even though they both bend. It's not a knee simulation, it's just something that bends. For some things (doors) that's perfectly fine, and there are billions of them in use. You can't transparently replace your knee with one though, it has biology-juice all over it and needs to handle very different behaviors at times.

Re: Map of an Insect’s Brain

#115

Post by moonbreams »

causality0 wrote: post #112
moonbreams wrote: post #94

Earlier quoted context omitted.

larvae behave, they learn, they forage, they do have a brain.

Do they learn? What behaviors make a fruit fly larva more intelligent than a jellyfish?

Well granted they're solving quadratic equations, but neither are the adults.

For instance, if you expose larvae a rewarding stimulus like sugar along with an odour, they will later be attracted to that odour. That is by definition learning, simple learning, but we have to start somewhere i guess.

Interestingly there is some evidence that the memory lasts through to the adult stage, despite the fact that a lot of the brain is actually rewired during pupation.

Re: Map of an Insect’s Brain

#116

Post by Someone »

flangola7 wrote: post #106
yourapostasy wrote: post #95

Earlier quoted context omitted.

An average cell contains an estimated 100 trillion atoms. I’m guessing to “just” simulate elegans’ 302 neurons at the atomic not to speak of quantum precision, is not within our compute capabilities yet. Until then, we’ll have to content ourselves with rather crude approximations of simulations. I’m not entirely convinced on a gut feel level that the current GPT (multimodal or not) AI will necessarily lead to AGI whe…

I think it's likely we will figure out how to make intelligence in silicon before we figure out how it works in brain matter. Just as there's more than one way of generating electricity there may be many ways of generating thought.

I would guess that, if we ever manage to make intelligence in silicon, we will know how every detail works, but not why the entire thing is intelligent.

Re: Map of an Insect’s Brain

#117

Post by causality0 »

moonbreams wrote: post #115
causality0 wrote: post #112

Earlier quoted context omitted.

Do they learn? What behaviors make a fruit fly larva more intelligent than a jellyfish?

Well granted they're solving quadratic equations, but neither are the adults. For instance, if you expose larvae a rewarding stimulus like sugar along with an odour, they will later be attracted to that odour. That is by definition learning, simple learning, but we have to start somewhere i guess. Interestingly there is some evidence that the memory lasts through to the adult stage, despite the fact that a lot of the…

Interesting, with the caveat that the odor/reward experiment was performed on larvae at a development stage with 10,000 neurons, not 3,000.

Re: Map of an Insect’s Brain

#118

Post by ouraf »

The name of one of the scientists involved in mapping a fly's brain is MOSCA?

I had to double check if I didn't click on a Babylon bee or the onion article just to be sure.

Re: Map of an Insect’s Brain

#119

Post by epgui »

toss1 wrote: post #103
epgui wrote: post #77

Earlier quoted context omitted.

Edit: I got confused and didn’t write this comment in the right place. —- I somewhat agree with how you described it as top-down vs bottom-up. I think it’s not exactly how I was framing it, but it’s close enough, and it’s a useful way to think of it. Even in the rest of your comment you’re taking a bit more of a bottom-up approach relative to what I’m saying: you’d be surprised how much we know about how the brain’s…

Thanks for the recommendation, tracking it down. And yes, modeling at the higher functional level can be very useful; knock out the Wernicke's center and speech goes, visual cortex, vision, etc... So, with a more detailed functional description of each level, we may wind up with a model with useful predictive value. Tho, that said, how does this approach create a truly robust abstraction from the lower level wetware?…

This is a little handwavy, but consider that, in the context of modelling a human brain:

- If you model top-down (at the tissue/functional level like you suggest), you'll be recreating the "broadly correct" kind of computation, and you'll be recreating something that looks and feels like a really really bad, quirky and dumb human brain. But it'll have certain human-like qualities that are maybe even difficult to pin down. These would possibly make a ton of mistakes, but there'd be a lot of human-like biases and mistakes.

- If you throw billions of neurons into a bag, you may be able to train them to perform calculations with a high degree of correctness (eg.: ChatGPT, generative art, modern ADAS systems) but when these make mistakes, the mistakes they make will look extraordinarily stupid to a human (eg.: "a human would never have suddenly steered his car into a brick wall like that").

Both approaches can produce extremely stupid results, but you need the top-down architecture if you want to preserve what makes "the human flavour of intelligence" what it is. (I suppose you could emulate the same result with a big enough bag of neurons, but that sounds very inefficient to me, intuitively.)

---

Depending on what you're interested in modelling, you may need to combine multiple approaches, as the brain has multiple layers of emergent properties. I don't think that for most purposes you'd need to go as far as modelling blood contents, but something like it might be required if "embodiment" was an important part of what you'd like to model. There are certain types of things that biological organisms learn particularly fast because they have a physical body that interacts with the real world.

I don't personally believe embodiment is fundamentally required in the model (ie.: I think it's probably possible to emulate the same result if you use a sufficiently large number of neurons), but I think realistically it will be a practical necessity for keeping models and computations as efficient as possible.

Re: Map of an Insect’s Brain

#120

Post by epgui »

meindnoch wrote: post #91
epgui wrote: post #80

Earlier quoted context omitted.

I’d argue they’re better (in some ways), given that they’re “dead” material as opposed to functional tissue. Human knees don’t last nearly as long when the tissue is dead.

Lol. That's an interesting definition of "better". If you're active, knee implants have to be replaced after 15-20 years, because they detach from the bone. Knee implants can harbor pockets of infections because they don't have an immune system. They are also more prone to dislocations. They are objectively inferior to a healthy organic knee.

Yes, my comment was made a bit in jest. I think everyone will agree that after an arthroplasty, your quality of life is not as good as it was before.

But most of the reasons why artificial knees are not as good as the real deal have to do with the fact that they're made of inert (albeit fancy) materials. They don't have the ability to continually heal and do tissue remodelling, which is what real tissue does.

I feel very optimistic when I think about this: we're limited, but I think it's absolutely wonderful what we're able to do.

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