9 ms·

It was my understanding that all this connectome-based research was largely a deadend, because it doesnt capture dynamics, nor a vast array of interactions. if

It was my understanding that all this connectome-based research was largely a deadend, because it doesnt capture dynamics, nor a vast array of interactions. if you've ever seen neurones being grown (go search YT), you'll see it's a massive gelatinous structure which is highly plastic and highly dynamic. Even in the simplest brains (eg., of elgans), you get 10^x exponential growth in number of neurones and their connections as it grows.

dekhn 2y ago
This is done agaist an adult so all the neurons have already grown. connectome isn't a dead end but it doesn't solve all known problems. It's like making a static map which you can then use to inspect all those cars driving around (the dynamics) and crashing (the interactions). [edit: I forgot to mention that neuron growth in adults (across many species) is still a controversial topic; see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554932/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554932/ for some commentary on the challenge in fly; https://en.wikipedia.org/wiki/Adult_neurogenesis https://en.wikipedia.org/wiki/Adult_neurogenesis for commentary on the larger problem ]
caseyy 2y ago
Giving scientists access to the connectome snapshot alone is very exciting. The first step to understanding why something is and how it came to be is seeing what it is. There are systems at play that form the brain into what it is and we don’t know much about them. The individual neurons — we have a better understanding of, but not the emergent systems. Now that many more scientists will know what the target for these systems is — what is the brain they shape, we can start to understand the control and feedback loops that result in this snapshot state of the brain. And that’s why it’s not a dead end. Just because it doesn’t immediately give some sort of a consumer product, doesn’t mean it’s not a step forward.
westurner 2y ago
From https://news.ycombinator.com/item?id=35877402#35886145 https://news.ycombinator.com/item?id=35877402#35886145 : > So, to run the same [fMRI, NIRS,] stimulus response activation observation/burn-in again weeks or months later with the same subjects is likely necessary given Representational drift And isn't there n-ary entanglement?
tgbugs 2y ago
You don't get the dynamics from connectomes, but you absolutely need them. So it isn't that they are a dead end, it is that the dynamics by themselves are also insufficient and the connectome is insufficient, you need both. Further, if you want to actually be able to have anything to attach the dynamics to, you need the cellular anatomy, so connectomes are absolutely necessary. The fact that connectomes are insufficient does not mean that such research is a dead end, but rather that the prerequisites for understanding the nervous system are vastly more complex and demanding than some might have hoped.
bhouston 2y ago
It is useful. It is like getting a static map of the country's roads with no cars on it. You can not make it come alive with cars (activity), but you can infer where people need to drive but you don't know when and why they drive or what they are doing, but it is a major clue.
- criddell 2y ago
  > It is like getting a static map of the country's roads with no cars on it. I was thinking it was more like giving somebody iPhone schematics and die shots of all the chips and then asking them to figure out how Portrait Mode works in the Camera app.
  - bhouston 2y ago
    Yup, it is similar to that as well. It is a part of the puzzle definitely, but not at all the whole picture.
  - samatman 2y ago
    Sort of, but mostly not. The critical distinction is that, given better data (the instruction set, the source code or binary of the OS and camera app), the schematics and die shots aren't necessary or even useful. It's unlikely that brains have an abstraction layer like that, so work like this is a necessary precondition to understanding the rest of how it works. That actual understanding may be elusive for quite some time to come, but without a connectome, forget it, no change.
    - snorin 2y ago
      Why exactly would it be unlikely?
      - Retric 2y ago
        It would be really inefficient and neurons inherently provide a great deal of flexibility. Larger animals might use this kind of thing, but insects don’t have that many neurons to work with. Luckily this is science so we can actually find out.
rkp8000 2y ago
Connectome-adjacent neuroscientist here. Definitely not a dead end! But also definitely not the whole picture. One of the main open questions in neuroscience right now is how network structure, dynamics, and function are related in the brain. Connectomes provide tremendous insight into structure, but as mentioned this does not generically solve either the dynamics or function problem. For example, for many of these neurons we don't have a good understanding of their input-output relationship, and the nature of this relationship can strongly affect the dynamics that emerge in a highly connected network. Individual variability across connectomes, and how connectomes change over development are also a significant issue, but at least for the fly it's thought that many of the basic structures are pretty conserved across adult animals, even if many of the details could differ. Modulo these caveats, knowing the physical network structure of the brain does still impose huge constraints on what kinds of models we should be using for gaining insight into dynamics and function. For example, there are well known areas (the "mushroom bodies") with specific feed-forward connectivity patterns that are very different from a random recurrent network. Further, there are at least some areas in the fly brain where we think there are indeed quite clean structure-function relationships, e.g. in the central complex of the fly brain, which contains a physical ring of neurons and is thought to support a "bump" of activity that acts as a sort of compass that helps flies navigate via a ring-attractor-like dynamical system. Thus, even though it has many missing pieces, a wiring diagram like this can be tremendously useful for generating hypotheses to guide more targeted experiments and theoretical studies.
- Animats 2y ago
  How's Open Worm coming along? The connectome of C. Elegans has been known for years, and Open Worm tries to simulate it. [1] Not with enormous success. [1] https://openworm.org/assets/OpenWormPoster_Celegans_Glasgow_2023.pdf https://openworm.org/assets/OpenWormPoster_Celegans_Glasgow_...
  - xandrius 2y ago
    Like everything in science: we don't know until we know. No need to treat research like a business.
mjfl 2y ago
Connectome is a necessary component to understanding dynamics.
dboreham 2y ago
You just need to supply your own training data.
ruthmarx 2y ago
> It was my understanding that all this connectome-based research was largely a deadend, There's obviously something to it or implementing what we map in software wouldn't give results as accurately as they do.
lawrenceyan 2y ago
Connectomes are like a static graph of a neural network. But it's the flow of information as signals pass through nodes where everything actually happens.
andbberger 2y ago
it's a tool in the toolbox. useful for mapping things out when doing functional experiments
Nahtnah 2y ago
https://www.sciencedirect.com/science/article/pii/S0896627320306139 https://www.sciencedirect.com/science/article/pii/S089662732... https://www.biorxiv.org/content/10.1101/2020.12.22.423967v1 https://www.biorxiv.org/content/10.1101/2020.12.22.423967v1
AlexCoventry 2y ago
That's a bit like saying that sequencing the genome was a dead end, because it doesn't capture the molecular biology of the encoded proteins. Assuming the connectome is accurate, it's a major advance in our knowledge of neuroanatomy.

dekhn 2y ago

This is done agaist an adult so all the neurons have already grown. connectome isn't a dead end but it doesn't solve all known problems. It's like making a static map which you can then use to inspect all those cars driving around (the dynamics) and crashing (the interactions). [edit: I forgot to mention that neuron growth in adults (across many species) is still a controversial topic; see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554932/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554932/ for some commentary on the challenge in fly; https://en.wikipedia.org/wiki/Adult_neurogenesis https://en.wikipedia.org/wiki/Adult_neurogenesis for commentary on the larger problem ]

caseyy 2y ago

Giving scientists access to the connectome snapshot alone is very exciting. The first step to understanding why something is and how it came to be is seeing what it is. There are systems at play that form the brain into what it is and we don’t know much about them. The individual neurons — we have a better understanding of, but not the emergent systems. Now that many more scientists will know what the target for these systems is — what is the brain they shape, we can start to understand the control and feedback loops that result in this snapshot state of the brain. And that’s why it’s not a dead end. Just because it doesn’t immediately give some sort of a consumer product, doesn’t mean it’s not a step forward.

westurner 2y ago

From https://news.ycombinator.com/item?id=35877402#35886145 https://news.ycombinator.com/item?id=35877402#35886145 : > So, to run the same [fMRI, NIRS,] stimulus response activation observation/burn-in again weeks or months later with the same subjects is likely necessary given Representational drift And isn't there n-ary entanglement?

tgbugs 2y ago

You don't get the dynamics from connectomes, but you absolutely need them. So it isn't that they are a dead end, it is that the dynamics by themselves are also insufficient and the connectome is insufficient, you need both. Further, if you want to actually be able to have anything to attach the dynamics to, you need the cellular anatomy, so connectomes are absolutely necessary. The fact that connectomes are insufficient does not mean that such research is a dead end, but rather that the prerequisites for understanding the nervous system are vastly more complex and demanding than some might have hoped.

bhouston 2y ago

It is useful. It is like getting a static map of the country's roads with no cars on it. You can not make it come alive with cars (activity), but you can infer where people need to drive but you don't know when and why they drive or what they are doing, but it is a major clue.

criddell 2y ago
> It is like getting a static map of the country's roads with no cars on it. I was thinking it was more like giving somebody iPhone schematics and die shots of all the chips and then asking them to figure out how Portrait Mode works in the Camera app.
- bhouston 2y ago
  Yup, it is similar to that as well. It is a part of the puzzle definitely, but not at all the whole picture.
- samatman 2y ago
  Sort of, but mostly not. The critical distinction is that, given better data (the instruction set, the source code or binary of the OS and camera app), the schematics and die shots aren't necessary or even useful. It's unlikely that brains have an abstraction layer like that, so work like this is a necessary precondition to understanding the rest of how it works. That actual understanding may be elusive for quite some time to come, but without a connectome, forget it, no change.
  - snorin 2y ago
    Why exactly would it be unlikely?
    - Retric 2y ago
      It would be really inefficient and neurons inherently provide a great deal of flexibility. Larger animals might use this kind of thing, but insects don’t have that many neurons to work with. Luckily this is science so we can actually find out.

rkp8000 2y ago

Connectome-adjacent neuroscientist here. Definitely not a dead end! But also definitely not the whole picture. One of the main open questions in neuroscience right now is how network structure, dynamics, and function are related in the brain. Connectomes provide tremendous insight into structure, but as mentioned this does not generically solve either the dynamics or function problem. For example, for many of these neurons we don't have a good understanding of their input-output relationship, and the nature of this relationship can strongly affect the dynamics that emerge in a highly connected network. Individual variability across connectomes, and how connectomes change over development are also a significant issue, but at least for the fly it's thought that many of the basic structures are pretty conserved across adult animals, even if many of the details could differ. Modulo these caveats, knowing the physical network structure of the brain does still impose huge constraints on what kinds of models we should be using for gaining insight into dynamics and function. For example, there are well known areas (the "mushroom bodies") with specific feed-forward connectivity patterns that are very different from a random recurrent network. Further, there are at least some areas in the fly brain where we think there are indeed quite clean structure-function relationships, e.g. in the central complex of the fly brain, which contains a physical ring of neurons and is thought to support a "bump" of activity that acts as a sort of compass that helps flies navigate via a ring-attractor-like dynamical system. Thus, even though it has many missing pieces, a wiring diagram like this can be tremendously useful for generating hypotheses to guide more targeted experiments and theoretical studies.

Animats 2y ago
How's Open Worm coming along? The connectome of C. Elegans has been known for years, and Open Worm tries to simulate it. [1] Not with enormous success. [1] https://openworm.org/assets/OpenWormPoster_Celegans_Glasgow_2023.pdf https://openworm.org/assets/OpenWormPoster_Celegans_Glasgow_...
- xandrius 2y ago
  Like everything in science: we don't know until we know. No need to treat research like a business.

mjfl 2y ago

Connectome is a necessary component to understanding dynamics.

dboreham 2y ago

You just need to supply your own training data.

ruthmarx 2y ago

> It was my understanding that all this connectome-based research was largely a deadend, There's obviously something to it or implementing what we map in software wouldn't give results as accurately as they do.

lawrenceyan 2y ago

Connectomes are like a static graph of a neural network. But it's the flow of information as signals pass through nodes where everything actually happens.

andbberger 2y ago

it's a tool in the toolbox. useful for mapping things out when doing functional experiments

Nahtnah 2y ago

https://www.sciencedirect.com/science/article/pii/S0896627320306139 https://www.sciencedirect.com/science/article/pii/S089662732... https://www.biorxiv.org/content/10.1101/2020.12.22.423967v1 https://www.biorxiv.org/content/10.1101/2020.12.22.423967v1

AlexCoventry 2y ago

That's a bit like saying that sequencing the genome was a dead end, because it doesn't capture the molecular biology of the encoded proteins. Assuming the connectome is accurate, it's a major advance in our knowledge of neuroanatomy.