Hacker News Reader

Comment by stochastician | Hacker News Reader

Also in the time-honored tradition of HN, the title isn't quite right. 1. we didn't build the connectome, the visual 6502 team did. 2. It's such a good connectome that we can simulate everything perfectly -- a Hansonian "Em", if you will. 3. It's still hard with total visibility to use contemporary techniques to achieve understanding.

View on HN

What's the basic point of a connectome? What understanding did anyone expect to achieve from making one? Sure, maybe you can emulate the device, but unless you're a very ardent philosophical connectionist, you're not understanding much. And if you are a very ardent philosophical connectionist, you're claiming that knowing the connections gives us all there is to understand, with no deeper principles than synaptic weights being available.

It's as silly as expecting to get a good theory of artificial intelligence by studying artificial neural networks.

(I'm aware of the irony in the above statement, but stand by it earnestly. An excellent engineering artifact whose functioning we can't explain is not scientific understanding. An excellent engineering artifact whose functioning we refuse to explain is bad philosophy, too.)

I think many in the neuroscience community would agree that there's a lot we can learn from connectomes, and there's a lot of value from just having a canonical, authoritative map of the underlying neuroanatomy. Every year there are a few new neuroanatomy papers that say "surprise, area X projects to area Y!" and that's sort of embarrassing given that many people have been studying an area for 30 years and the sudden appearance of dopaminergic projections upsets all their previous models.

Also, there exist brain areas and regions where we do in fact have a few good good models, and connectomics has the potential to help us resolve them -- see http://www.nature.com/nature/journal/v500/n7461/full/nature1...

Even in these apparently simple feedforward sensory networks, connectomics haven't been the anticipated panacea. There's been a flurry of follow-up papers to Takemura et al., essentially refuting the suggested model.

Turns out, even where they should connections don't constrain circuits to a sufficient degree.

Awesome, do you have a good cite for that? The last time I paid attention in this space was a year+ ago, when the vision people were trumpeting these results, so I'd love to know more about the current thinking. It's been my go-to example for "connectomics will help with some things", but I'm not a sensory physiologist.

Try this: https://www.ncbi.nlm.nih.gov/pubmed/26234212

I guess the key lesson is -- don't rely on a single approach, because its limitations may well lead you astray. Applies to connectomics, physiology, modelling, etc.

I don't think anyone really claims that all you need is the wiring diagram, even those who really want to see a connectome. Then again, I stay away from philosophical debates about the connectome.

Everyone who's paying attention understands that individual neurons have the potential for very complex, but precise, behavior.

But knowing the connections across the brain (at some resolution) is helpful for plenty of reasons. If I want to understand how areas in the brain communicate, it's immensely useful to know where they're connected, for instance. Let's say I have 200 sensors I can place in the brain wherever I want. Placing them at crucial nodes or connected areas could be tremendously useful, since we can't yet put sensors everywhere for most spatial and temporal resolutions we want.

We'd happily change the HN title again if someone would suggest one that's accurate and neutral. I spent several minutes trying to figure out how to replace the original clickbait and clearly got it wrong.

Reply on news.ycombinator.com