Monday open question: How long will it take to “solve” the brain?

Let’s do a quick calculation…

At the largest neuroscience conference, SfN, there are maybe 30,000 scientists who show up. Let’s pretend that this is about 1/3 of all neuroscientists (probably an underestimate) so we get 100,000 of us suckers.

Now let’s pretend we could assign each one of them a neuron that we wanted them to study. And let’s pretend that we were going to try to understand mice because, well, why not. There are ~71,000,000 neurons in the mouse brain according to Wikipedia.

This means that the mouse has about 700 neurons per neuroscientist.

There are ~10^11 synapses in the mouse brain, or about 1400 per neuron. That means there are roughly 980,000 synapses per neuroscientist.

Additionally, inside of each neuron is a whole bunch of molecular machinery that we don’t understand. Here is a simplified schematic of one of these pathways (dopamine):

molecular pathways

I have no idea how many of these pathways there are, nor how they interact. They’re kind of complicated.

Now let’s go up a step and remember that you can’t study a neuron in isolation because you have no idea what it’s inputs are or what it is outputting to. So now we need people to investigate sets of networks. And how those networks interact with each other. And how that interaction affects the physical world. And so on.

And all this is just for a mouse.

Whenever you hear, “but we’ve been studying [Alzheimers/Parkinsons/anything else] for thirty years!” remember what we’re dealing with.

The only way we can understand the mammalian brain without precisely measuring every single step of this is to find regularities and make theoretical models that can generalize from what we know to make predictions about other parts of the system. Otherwise, the hope of “understanding the brain” at all in our lifetimes is hopeless.

 

 

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4 thoughts on “Monday open question: How long will it take to “solve” the brain?

  1. Number of google employees: ~50,000. Number of emails per day: ~100 billion. Could google “understand” all of our emails, or even “understand” us? I would argue that the number of emails per google employee is as important as the number of neurons to be understood, divided by number of neuroscientists. Both facts are distracting, and potentially misleading. What matters is access to the relevant data, which is hard for neurons and easy for emails. Good data is what makes our models strong.

  2. By the time we humans begin to understand the intricacies of the mouse (or any, for that matter) brain, the brain will have evolved into something else entirely and what you would be left knowing is the last common ancestor of what will exist then and will have just begun the process of understanding the implications of those evolutionary changes.

  3. The purely reductionist approach you suggest simply will not work. For one, its intractable. The neurotransmitter signalling diagram above is meaningless. Trust me, I do this for a living. Or better yet, don’t trust me and figure out why I have come to this conclusion. I have a paper coming out on the matter and will make it public when I can.

    On a positive note, you are correct to, at least crudely, recognize the levels of organization. There are others you left out that are critical to brain function, such as regional cell types, regional interconnections, region-to-region connections, and so on. These will likely only be mappable statistically as they probably form in a partially deterministic and partially stochastic fashion.

    It is my net contention the nervous system will never be fully understood with the tools at the disposal of modern science. If you would like to see a more detailed, but not fully detailed, argument to this effect, please check out my free Ebook “What is Science?”

    http://dondeg.wordpress.com/2014/05/16/what-is-science-is-now-a-free-ebook/

    Thanks, and best wishes,

    Don

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