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):

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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