Possibly relevant: I am my connectome
It’s already possible to model brains on the neuronal level—to compute a graph of which neurons are connected to which others. The problem is scale: we’ve already completed C. elegans, we’re still a few years away from a mouse connectome, and who knows about the human connectome.
Microscope resolution isn’t the problem. The problem is the computing power required to get from tiny 3d cubes of microscopic images, to a model graph of where the neurons are—it’s an expensive image recognition problem.
That is about as true as “a city is its street map.” A street map may uniquely correspond to a real city, but it’s still a type error, and there is the strong possibility that significant information is not contained in what got put into the map.
Possibly relevant: I am my connectome It’s already possible to model brains on the neuronal level—to compute a graph of which neurons are connected to which others. The problem is scale: we’ve already completed C. elegans, we’re still a few years away from a mouse connectome, and who knows about the human connectome.
Microscope resolution isn’t the problem. The problem is the computing power required to get from tiny 3d cubes of microscopic images, to a model graph of where the neurons are—it’s an expensive image recognition problem.
That is about as true as “a city is its street map.” A street map may uniquely correspond to a real city, but it’s still a type error, and there is the strong possibility that significant information is not contained in what got put into the map.