It’s a neural network without weights. And it doesn’t have a body.
Figuring out the behaviour of the neurons could take decades, although I have no doubt that people will eventually. And simulating a whole fruit fly body seems like it’s going to be out of reach for a very long time.
It has approximate weights. Neuron connection strength is determined by the number of synapses (1-100s, sometimes 1000s), the type of synapse neurotransmitter, and the number of receptors. The connectome has 1 and 2 and is only missing 3. The number of receptors may not even be that important- the fact that the number of synapses is important may well mean the number of receptors is unreliable.
Neurons also don't transmit scalars to each other. The synapse is stimulate by frequency of action potentials much more than strength.
> And it doesn’t have a body.
It does have nervous connections outside the brain. That behavior is not as complex.
> Figuring out the behaviour of the neurons could take decades
Neurons are not that complex in terms of matching in->out behavior. Since spiking is frequency-based, you can verify it quite well by ensuring the frequency of spikes in->out matches; you can even measure single neurons with implanted electrodes. You don't need so much precision to see individual spikes, since the size of the spikes does not matter much at all.
Long term potentiation also makes measuring individual neuron strength even less important- if you model potentiation correctly, then over time you'll converge accurately as understimulated connections weaken and vice versa.
The real issue is we have barely any clue how potentiation works and can't model it well at all. It's very important to brain behavior and most of the interesting things brains do. Its kind of an issue.
> Neuron connection strength is determined by the number of synapses (1-100s, sometimes 1000s), the type of synapse neurotransmitter, and the number of receptors.
But the astrocytes are dynamically modulating the signal at the synapse, it doesn't seem like we really know "the" weight.
And of course, not just frequency of incoming action potentials, but processes within the receiving cell, in the cell membrane, at the site of the synapse, and between the cell and any supporting cells (astrocytes and glia).
It's also not just frequency, but "shape" (for lack of a better word) of incoming inputs that matters, as such there is a very wide variety of spiking patterns that certain cells exhibit, like chopper cells.
As such, unlike the vast majority of emulated humans, the emulated Miguel Acevedo boots with an excited, pleasant demeanour. He is eager to understand how much time has passed since his uploading, what context he is being emulated in, and what task or experiment he is to participate in.
...
MMAcevedo's demeanour and attitude contrast starkly with those of nearly all other uploads taken of modern adult humans, most of which boot into a state of disorientation which is quickly replaced by terror and extreme panic. Standard procedures for securing the upload's cooperation such as red-washing, blue-washing, and use of the Objective Statement Protocols are unnecessary. This reduces the necessary computational load required in fast-forwarding the upload through a cooperation protocol, with the result that the MMAcevedo duty cycle is typically 99.4% on suitable workloads, a mark unmatched by all but a few other known uploads. However, MMAcevedo's innate skills and personality make it fundamentally unsuitable for many workloads.
no. turaga and co have some work where they constrain model network topologies with the connectome and train on visual data. this is imo a very silly line of research and they come to some very wrong conclusions about what neurons do what with it. but that's the closest to what you're asking for
