But reverse-engineering something that is the product of almost 4 billion years of evolution, that has been tweaked and finessed in complex and incomprehensible ways, and that is dependent on activity at a sub-cellular level, by hacking it apart and taking pictures of it? Total bollocks.
I agree with the last sentence.
While it is possible that key features aspects of intelligence can’t be modeled without an extremely low level of detail of brain function, it’s also possible that many of those details are not needed. I think it’s likely. My guess is that if neurons were so chaotically fiddly on a functional level, we wouldn’t work at all in the first place.
My hypothesis is that there are a finite number of classes of neurons, glial cells, and classes of synaptic junctions, that bound closely into certain behavioral groupings. In which case, you need only prod enough neurons in petri dishes to develop good statistical models of each type of neuron, glia, and synapse you’re modelling. I suspect, but can’t prove right now, that only the broad probabilistic behavior of each functional element would be meaningful on the scales we care about.
The reason I believe that is exactly what you said—it’s too noisy. Human brains are way too robust to be extremely sensitive to sub-cellular changes. If you want sub-cellular changes to make a difference (say, in the case of drugs) you have to affect billions of neurons.
EDIT: Actually, you can pretty cleanly rebut his argument about how hard it is to preserve the fish’s neural tissue in what he considers to be ‘sufficient detail.’ If brains really were that sensitive to sub-cellular shifts in neuronal state, there’s no way it would be possible for someone to recover from being clinically dead for a few seconds, much less the hours or days that have been observed in cold conditions.
I agree with the last sentence.
While it is possible that key features aspects of intelligence can’t be modeled without an extremely low level of detail of brain function, it’s also possible that many of those details are not needed. I think it’s likely. My guess is that if neurons were so chaotically fiddly on a functional level, we wouldn’t work at all in the first place.
My hypothesis is that there are a finite number of classes of neurons, glial cells, and classes of synaptic junctions, that bound closely into certain behavioral groupings. In which case, you need only prod enough neurons in petri dishes to develop good statistical models of each type of neuron, glia, and synapse you’re modelling. I suspect, but can’t prove right now, that only the broad probabilistic behavior of each functional element would be meaningful on the scales we care about.
The reason I believe that is exactly what you said—it’s too noisy. Human brains are way too robust to be extremely sensitive to sub-cellular changes. If you want sub-cellular changes to make a difference (say, in the case of drugs) you have to affect billions of neurons.
EDIT: Actually, you can pretty cleanly rebut his argument about how hard it is to preserve the fish’s neural tissue in what he considers to be ‘sufficient detail.’ If brains really were that sensitive to sub-cellular shifts in neuronal state, there’s no way it would be possible for someone to recover from being clinically dead for a few seconds, much less the hours or days that have been observed in cold conditions.