Neural field theory is different than the neuron doctrine. It accepts the neuron doctrine.
That abstract does not seem to be questioning the neuron doctrine but a particular way of thinking about neuronal populations. It is not proposing that we need to think about something other than neuronal axons and dendrites passing information, but rather about how to think about population dynamics.
So this is the opposite of proposing a more detailed model of brain function is necessary, but proposing a courser-grained approximation.
And they’re not addressing what it would take to perfectly understand or reproduce brain dynamics, just a way to approximately understand them.
It is not proposing that we need to think about something other than neuronal axons and dendrites passing information, but rather about how to think about population dynamics.
Really? Isn’t the shape of the brain something other than axons and dendrites?
The model used in the paper doesn’t take any information about neurons into account, it’s just based on a mesh of the geometry of the particular brain region.
So this is the opposite of proposing a more detailed model of brain function is necessary, but proposing a courser-grained approximation.
And they’re not addressing what it would take to perfectly understand or reproduce brain dynamics, just a way to approximately understand them.
The results (at least the flagship result) are about a coarse approximation, but the claim that anatomy restricts function still seems to me like contradicting the neuron doctrine.
Admittedly the neuron doctrine isn’t well-defined, and there are interpretations where there’s no contradiction. But shape in particular is a property that can’t be emulated by digital computers, so it’s a contradiction as far as the OP goes (if in fact the paper is onto something).
Shape can most certainly be emulated by a digital computer. The theory in the paper you linked would make a brain simulation easier, not harder, and the authors would agree with that (while saying their theory is miles off from a proposal to emulate the brain in depth).
And the paper very likely is on to something, but not quite what they’re talking about. fMRI analyses are notoriously noisy and speculative. Nobody talking about brain emulation talks about fMRI; it’s just too broad-scale to be helpful.
Shape can most certainly be emulated by a digital computer. The theory in the paper you linked would make a brain simulation easier, not harder, and the authors would agree with that
Would you bet on this claim? We could probably email James Pang to resolve a bet. (Edit: I put about 30% on Pang saying that it makes simulation easier, but not necessarily 70% on him saying it makes simulation harder, so I’d primarily be interested in a bet if “no idea” also counts as a win for me.)
Neural field theory is different than the neuron doctrine. It accepts the neuron doctrine.
That abstract does not seem to be questioning the neuron doctrine but a particular way of thinking about neuronal populations. It is not proposing that we need to think about something other than neuronal axons and dendrites passing information, but rather about how to think about population dynamics.
So this is the opposite of proposing a more detailed model of brain function is necessary, but proposing a courser-grained approximation.
And they’re not addressing what it would take to perfectly understand or reproduce brain dynamics, just a way to approximately understand them.
Really? Isn’t the shape of the brain something other than axons and dendrites?
The model used in the paper doesn’t take any information about neurons into account, it’s just based on a mesh of the geometry of the particular brain region.
The results (at least the flagship result) are about a coarse approximation, but the claim that anatomy restricts function still seems to me like contradicting the neuron doctrine.
Admittedly the neuron doctrine isn’t well-defined, and there are interpretations where there’s no contradiction. But shape in particular is a property that can’t be emulated by digital computers, so it’s a contradiction as far as the OP goes (if in fact the paper is onto something).
Shape can most certainly be emulated by a digital computer. The theory in the paper you linked would make a brain simulation easier, not harder, and the authors would agree with that (while saying their theory is miles off from a proposal to emulate the brain in depth).
And the paper very likely is on to something, but not quite what they’re talking about. fMRI analyses are notoriously noisy and speculative. Nobody talking about brain emulation talks about fMRI; it’s just too broad-scale to be helpful.
Would you bet on this claim? We could probably email James Pang to resolve a bet. (Edit: I put about 30% on Pang saying that it makes simulation easier, but not necessarily 70% on him saying it makes simulation harder, so I’d primarily be interested in a bet if “no idea” also counts as a win for me.)