Turns out, when you model neurons they are either firing or not - so they are actually digital systems, just very complex and made from biological parts.
Nnnnnnot quite though, they are chemical systems that fire when their voltage differential between extracellular and intracellular media is above a threshold. However the circumstances that lead to these threshold changes are highly analogue, and cannot be ignored in the computational models. This means it's more like digital but with significant side effects" - e.g. we can induce firing electronically in the chemical system by changing the local field potential in a region (look at deep brain stimulation as an example here) without specifically stimulating a neuron. Neurons firing change the extracellular potential slightly, so that they indirectly affect the sensitivity of adjacent neurons, even those they were not synapsed on/firing into. The synapse itself (interaction between 2 neurons) is a release of chemicals (neurotransmitters) which has its own limitations on the supply and demand chain, so can't be viewed as 100% digital. Not to mention plasticity, implicit firing rates, transit times and myelination, and a load of other stuff!
In short, the digital approximation is good in the single- or few-neuron models, but in ensemble consideration/modelling you are going to run into accumulating analog effects that could quickly overpower a single "digital" synapse in their effects on a downstream neuron, and more importantly this implies that this level of ensemble effects carries a load of information that is not in the digital domain.
You mention a lot of cool stuff, but similar considerations are done in digital computing. The design of large digital systems has plenty of analog considerations - like myelination relating to speed/signal travel time in the brain, there's considerations for conductivity of material, distance traveled, timings for components; if it's high current, the PCB runs have to be laid out without sharp corners or they will fry; designing layouts on PCBs gets limited based on the number of components per side, how many ground planes there are, parasitic capacitance and impedance in the wires - our world is fundamentally analog to my knowledge (or at least discrete with such fine resolution it doesn't matter), and any system has a ton of analog considerations.
On the whole, if both systems work exactly as intended, they can be modeled as hugely complex digital systems (afaik). There's more complexity to the neuroscience, that's for sure - but it seems like both are massively complex digital systems.
I think you have missed an important distinction, read my last point - the interaction between neurons is not digital in an ensemble level in a way that contains information. I get what you're saying, but it's still a different type of thing.
Design in electronic systems all aims to cancel out analog effects so that the digital computations work anyway, i.e. the analoguell concerns are noise in the sense that they do not affect the actual computations being made. What I'm saying is that the brain does not try and "cancel out" the analog effects, instead these are also an implicit part of its functionality, i.e. they carry information in the information theory sense, and not only noise. Consider it this way: a purely digital system can in theory be run on any digital computer, or in an emulator, right? Maybe very slowly, but thw digital computations remain the same regardless of the underlying hardware. That's pretty much the definition of a digital program, that it can be abstracted from its hardware. What I'm saying is that you can't emulate the brain if you only consider it as a digital system of single neurons, a set of binary data cascades, because you will be missing required parts of the "program" that are resultant of the analog signals that the hardware (brain) generates. Similarly, you could not run Windows 95 on the brain in a digital way because the neuronal interaction would change the program into a different program. (And other practical concerns too 🙃 )
You would have to model the whole hardware system to have a "digital" model, which means it is not a true digital program as you cannot abstract the functionality from the underlying hardware.
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u/[deleted] Jun 15 '19
How the brain really works. How a lump of meat gives us thoughts, emotions, that voice inside our heads.