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Doing this sort of comparison is very difficult. First, the brain is not digital by any stretch of the imagination, it is highly analog. Computers, on the other hand, are digital (binary, specifically). So doing a calculation measurement on a brain is hard to begin with. Second, the way they handle tasks is very different. Computers are designed to ...


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As in the ideal gas law, the universal gas constant allows for calculation of amount of energy associated with a certain group of molecules (see https://en.wikipedia.org/wiki/Gas_constant). As the Nernst equation compares the "osmotic pressure" to "electrical pressure", the universal gas constant is needed to convert amount of an ion on the two sides of a ...


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The short answer is yes. The longer answer involves a more precise meaning of deterministic and a number of research considerations. In the strict sense of deterministic, which means that given the same input, the same output will always occur, any probability distribution modeled on a computer is deterministic, since most digital computers have a ...


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First, many neurons don't have action potentials at all, and of those that do some don't encode information based on firing rate (rather they use the timing of spikes or some other code). So the question isn't relevant for all neuron types. Further, even for neurons that do encode information based on firing rate, the "average" is often not a very useful ...


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The number of types varies depending on exactly how you count, but there are likely thousands, if not tens of thousands. NeuroLex has 775 named neurons, and that is just a fraction of all the neurons that exist. They vary in their size, their shape, the number, length, thickness, and branching pattern of their axons (if any), the number, length, thickness, ...


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You're basically trying to replicate the work of the Blue Brain Project. To get a good summary of their work, check out their 2015 Cell paper, where they describe assembling a few columns of the rat barrel (whisker sensing) cortex. In this incredibly specialised, small cortex there are a ridiculous amount of neurons (207 electrical sub-types), with a wide ...


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The phrase "fire together, wire together" comes from an explanation of Hebbian Learning and refers to the adaptation of synapses as a response to the firing of already connected neurons. This is one of several Synaptic Plasticity mechanisms. Two others that exist are Long Term Potentiation (strengthening and creation) and Long Term Depression (weakening and ...


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This question seems to be asking "How is knowledge represented in neurons" and then jumps to the assumption "synapses represents relations". As discussed in the linked question, there is a lot of evidence that this method of binding is not biologically plausible, given that it doesn't scale well to the level of human vocabulary. So, to answer your question, ...


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What leaps in technology would be needed to scan the total state of the human brain? Preface In 2016, the "Small Mammal BPF Prize" was won, see: http://www.brainpreservation.org/small-mammal-announcement/. It's the first of two stages of competition for brain preservation (BP) achievements. This competition is doing for BP what XPRIZE is doing for ...


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Your question can be reduced to "What level of detail do we need to know about a brain to be able to simulate it?" The answer to this question is that we have no idea and that's a problem. The Blue Brain project has bet on the synaptic level, but they haven't been able to scale that up to behaviour yet. But why stop at the synaptic level? Why not go down to ...


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The simplest equation for getting a BOLD signal from neurotransmitter that I could find was in "Tracing Problem Solving in Real Time: fMRI Analysis of the Subject-paced Tower of Hanoi", which itself references many other publications where it was used: $$H(t)= m \times(t/s)^a\times e^{-(t/s)}$$ The parameters $s$, $a$ and $m$ don't have an explicit meaning....



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