6 ms·

A single neuron has somewhere on the order of 5x10^16 atoms in it. There's no rule that says it couldn't potentially use a large fraction of those atoms for its

• bckr 5y ago
  Yes, and we don't know how much of that possible computational complexity is required for producing our consciousness. However, if we are modeling particular functions e.g. motor control of the limbs, we can black box a lot of that complexity.
• qweqwweqwe-90i 5y ago
  That's not a informative upper bound. We already know most of those atoms are not contributing to it's computational complexity.
  • vixen99 5y ago
    its
  • jjtheblunt 5y ago
    why is that known?
  • acchow 5y ago
    How do we know this?
    • not2b 5y ago
      Read the article. They accurately modeled the biological neuron's behavior with about 1000 'neurons'. They didn't need quintillions of neurons. So clearly the computational complexity is vastly lower than the number of atoms or molecules.
      • jhayward 5y ago
        I believe they modeled the behavior of a model of a neuron, not an actual neuron. Models are intrinsically simplifications of the reality.
        • not2b 5y ago
          But that model represented the input/output behavior of the neuron. Of course it doesn't represent the behavior of every single atom of the neuron itself, but that isn't relevant to its computational behavior.
• ud_0 5y ago
  > There's no rule that says it couldn't potentially use a large fraction of those atoms for its functionality There is no question that a neuron uses a large fraction of its atoms for its functionality, as is every other cell. What I think you're postulating is that these atoms form a functionally uber-complex network with mind-boggling combinatorics - but that position does not align well with current science. Single neurons are not that smart. For starters, they don't have the I/O address space or bandwidth to be, nor do they have the energy budget to behave like a block of Computronium. Neurons have not been opaque black boxes to us for a long time now. We understand a lot of the biochemical processes going on in there. We may not have a complete picture in many areas regarding many neuron types, but there is not enough unexplored space in there to allow for a cell-sized quantum supercomputer or anything like that. The upper bound on a neuron's computational complexity is dictated by the intricacies of its protein machinery, which is many many orders of magnitude lower than the number of atoms making up the whole.
  • lend000 5y ago
    While that's true, you need to consider that neurons don't act alone in a real system. Not only must one simulate the dozens of types of ligands and receptors in a typical neuron, but also how those ligands are modulated not only by neighbors, but also at a macro-scale (for example, if an organism increases serotonin levels due to some external stimuli, that will have significant effects across the nervous system, even parts that ostensibly have nothing to do with responding to that stimuli.) So given ~20 types of receptors, ~8 response types ranging from inverse agonist to full agonist, and conservatively, 20 relevant concentrations per ligand, we have over 3000 states dictated both by macro and local conditions.
    • ud_0 5y ago
      Forgive me if I misunderstood your intent, but this feels a little like moving the goal posts on me. In my comment, I was addressing the specific claim that we know little enough about neuronal complexity so the number of atoms in a cell could be seen as a reasonable upper bound on the complexity of the neuron. When you say I "need to consider" the complexities of response modulation and the combinatorics of the entire neuron population acting together, I disagree (purely in the context of the original claim, because that was specifically about the capabilities of a single neuron).
• eximius 5y ago
  I mean, there are some rules, actually. The structure of a neuron is not a black box about which we know nothing. There will be many atoms used to construct the cell wall, for example. Your analogy is like saying my computer has X number of atoms, so they might all be used for computation! Instead, we know that, for example, the case is not used for computation. The power supply is not used for computation, etc.