A nerve is a cell that forms electrical links to other nerves. Nerves in the growing brain spread like plant roots in a dense mat to explore every link (Figure 6.34) but only those that are used survive. Neural Darwinism is that nerves compete to survive in the brain as species do in the world because unused nerves wither away over time (Edelman, 1987).
A nerve with up to five thousand dendrites (Figure 6.35) must find the combinations with other neurons that fire it as fast as possible to survive. This isn’t easy with so many combinations and it is more difficult due to noise – random firing variations not due to signal input.
Nerve tubulins can synchronize adjacent dendrites to allow them to cohere. It has been found that pyramidal dendrites don’t spike if inputs differ, even if either input alone gives a spike (Gidon, 2020). The computing result is an eXclusive OR (Note 1) gate not just a AND/OR gate as once supposed, a function that classical computing needs two steps to do. Quantum coherence lets dendrites compare close inputs in an XOR operation that reduces noise because nearby dendrites must agree to be accepted.
Instead of a dumb neuron, a transistor that just adds inputs, the nerve is a processing network whose dendrite layer purifies the data by inhibiting erratic input (Cepelwicz, 2020). Nerves evolved molecular computations based on quantum effects:
“Physicists thought the bustle of living cells would blot out quantum phenomena. Now they find that cells can nurture these phenomena – and exploit them.” (Vedral, 2015)
Neuroscience now sees the brain as a neural net (Figure 6.36) that uses quantum effects to explore its trillions of links by exponential learning (Yang & Zhang, 2020).
Note 1. An eXclusive OR operation compares two input bits and generates zero if the bits are the same and one if the bits are different. The XOR logic is widely used in cryptography.