To find out, David Beniaguev, Idan Segev and Michael London, all at the Hebrew University of Jerusalem, trained an artificial deep neural network to mimic the computations of a simulated biological neuron. They showed that a deep neural network requires between five and eight layers of interconnected “neurons” to represent the complexity of one single biological neuron.
Even the authors did not anticipate such complexity. “I thought it would be simpler and smaller,” said Beniaguev. He expected that three or four layers would be enough to capture the computations performed within the cell.
– Allison Whitten, “How Computationally Complex Is a Single Neuron?” at Quanta Magazine (September 22, 2021) the Paper Is Closed Access.News, “How complex is a single neuron in your brain?” at Mind Matters News
Takehome: An artificial intelligence network did not do nearly as well. Researchers showed that a deep neural network needs 5-8 layers of [artificial] interconnected “neurons” to mimic the complexity of one single biological neuron.
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