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Significance Engineers describe the human brain as a low-energy form of computation. However, from the simplest physical viewpoint, a neuron’s computation cost is remarkably larger than the best possible bits per joule—off by a factor of1 0 8 . Here we explicate, in the context of energy consumption, a definition of neural computation that is optimal given explicit constraints. The plausibility of this definition as Nature’s perspective is supported by an energy audit of the human brain. The audit itself requires modifying conventional perspectives and calculations revealing that communication costs are 35-fold computational costs.

Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number