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

ABSTRACT: Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. Taking a particular energy-efficient viewpoint, we define neural computation and make use of an energy-constrained computational function. This function can be optimized over a variable that is proportional to the number of synapses per neuron. This function also implies a specific distinction between adenosine triphosphate (ATP)-consuming processes, especially computation per se vs. the communication processes of action potentials and transmitter release. Thus, to apply this mathematical function requires an energy audit with a particular partitioning of energy consumption that differs from earlier work. The audit points out t

SUBMITTER: Levy WB 

PROVIDER: S-EPMC8106317 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature