Introducing the brain: saving energy consumption (Introduction)

by David Turell @, Friday, January 14, 2022, 19:17 (6 days ago) @ David Turell

Important since our brain uses 20% of daily consumption:

"Published in the scientific journal Communications Biology, the study first shows how the free-energy principle is the basis for any neural network that minimizes energy cost. Then, as proof of concept, it shows how an energy minimizing neural network can solve mazes. This finding will be useful for analyzing impaired brain function in thought disorders as well as for generating optimized neural networks for artificial intelligences.

"Biological optimization is a natural process that makes our bodies and behavior as efficient as possible. A behavioral example can be seen in the transition that cats make from running to galloping. Far from being random, the switch occurs precisely at the speed when the amount of energy it takes to gallop becomes less that it takes to run. In the brain, neural networks are optimized to allow efficient control of behavior and transmission of information, while still maintaining the ability to adapt and reconfigure to changing environments.

"'We were able to demonstrate that standard neural networks, which feature delayed modulation of Hebbian plasticity, perform planning and adaptive behavioral control by taking their previous 'decisions' into account," says first author and unit leader Takuya Isomura. "Importantly, they do so the same way that they would when following the free-energy principle."

"Once they established that neural networks theoretically follow the free-energy principle, they tested the theory using simulations. The neural networks self-organized by changing the strength of their neural connections and associating past decisions with future outcomes. In this case, the neural networks can be viewed as being governed by the free-energy principle, which allowed it to learn the correct route through a maze through trial and error in a statistically optimal manner.

"These findings point toward a set of universal mathematical rules that describe how neural networks self-optimize. As Isomura explains, "Our findings guarantee that an arbitrary neural network can be cast as an agent that obeys the free-energy principle, providing a universal characterization for the brain.'"

Comment: I assume the initial neurons in the first sapiens brain had this designed ability, and that that ability to conserve energy was present in all previous ancestors. Since brain activity is so fuel-costly as brains became larger this system was vital to maintain an energy metabolism that could be fed properly by keeping it in limits. Chanced uncontrolled design of the brain could lead to run away costs.

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