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Sensory perception relies on fitness-maximizing codes

Jonathan Schaffner, Sherry Dongqi Bao, Philippe N. Tobler, Todd A. Hare (todd.hare@econ.uzh.ch) and Rafael Polania (rafael.polania@hest.ethz.ch)
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Jonathan Schaffner: University of Zurich
Sherry Dongqi Bao: University of Zurich
Philippe N. Tobler: University of Zurich
Todd A. Hare: University of Zurich
Rafael Polania: Neuroscience Center Zurich

Nature Human Behaviour, 2023, vol. 7, issue 7, 1135-1151

Abstract: Abstract Sensory information encoded by humans and other organisms is generally presumed to be as accurate as their biological limitations allow. However, perhaps counterintuitively, accurate sensory representations may not necessarily maximize the organism’s chances of survival. To test this hypothesis, we developed a unified normative framework for fitness-maximizing encoding by combining theoretical insights from neuroscience, computer science, and economics. Behavioural experiments in humans revealed that sensory encoding strategies are flexibly adapted to promote fitness maximization, a result confirmed by deep neural networks with information capacity constraints trained to solve the same task as humans. Moreover, human functional MRI data revealed that novel behavioural goals that rely on object perception induce efficient stimulus representations in early sensory structures. These results suggest that fitness-maximizing rules imposed by the environment are applied at early stages of sensory processing in humans and machines.

Date: 2023
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DOI: 10.1038/s41562-023-01584-y

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