AUTHOR=Chen Runping , Kunde Gerd J. , Tao Louis , Sornborger Andrew T. TITLE=Foveal vision reduces neural resources in agent-based game learning JOURNAL=Frontiers in Neuroscience VOLUME=Volume 19 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1547264 DOI=10.3389/fnins.2025.1547264 ISSN=1662-453X ABSTRACT=Efficient processing of information is crucial for the optimization of neural resources in both biological and artificial visual systems. In this paper, we study the efficiency that may be obtained via the use of a fovea. Using biologically-motivated agents, we study visual information processing, learning, and decision making in a controlled artificial environment, namely the Atari Pong video game. We compare the resources necessary to play Pong between agents with and without a fovea. Our study shows that a fovea can significantly reduce the neural resources, in the form of number of neurons, number of synapses, and number of computations, while at the same time maintaining performance at playing Pong. To our knowledge, this is the first study in which an agent must simultaneously optimize its visual system, along with its decision making and action generation capabilities. That is, the visual system is integral to a complete agent.