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- W4360839595 abstract "An animal entering a new environment typically faces three challenges: explore the space for resources, memorize their locations, and navigate towards those targets as needed. Experimental work on exploration, mapping, and navigation has mostly focused on simple environments – such as an open arena [55], a pond [35], or a desert [37] – and much has been learned about neural signals in diverse brain areas under these conditions [11, 45]. However, many natural environments are highly complex, such as a system of burrows, or of intersecting paths through the underbrush. The same applies to many cognitive tasks, that typically allow only a limited set of actions at any given stage in the process. Here we propose an algorithm that learns the structure of a complex environment, discovers useful targets during exploration, and navigates back to those targets by the shortest path. It makes use of a behavioral module common to all motile animals, namely the ability to follow an odor to its source [4]. We show how the brain can learn to generate internal “virtual odors” that guide the animal to any location of interest. This endotaxis algorithm can be implemented with a simple 3-layer neural circuit using only biologically realistic structures and learning rules. Several neural components of this scheme are found in brains from insects to humans. Nature may have evolved a general mechanism for search and navigation on the ancient backbone of chemotaxis." @default.
- W4360839595 created "2023-03-25" @default.
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- W4360839595 date "2023-03-24" @default.
- W4360839595 modified "2023-10-03" @default.
- W4360839595 title "Endotaxis: A neuromorphic algorithm for mapping, goal-learning, navigation, and patrolling" @default.
- W4360839595 doi "https://doi.org/10.7554/elife.84141" @default.
- W4360839595 hasPublicationYear "2023" @default.
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