Author Response: Endotaxis: A neuromorphic algorithm for mapping, goal-learning, navigation, and patrolling
Year: 2023
Type: peer-review
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 [68], a pond [42], or a desert [44] -and much has been learned about neural signals in diverse brain areas under these conditions [12, 54].However, many natural environments are highly structured, such as a system of burrows, or of intersecting paths through the underbrush.Similarly, for many cognitive tasks, a sequence of simple actions can give rise to complex solutions.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. eLife assessmentThis valuable work proposes a framework inspired by chemotaxis for understanding how the brain might implement behaviours related to navigating toward a goal.The evidence supporting the conceptual claim is convincing.The manuscript proposes a hypothesis that would be of interest to the broad systems neuroscience community, although it was noted the relationship to existing similar hypotheses could be clarified.
Source: eLife
Institution: California Institute of Technology
Language: English
Topic: Memory and Neural Mechanisms
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,500
Funder: National Science Foundation
OpenAlex ID: W4388696755