Mar 24, 2016

Neural mechanisms for reward-modulated vector learning and navigation: from social insects to embodied agents

BioRxiv : the Preprint Server for Biology
Dennis GoldschmidtSakyasingha Dasgupta


Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories anchored globally to the nest or visual landmarks. Although existing computational models reproduced similar behaviors, they largely neglected evidence for possible neural substrates underlying the generated behavior. Therefore, we present here a model of neural mechanisms in a modular closed-loop control - enabling vector navigation in embodied agents. The model consists of a path integration mechanism, reward-modulated global and local vector learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns in circular arrays. A reward-modulated...Continue Reading

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