Mimicking Associative Learning of Rats via a Neuromorphic Robot in Open Field Maze Using Spatial Cell Models

Data-driven Artificial Intelligence (AI) approaches have exhibited remarkable prowess across various cognitive tasks using extensive training data. However, the reliance on large datasets and neural networks presents challenges such as high-power consumption and limited adaptability, particularly in...

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Bibliographic Details

Published in:	2024 International Conference on Neuromorphic Systems (ICONS) pp. 299 - 306
Main Authors:	Liu, Tianze, Bakr Siddique, Md Abu, An, Hongyu
Format:	Conference Proceeding
Language:	English
Published:	IEEE 30.07.2024
Subjects:	Associative Learning Biological system modeling Cells (biology) Cognition Grid Cells Navigation Neuromorphic Robotics Neuromorphics Place Cells Real-time systems Robots Rodents Testing Training data
Online Access:	Get full text
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