From neural circuits to adaptive spatial navigation: A comprehensive review of brain-inspired navigation techniques

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Authors: Yixin Liu, Zhihao Zhang, Lingling Wang, Li Fu, Maria S. Selezneva, Konstantin A. Neusypin
Cited by: 2
References: 115

Abstract

Brain-inspired navigation technology, which is derived from the neural mechanisms of the animal brain, demonstrates notable adaptability and energy efficiency. It offers solutions to the shortcomings of conventional analytical navigation systems in complex and dynamic environments. This approach effectively combines spatial cognition and path planning by integrating multimodal information perception, modeling navigation cells, and utilizing brain-inspired neural network algorithms. In particular, adaptability plays a central role in enabling systems to cope with environmental variability, sensor uncertainty and unexpected disturbances. However, challenges remain in enhancing information fusion accuracy, system robustness and real-time performance. Future research should emphasize investigating adaptive neural mechanisms in animals to guide the development of biologically plausible and computationally efficient navigation systems that can operate flexibly and reliably in real-world scenarios.

Fields of Study & Subjects

Spatial Cognition and Navigation Tactile and Sensory Interactions EEG and Brain-Computer Interfaces

Publication details

Journal / source
Measurement
Publisher
Elsevier BV
Volume
271
Pages
121046–121046
Publication date
3 March 2026
Language
EN