{"title":"Grid cell modules coordination improves accuracy and reliability for spatial navigation.","authors":"Luca Sarramone, Jose A Fernandez-Leon","doi":"10.1007/s11571-025-10263-9","DOIUrl":null,"url":null,"abstract":"<p><p>Most mammals efficiently overcome self-localization deviations by coordinating grid and place cells in their brain's navigation system. However, the coordination of grid cell modules during spatial navigation and its impact on position estimation are poorly understood. This study addresses this issue by introducing a system that decodes grid-cell module activity and integrates networks of multiple grid-cell modules for self-position estimation in a mobile robot. Our results show that even when individual grid module estimates deviated substantially from the robot's actual location, the modules remained tightly coordinated. Corrections of these deviations were studied based on anchoring the activity of grid cells to spatial landmarks. Detailed numerical investigations indicate that path integration is critically dependent on the intrinsic coordination between grid cell modules which enhances the accuracy and reliability of spatial navigation. Furthermore, we show that this coordination enables effective vector navigation, even when the overall position estimation is inaccurate. These insights advance our understanding of grid-cell module coordination in location estimation during path integration and offer potential applications in robotics.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"76"},"PeriodicalIF":3.1000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12089575/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Neurodynamics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11571-025-10263-9","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/19 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Most mammals efficiently overcome self-localization deviations by coordinating grid and place cells in their brain's navigation system. However, the coordination of grid cell modules during spatial navigation and its impact on position estimation are poorly understood. This study addresses this issue by introducing a system that decodes grid-cell module activity and integrates networks of multiple grid-cell modules for self-position estimation in a mobile robot. Our results show that even when individual grid module estimates deviated substantially from the robot's actual location, the modules remained tightly coordinated. Corrections of these deviations were studied based on anchoring the activity of grid cells to spatial landmarks. Detailed numerical investigations indicate that path integration is critically dependent on the intrinsic coordination between grid cell modules which enhances the accuracy and reliability of spatial navigation. Furthermore, we show that this coordination enables effective vector navigation, even when the overall position estimation is inaccurate. These insights advance our understanding of grid-cell module coordination in location estimation during path integration and offer potential applications in robotics.
期刊介绍:
Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models.
The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome.
The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged.
1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics.
2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages.
3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.