【Abstract】　Physiological　studies　have　revealed　that　rats　perform　spatial　localization　relying　on　grid　cells　and　place　cells　in　the　entorhinal-hippocampal　CA3　structure.　The　dynamic　connection　between　the　entorhinal-hippocampal　structure　and　the　prefrontal　cortex　is　crucial　for　navigation.　Based　on　these　findings,　this　paper　proposes　a　spatial　navigation　method　based　on　the　entorhinal-hippocampal-prefrontal　information　transmission　circuit　of　the　rat’s　brain,　with　the　aim　of　endowing　the　mobile　robot　with　strong　spatial　navigation　capability.　Using　the　hippocampal　CA3-prefrontal　spatial　navigation　model　as　a　foundation,　this　paper　constructed　a　dynamic　self-organizing　model　with　the　hippocampal　CA1　place　cells　as　the　basic　unit　to　optimize　the　navigation　path.　The　path　information　was　then　fed　back　to　the　impulse　neural　network　via　hippocampal　CA3　place　cells　and　prefrontal　cortex　action　neurons,　improving　the　convergence　speed　of　the　model　and　helping　to　establish　long-term　memory　of　navigation　habits.　To　verify　the　validity　of　the　method,　two-dimensional　simulation　experiments　and　three-dimensional　simulation　robot　experiments　were　designed　in　this　paper.　The　experimental　results　showed　that　the　method　presented　in　this　paper　not　only　surpassed　other　algorithms　in　terms　of　navigation　efficiency　and　convergence　speed,　but　also　exhibited　good　adaptability　to　dynamic　navigation　tasks.　Furthermore,　our　method　can　be　effectively　applied　to　mobile　robots.　©　2024　West　China　Hospital,　Sichuan　Institute　of　Biomedical　Engineering.　All　rights　reserved.