In　current　computation　neuroscience,　it　is　widely　accepted　that　the　mammalian　entorhinal-hippocampus　complex　provides　representations　of　spatial　environment,　exhibiting　specific　responses　to　particular　locations　and　directions.　Various　computation　models　of　spatial　cell　firing　have　been　proposed　to　unravel　the　mysteries　of　spatial　cognition　representation　in　the　brain.　However,　an　increasing　body　of　experimental　evidence　suggests　that　the　brain　operates　more　akin　to　a　predictive　system.　Actively　acquiring　and　utilizing　limited　environmental　information,　the　brain　constructs　internal　models　during　interaction　with　the　external　world,　generating　predictive　representations　of　internal　states　following　environmental　changes.　Building　upon　this　premise,　we　propose　a　predictive　coding　theory-based　entorhinal-hippocampus　spatial　cognition　model.　This　model　incorporates　vestibular　proprioceptive　cues　and　border　vector　cells　discharge　responses　to　initially　derive　unimodal　place　cell　discharge　fields,　followed　by　hippocampal　place　cells　projecting　to　the　entorhinal　cortex　via　excitatory-inhibitory　synaptic　connections,　ultimately　generating　periodic　hexagonal　grid　cell　discharge　fields.　Experimental　results　demonstrate　that　the　neuronal　discharge　patterns　obtained　by　this　model　align　with　physiological　research　findings,　thereby　providing　new　insights　for　further　investigations　into　brain　cognitive　mechanisms.　©　2024　Technical　Committee　on　Control　Theory,　Chinese　Association　of　Automation.