A Hippocampus Spatial Cognition Model based on Predictive Coding

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.