Title: Integration of Landmark Information into Putative Head Direction Ring Attractor Networks in Retrosplenial Cortex.

Head direction (HD) cells are directionally tuned neurons that function as an allocentric (world-centered) neural compass when animals navigate throughout the environment. Classic computational models of HD cells suggested that HD cells are driven by angular velocity path integration, accumulating errors unless reset by external inputs (e.g., visual inputs). Developed in the 1990s, the HD ring attractor model has become partly outdated, challenged by experimental findings that distal cues exert greater influence over HD cells than proximal cues, indicating that HD networks do not weigh all the visual cues equally. The classic ring attractor model avoids differentiation among various landmarks during their integration into the HD representations by placing the visual cues at infinity. However, real-world environments present complex and proximal visual cues, and experimental data on how different types of visual information are integrated into the HD ring attractor core remains absent. Our proposal aims to address these gaps by using high-density Neuropixels 2.0 probes to record HD cells in the retrosplenial cortex (RSC) as rats navigate a virtual reality apparatus.