Princeton Neuroscience Institute, Princeton University, Princeton, United States; Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, United States; Department of Molecular Biology, Princeton University, Princeton, United States
Yi Gu
Princeton Neuroscience Institute, Princeton University, Princeton, United States; Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, United States; Department of Molecular Biology, Princeton University, Princeton, United States
Dmitriy Aronov
Princeton Neuroscience Institute, Princeton University, Princeton, United States; Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, United States; Department of Molecular Biology, Princeton University, Princeton, United States
Princeton Neuroscience Institute, Princeton University, Princeton, United States; Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, United States; Department of Molecular Biology, Princeton University, Princeton, United States
During spatial navigation, animals use self-motion to estimate positions through path integration. However, estimation errors accumulate over time and it is unclear how they are corrected. Here we report a new cell class (‘cue cell’) encoding visual cues that could be used to correct errors in path integration in mouse medial entorhinal cortex (MEC). During virtual navigation, individual cue cells exhibited firing fields only near visual cues and their population response formed sequences repeated at each cue. These cells consistently responded to cues across multiple environments. On a track with cues on left and right sides, most cue cells only responded to cues on one side. During navigation in a real arena, they showed spatially stable activity and accounted for 32% of unidentified, spatially stable MEC cells. These cue cell properties demonstrate that the MEC contains a code representing spatial landmarks, which could be important for error correction during path integration.
