Heterogeneous single-cell dynamics support stable population codes for objects in the mouse anterior cingulate cortex

Abstract

Remembering object locations is crucial for survival, yet how the anterior cingulate cortex (ACC) encodes spatial features across repeated experiences has not been fully characterized. Using longitudinal calcium imaging in freely moving mice, we tracked excitatory ACC neurons while animals explored objects across multiple days. We demonstrate that the ACC employs a highly dynamic coding strategy: while the overall proportion of object-responsive neurons remains constant across sessions, the specific identities of these cells fluctuate, showing a continuous turnover alongside a small, stable core. This dynamic coding is modulated by behavior, with high-exploring mice exhibiting greater cellular stability. Crucially, population-level analyses reveal that stable spatial representations emerge from collective dynamics rather than fixed single-cell identities. Population decoding demonstrates that information becomes linearly separable and highly efficient at a coarser ensemble scale. Thus, the ACC achieves representational stability through emergent network organization despite persistent single-cell dynamics.