Omer Hazon

All Publications

• Heterogeneous single-cell dynamics support stable population codes for objects in the mouse anterior cingulate cortex. Cell reports Descamps, L. A., Clawson, W. P., Carvalho, M. M., Rogerson, T., Hazon, O., Chadney, O. M., Schnitzer, M. J., Kentros, C. 2026; 45 (9): 117890

  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.

  View details for DOI 10.1016/j.celrep.2026.117890

  View details for PubMedID 42658677

• Noise correlations in neural ensemble activity limit the accuracy of hippocampal spatial representations. Nature communications Hazon, O., Minces, V. H., Tomas, D. P., Ganguli, S., Schnitzer, M. J., Jercog, P. E. 2022; 13 (1): 4276

  Abstract

  Neurons in the CA1 area of the mouse hippocampus encode the position of the animal in an environment. However, given the variability in individual neurons responses, the accuracy of this code is still poorly understood. It was proposed that downstream areas could achieve high spatial accuracy by integrating the activity of thousands of neurons, but theoretical studies point to shared fluctuations in the firing rate as a potential limitation. Using high-throughput calcium imaging in freely moving mice, we demonstrated the limiting factors in the accuracy of the CA1 spatial code. We found that noise correlations in the hippocampus bound the estimation error of spatial coding to ~10cm (the size of a mouse). Maximal accuracy was obtained using approximately [300-1400] neurons, depending on the animal. These findings reveal intrinsic limits in the brain's representations of space and suggest that single neurons downstream of thehippocampus can extract maximal spatial information from several hundred inputs.

  View details for DOI 10.1038/s41467-022-31254-y

  View details for PubMedID 35879320