Two-Phase Coding Strategy by CA1 Pyramidal Neurons: Linking Spatiotemporal Integration to Predictive Behavior

Abstract

Space and time are fundamental components of memory, yet how the brain encodes these dimensions to guide behavior remains unclear. Using virtual-reality environments, we uncovered a two-phase neural code in hippocampus CA1 that represents time or distance through two functional pyramidal subpopulations, PyrUp and PyrDown. In Phase I, PyrUp activity synchronously increases to mark the initiation of encoding; In Phase II, their activity decays at heterogeneous, neuron-specific rates, creating a gradual divergence in across-population firing rates that scales with elapsed time. Conversely, PyrDown activity initially decreases before gradually rising. The crossover point, where rising PyrDown activity surpasses declining PyrUp activity, precedes predictive licking behavior. Combining optogenetics and computational modeling, we provided circuit-level evidence that PyrUp neurons primarily process locomotion-related inputs regulated by somatostatin-positive interneurons, whereas PyrDown neurons mainly receive reward-related inputs gated by parvalbumin-positive interneurons. These findings advance our understanding of how hippocampal circuits compute spatiotemporal information to inform behavior.