Fig. 3

The different internal structures in the ACC and the hippocampus reflect different representations of locations and actions. a Pearson correlation between ensemble activity patterns from the two sides of the linear track, for each behavioral state, for data recorded in the ACC (left) and hippocampal CA1 (right). Ensemble activity patterns consist of concatenated epochs from a given behavioral state on the same side of the track. Data show means for N = 3 mice in the ACC and N = 4 mice in the CA1. b An example trajectory-phase cell recorded in the ACC (left) and an example place cell recorded in the hippocampus (right). The black lines show the positions of the animals, and the green and red dots show the activity of the neurons during rightward and leftward running, respectively. c Distribution of decoding error of trajectory phase for data recorded in the ACC (blue) and CA1 (red). The decoder was trained on data from running in one direction and tested on data from running in the other direction. Inset, cumulative fraction of the absolute decoder error. d Pearson correlation between ensemble activity patterns across different spatial locations on the linear track, for data recorded in the ACC (left) and CA1 (right). Ensemble activity patterns consist of concatenated epochs from a given location, separated according to the two running directions. e Pearson correlation (mean ± SEM) between ensemble activity patterns from the two sides of the linear track, given the same trajectory phase, for data recorded in the ACC (blue) and CA1 (red). Ensemble activity patterns are defined as the mean event rate for each neuron given a spatial bin and running direction. Data in c-e pooled from N = 3 mice in the ACC and N = 4 mice in the CA1