The balance of forward and backward hippocampal sequences shifts across behavioral states

Abstract

Place cell firing patterns in the rat hippocampus are often organized as sequences. Sequences falling within cycles of the theta (6-10 Hz) local field potential (LFP) oscillation represent segments of ongoing behavioral trajectories. Sequences expressed during sharp wave ripple (SWR) complexes represent spatial trajectories through the environment, in both the same direction as actual trajectories (forward sequences) and in an ordering opposite that of behavior (backward sequences). Although hippocampal sequences could fulfill unique functional roles depending on the direction of the sequence and the animal's state when the sequence occurs, quantitative comparisons of sequence direction across behavioral and physiological states within the same experiment, employing consistent methodology, are lacking. Here, we used cross-correlation and Bayesian decoding to measure the direction of hippocampal sequences in rats during active behavior, awake rest and slow-wave sleep. During pretask sleep, few sequences were detected in either direction. Sequences within theta cycles during active behavior were overwhelmingly forward. Sequences during quiescent moments of behavior were both forward and backward, in equal proportion. During postbehavior sleep, sequences were again expressed in both directions, but significantly more forward than backward sequences were detected. The shift in the balance of sequence direction could reflect changing functional demands on the hippocampal network across behavioral and physiological states.

Figure 1

Examples of spatial firing rate maps and cross-correlograms for two cell pairs. Firing rate maps are normalized for ease of visual comparison (peak rate of the cell is indicated in the bottom-right corner of each rate map). During the pre-run epoch, little coordinated spiking is present. In contrast, during the run-theta epoch a strong, theta-modulated correlation is apparent. During the run-LIA and post-run epochs, peaks in the correlograms consistent with forward and backward-ordered sequential activity are present.

Figure 2

Cross-correlograms of cell pairs exhibiting place fields during behavior. The color scale is equal for all panels (more intense colors indicate greater correlation strength). The maximum value in each 1 ms time bin is marked with a blue dot. Correlations were unpatterned preceding behavior (pre-run). During the run-theta epoch, forward correlations due to the nearby place fields (large band of heightened correlation across the entire window) and due to sequences within theta cycles (smaller bands spaced at approximately 120 ms intervals) are visible. Correlation patterns during the run-LIA epoch suggest both forward and backward sequences, as evidenced by bands of activity along both diagonals. During the post-run epoch, heightened activity is again present along both diagonals.

Figure 3

To quantify the strength of correlations in each direction, we compared pixels in the quadrants of correlograms corresponding to forward and backward sequences. Correlation strength did not differ for the pre-run and run-LIA epochs. However, forward correlations were significantly stronger during the run-theta and post-run conditions.

Figure 4

A Bayesian decoding algorithm was used to estimate spatial trajectories represented by firing sequences. The top panel shows decoding as a subject runs a trajectory around the track. The peak of the decoded posterior distribution for each time step (top left) matches the animal’s position each moment in time. Similarly, decoded position tracks actual location well (top right). The bottom panel displays the mean decoded posterior distribution for each position in space within the run-theta epoch. Food delivery locations are marked with white lines. Decoded probability is concentrated along the diagonal, indicating accurate spatial decoding.

Figure 5

Four decoded firing sequences from the run-LIA (first column) and post-run (second column) epochs. The left-hand plot for each sequence shows rasters of place cell spiking. Cells are ordered by the position of their place fields on the maze (cells with multiple fields are plotted at the position of the field with the highest firing rate). Panels below each raster show the ripple band-pass filtered LFP. The right-hand plot for each sequence is the decoded probability distribution, with position on the y axis and time on the×axis. Food delivery locations are indicated with white lines, and the decoded position at each time step containing at least one spike is marked with a white dot.

Figure 6

To measure sequence direction we fit regression lines to the cumulative sum of differences between consecutive decoded positions. Forward sequences have positive slopes, while backward sequences have negative slopes. Histograms of sequence slopes are shown, with a vertical grey line at zero. To assess the balance of forward and backward sequences, we used a sign-rank test to test if medians of the distributions were significantly different than zero. The medians of distributions were not different than zero for the pre-run and run-LIA conditions. However, medians were significantly greater than zero during the run-theta and post-run epochs.