Hippocampus leads ventral striatum in replay of place-reward information

Abstract

Associating spatial locations with rewards is fundamental to survival in natural environments and requires the integrity of the hippocampus and ventral striatum. In joint multineuron recordings from these areas, hippocampal-striatal ensembles reactivated together during sleep. This process was especially strong in pairs in which the hippocampal cell processed spatial information and ventral striatal firing correlated to reward. Replay was dominated by cell pairs in which the hippocampal "place" cell fired preferentially before the striatal reward-related neuron. Our results suggest a plausible mechanism for consolidating place-reward associations and are consistent with a central tenet of consolidation theory, showing that the hippocampus leads reactivation in a projection area.

Figure 1. Sparse hippocampal and ventral striatal ensemble firing patterns during track running and postbehavioral rest.

Example of the firing patterns of concurrently recorded hippocampal (HC1–HC4) and ventral striatal (VS1–VS3) cells during track running (A) and QW-SWS (B). Only cells that exhibited a place field or a reward-related correlate are shown in these graphs. Local field potentials recorded near the hippocampal fissure (A) and the hippocampal pyramidal cell layer (B) are plotted in parallel. (A) When the rat ran along the triangular track, the LFP displayed an oscillation of theta frequency (6–10 Hz, top: raw trace; bottom: filtered trace [6–10 Hz]). During the plotted period of 25 s, the rat encountered six reward sites (s = sucrose solution, v = vanilla desert, c = chocolate mousse) of which three contained a reward (green arrow) and the others were empty (red arrows). Each row in the black field represents one cell; its spikes are shown with colored dots. (B) During QW-SWS, the LFP displays large irregular activity intermitted with sharp wave-ripple complexes (top: raw trace; bottom: filtered trace [100–250 Hz]). Identified ripples are indicated with an asterisk (*). Several units that were activated during track running were reactivated within a short time period. Note the different time scales in (A and B). The relative firing order of pairs of HC and VS cells roughly corresponds to that observed during behavior (A).

Figure 2. Coherent cross-structural reactivation in the hippocampal–ventral striatal circuitry.

(A) Diagrams representing firing pattern correlations for pairs of simultaneously recorded hippocampal and ventral striatal units during periods of active behavior and rest in a single session. Individual neurons are represented as dots around the perimeter of a circle (filled dots: hippocampal CA1 units, n = 10; open dots: ventral striatal units, n = 13). Lines indicate a significant firing correlation between two neurons (red: positive, yellow: negative correlations). A pattern of correlations emerges during track running and is reinstated in postbehavioral rest, whereas it was largely absent in rest preceding behavior. (B) The EV was significantly larger than the control value (REV) when compared across sessions (**p<0.01). Error bars represent the standard error of the mean (SEM). (C) Temporal dynamics of joint reactivation were examined in three 20-min blocks of rest. Reactivation occurs at least up to an hour of rest after the experience but decays gradually (***p<0.002). (D) Reactivation observed during QW-SWS (**p<0.01) was not different from that found for the entire rest episodes (Rest, *p<0.05; n = 13 sessions). Reactivation was not observed in REM sleep. Between-condition statistics hold for EV values and the difference between [EV−REV].

Figure 3. Reactivation of subgroups composed according to three firing pattern characteristics.

(A) Modulation by theta oscillations. Four examples show binned spike counts (upper panels, solid lines) in relation to the hippocampal theta rhythm (bottom panels) for two successive theta cycles. Randomization of spike intervals abolished the relation between firing pattern and theta rhythm (dashed lines). Distributions of EV and REV values for each subgroup, obtained with bootstrapping, showed significant reactivation in all but the VS only subgroups. Reactivation in the Both Cells group was significantly stronger than in the other groups (p<1×10⁴; right-hand panel). (B) Processing of place and reward information. The left panel shows the spatial distribution of local firing rates of two hippocampal–ventral striatal pairs. The rat's trajectory is shown in black, and the firing rate of the neurons is color coded, ranging from low rates in dark red to their individual maxima (top right corners) in yellow and white. The Double Correlates group reactivated significantly, whereas the other subgroups did not. PF: place field; RRU, reward-related unit. (C) Firing order was defined by the difference in area between the light- and dark-shaded regions of cross-correlograms. Reactivation was observed in all groups, but the HC→VS group reactivated more strongly than the other groups.

Figure 4. Order of firing is maintained in accelerated cross-structural replay.

(A) Cross-correlograms for three pairs of simultaneously recorded neurons showing the temporal relation of firing during prebehavioral rest, track running, and postbehavioral rest. Hippocampal activity is synchronized on ventral striatal firing (time = 0, bin size 20 ms). Spatially distributed firing patterns of the neurons are shown in the blue squares (left: HC, bottom: VS; see also Figure 3B). During track running, the three pairs of neurons show correlated firing with peaks at different offsets relative to time zero. This correlated firing was absent in prebehavioral rest but reinstated during postbehavioral rest (indicated by arrows). In the topmost example, a secondary peak during track running is recurring in postbehavioral rest (indicated by the asterisk [*]). The relative time offsets of peaks were preserved from track running to postbehavioral rest. (B) Scatter plots of the temporal offsets of the peaks in the cross-correlograms (CCG) during track running and prebehavioral rest (left) and postbehavioral rest (right). The peak offsets during track running were correlated to the peak-offsets during postbehavioral rest (R ² = 0.09, p<0.05), but not to prebehavioral rest. The peak offsets during postbehavioral rest were significantly reduced compared to track running, indicating accelerated reactivation. Note that cell pairs showing a significant peak in the cross-correlograms of track running and of at least one rest episode were included in analysis. Therefore, the number of data points is different in the left and the right panels.