The hippocampus converts dynamic entorhinal inputs into stable spatial maps

Abstract

The medial entorhinal cortex (MEC)-hippocampal network plays a key role in the processing, storage, and recall of spatial information. However, how the spatial code provided by MEC inputs relates to spatial representations generated by principal cell assemblies within hippocampal subfields remains enigmatic. To investigate this coding relationship, we employed two-photon calcium imaging in mice navigating through dissimilar virtual environments. Imaging large MEC bouton populations revealed spatially tuned activity patterns. MEC inputs drastically changed their preferred spatial field locations between environments, whereas hippocampal cells showed lower levels of place field reconfiguration. Decoding analysis indicated that higher place field reliability and larger context-dependent activity-rate differences allow low numbers of principal cells, particularly in the DG and CA1, to provide information about location and context more accurately and rapidly than MEC inputs. Thus, conversion of dynamic MEC inputs into stable spatial hippocampal maps may enable fast encoding and efficient recall of spatio-contextual information.

Keywords: context; decoder; dentate gyrus; episodic memory; hippocampus; medial entorhinal cortex; population activity; space; two-photon imaging; virtual reality.

Graphical abstract

Figure 1

Two-photon calcium imaging of MEC boutons activity in the hippocampus in two virtual environments (A) Experimental schematic of our virtual-reality setup for mice. (B) Top, schematic of the two familiar virtual contexts; bottom, timeline of a recording session. (C) GCaMP6s-labeled MEC neurons (green); tissue counterstained with DAPI (blue). (D) Imaging window implantation site. Axonal projections from the MEC (GCaMP6s, green) over DAPI staining (blue). Red dotted lines, imaging planes in CA1, CA3, and DG. (E) Calcium activity of axonal projections imaged in CA1, CA3, and DG. (F) Raw calcium traces (gray) with significant transients (red) and linear-track position (blue) of a MEC-to-CA3 bouton showing place fields over time; left, context A; middle, context B; right, calcium activity over track distance of the same bouton in context A (top) and B (bottom). (G) Same as (F) for a MEC-to-DG bouton having place fields (see STAR Methods). (H) Top, fraction of active (>2 transients per min) boutons. Middle, boutons showing significant spatial information. Bottom, boutons with single or multiple place fields. Test for population overlap (χ² test). (I and L) Mean calcium activity for all boutons (BT) and principal cells (PC). (J and M) Spatial information of all active BTs and PCs. (K and N) Width of place fields in context A for all place BTs and PCs. (I–K) Rank-sum tests, per region (CA1/CA3/DG). (L–N) ANOVA on ranks, Dunn’s test, per functional domain (BT/PC). Boxes, 25th to 75th percentiles; bars, median; whiskers, 99% range. Values represent number of BTs/PCs. NS, not significant; ^∗p < 0.05; ^∗∗p < 0.01; ^∗∗∗p < 0.001. For exact p values, see Table S1.

Figure 2

MEC spatial boutons show low reliability over multiple exposures to the same context (A) Activity maps of MEC-to-CA1 (top), MEC-to-CA3 (middle), and MEC-to-DG (bottom) place-modulated boutons during the first (left), second (middle), and third (right) blocks of runs in context A. (B) Same as A for principal cells (PC) in CA1, CA3, and DG, respectively. (C) Mean trial-to-trial reliability of place boutons (BT) and PC responses in context A. (D) Mean activity correlations between first and second blocks of runs in context A (A-A′) and first and third blocks of runs in context A (A-A′′) for place boutons. (E) Same as (D) for PC. (F) Mean activity correlations between first and second blocks of runs in context A; comparison between place BTs and PCs for each hippocampal region. (G) Same as (F) for the first and third blocks of runs. (C–E) ANOVA on ranks, Dunn’s test. (F and G) Rank Sum-Tests, per region (CA1/CA3/DG). Values represent number of BTs/PCs. Boxes, 25th to 75th percentiles; bars, median; whiskers, 99% range. NS, not significant; ^∗p < 0.05; ^∗∗∗p < 0.001. For exact p values, see Table S1. For context B, see Figure S9.

Figure 3

MEC boutons targeting hippocampal areas discriminate between contexts (A and B) Activity-rate difference scores (see STAR Methods) between contexts A and B. Comparison of hippocampal regions (A) and functional domains (boutons/cells, B). BT, boutons; PC, principal cells. (C) Left, activity maps of MEC-to-CA1 (top), MEC-to-CA3 (middle) or MEC-to-DG (bottom) BT having place fields in context A. Left, activity in context A; right, activity in context B; all blocks of runs in each context were merged. Right, similar to left for CA1 (top), CA3 (bottom), and DG (bottom) PC. (D) Mean activity correlations between all runs in contexts A and B of boutons having place fields in context A. (E) Mean activity correlations between first and second blocks of runs in context A (A-A′) and first block in A and first block in B (A-B) of place BT (left) and PC (right). (A) Rank-sum tests, per region (CA1/CA3/DG). (B and E) ANOVA on ranks, Dunn’s test, per functional domain (BT/PC). (D) ANOVA on ranks, Dunn’s test. Boxes, 25th to 75th percentiles; bars, median; whiskers, 99% range. Values represent number of BTs/PCs. NS, not significant; ^∗p < 0.05; ^∗∗p < 0.01; ^∗∗∗p < 0.001. For exact p values, see Table S1.

Figure 4

Decoding of space and context from neuronal activity (A) Decoding example. Top, activity of CA1 place cells over time; bottom, decoder output. White line denotes true position of the mouse, and green dots, the most likely decoded position. (B) Spatial (colored lines) and contextual (gray lines) decoding error as a function of the number of neurons used simultaneously for decoding. (C) Average spatial errors for ensembles of 50 cells or MEC boutons. (D) Same as (C) for context errors. (E) Ratio of spatial decoding errors from the half of the datasets with the highest values of each parameter divided by the lowest half. Open circles denote the mean of each region, filled circles the overall mean. The spatial error ratio is plotted for data split by activity-rate (rate), spatial information (SI), trial-to-trial reliability (rel), short-term consistency among sessions (A-A′), the inverse of the activity-map correlation between context A and B (−(A-B)), and the activity difference score between context A and B (DiffSc). (F) Same as (E) for context errors. (G) Ratio of context-decoding errors obtained using a template based on context-specific spatial maps divided by errors obtained using mean activity-rate per context only (Err_aSC/Err_aC; see also Figure S15B). (H) Cumulative probability for decoding the correct context as a function of time and ensemble size for boutons (left) and cells (right). (I) Average time to 90% context-decoding accuracy for a fixed ensemble size of 50 cells or boutons, respectively. (C, D, and I) Kruskal-Wallis, Dunn’s test. (E–G) Paired t test between upper and lower half (E and F) or template type (G), respectively. Boxes, 25th to 75th percentiles; bars, median; whiskers, 99% range. NS, not significant; ^∗p < 0.05; ^∗∗p < 0.01; ^∗∗∗p < 0.001. For exact p values, see Table S1.