Loss of functional heterogeneity along the CA3 transverse axis in aging

Abstract

Age-related deficits in pattern separation have been postulated to bias the output of hippocampal memory processing toward pattern completion, which can cause deficits in accurate memory retrieval. Although the CA3 region of the hippocampus is often conceptualized as a homogeneous network involved in pattern completion, growing evidence demonstrates a functional gradient in CA3 along the transverse axis, as pattern-separated outputs (dominant in the more proximal CA3) transition to pattern-completed outputs (dominant in the more distal CA3). We examined the neural representations along the CA3 transverse axis in young (Y), aged memory-unimpaired (AU), and aged memory-impaired (AI) rats when different changes were made to the environment. Functional heterogeneity in CA3 was observed in Y and AU rats when the environmental similarity was high (altered cues or altered environment shapes in the same room), with more orthogonalized representations in proximal CA3 than in distal CA3. In contrast, AI rats showed reduced orthogonalization in proximal CA3 but showed normal (i.e., generalized) representations in distal CA3, with little evidence of a functional gradient. Under experimental conditions when the environmental similarity was low (different rooms), representations in proximal and distal CA3 remapped in all rats, showing that CA3 of AI rats is able to encode distinctive representations for inputs with greater dissimilarity. These experiments support the hypotheses that the age-related bias toward hippocampal pattern completion is due to the loss in AI rats of the normal transition from pattern separation to pattern completion along the CA3 transverse axis.

Keywords: CA3; aging; hippocampus; hyperactivity; memory impairment; pattern completion; pattern separation; place cells; remapping.

Figure 1.. CA3 recording locations and experimental procedures.

(A) Recordings were made along the CA3 transverse axis. (B) A learning index (LI) score was derived from measures of proximity to the goal location during probe trials, with lower scores indicating more accurate performance. Aged rats that performed on par with young rats (below the dotted line, representing 2 S.D. above the mean of Y rats based on a large population study) were designated as aged-unimpaired (AU), and those that performed more poorly than young rats (above the dotted line) were designated as aged-impaired (AI), according to established criteria. (C) In the local-global cue mismatch experiment, recording sessions consisted of three standard (STD) sessions interleaved with two mismatch (MIS) sessions. In the STD sessions, the local cues on the track (denoted by the inner ring with four different textures) and the global cues along the curtain at the periphery (denoted by the black outer ring) were arranged in a fixed configuration that the rat had experienced during training periods. In the MIS sessions, the global cues were rotated in a clockwise direction and the local cues were rotated in a counterclockwise direction by the same amount, for a net mismatch of 90°, 135°, or 180°. (D) In the two-shape experiment, recording sessions consisted of 4 sessions (two sessions in a circle and two sessions in a square) in room A. In the two-room experiment, after 4 sessions in room A, two additional sessions (one session each in circle and square) were recorded in room B. Different cue cards and paper floor were used in each room (see STAR Methods). See also Figure S1.

Figure 2.. Responses to the cue manipulations differ among the groups along the CA3 transverse axis.

(A) Examples of five different response types observed in CA3. “Rotate” cells were defined as cells with place fields in both standard and mismatch sessions that either followed the local cues (by rotating their fields CCW between STD1 and MIS sessions), followed the global cues (by rotating their fields CW), or were affected by both sets of cues (ambiguous (AMB) rotation). “Remap” cells were defined as cells with place fields that APPEAR or DISAPPEAR in MIS. (B) Y and AU rats showed a similar trend of a decreasing proportion of Remap cells from proximal to distal CA3, with an increasing proportion of Rotate cells from proximal to distal CA3. In contrast, AI rats showed an opposite trend. (C) Logistic regression model showing the probability that cells along the proximal-distal axis were classified as “Rotate” cells. The solid lines show the model’s best fits, and the shaded regions indicate the 95% confidence intervals. Complementary to the proportion data in (B), in Y and AU rats, the probability of being a “Rotate” cell increases from proximal to distal CA3. In contrast, in AI rats, the probability of being a “Rotate” cell decreases from proximal to distal CA3. See also Table S1.

Figure 3.. Correlated representations between the STD and MIS sessions differ in age groups along the transverse axis.

(A) STD1 x STD2 matrices (columns 1, 3, 5) and STD1 x MIS matrices (columns 2, 4, 6) in each CA3 subregion for all groups. (B) The correlation differences along the transverse axis organized according to each animal. Each dot represents a tetrode recorded in that region along the axis. There are not enough data points to run a valid chi-squared test on these numbers, but the trends appear to indicate, on a per-animal basis, a shift from decreasing pattern separation along the transverse axis (from proximal to distal) in Y rats to increasing pattern separation along the axis in AI rats. (C) A linear mixed effects model was used to compare the correlation differences along the transverse axis as a continuous variable. The solid lines show the model’s best cubic-splines fits, and the shaded regions indicate the 95% confidence intervals. There were differences in the shapes of the fitted curves between Y and AI groups but not between Y and AU or AU and AI groups. See also Figure S2, S3, S4, S5 and Table S1.

Figure 4.. Representative rate maps for Y, AU and AI rats showing different degrees of remapping in the two-shape experiment.

Rate maps of two example cells from each age group in each CA3 subregion. Example cells in Y rats showed remapping between the two shapes in proximal and intermediate CA3 but fired in both shapes, with similar place fields, in distal CA3. Example cells in AU rats showed remapping in proximal CA3, but fired in both shapes, with similar place fields, in intermediate and distal CA3. Example cells in AI rats fired in both shapes, with similar place fields, in all CA3 subregions. These representative cells have spatial correlation values between the different shapes that are within the second quartile or the third quartile from the population distribution. Values indicate peak rate in Hz.

Figure 5.. Representations for the different shape environments are less distinguishable in AI rats compared to Y and AU rats.

(A) Illustration showing the PV correlation analysis (top). The rate maps of all CA3 cells were stacked, and the firing rates along the z axis represent the PV for each x-y bin that was shared between the circle and the square. Correlations between the PVs were computed between the same shapes (C-C or S-S) and the different shapes (C-S). (B) Cumulative distribution plots for PV correlations between the same shape (solid lines) and the different shape (dashed lines) in Y (top row), AU (middle row), and AI rats (bottom row). PV correlation of 0 indicates strong remapping and PV correlation of 1 indicates completely correlated firing patterns between the two environments. (C) Observed PV correlation differences along the transverse axis organized according to each animal. Each dot represents a tetrode recorded at that location along the axis. (D) A linear mixed effects model showing the PV correlation differences along the transverse axis as a continuous variable. The solid lines show the model’s best cubic-spline fits, and the shaded regions indicate the 95% confidence intervals. There were differences in the shape of the fitted curves between Y and AI groups but not between Y and AU or between AU and AI groups. See also Figure S6 and Table S2.

Figure 6.. CA3 place cells in all age groups remap between the two rooms.

(A) Rate maps of two example cells from each animal group in each CA3 subregion. Cells show remapping between the two rooms in all CA3 subregions in all age groups. Values indicate peak rate in Hz. (B) Cumulative distribution plots for PV correlation between Room A and Room B in each CA3 subregion. (C) A linear mixed effects model showing the PV correlation differences along the transverse axis as a continuous variable. The solid lines show the model’s best cubic-spline fits, and the shaded regions indicate the 95% confidence intervals. There were no differences in the shape of the fitted curves among the age groups. See also Table S2.

Figure 7.. Hypothesized model of how the attractor dynamics of CA3 is affected by aging.

(A) In proximal CA3 (pCA3, left), the EC neural representations of similar experiences (shown as distance between two input arrows along a “representational similarity” axis) will be pattern separated in the DG (indicated by the larger distance between the DG output to CA3 than the distance between the two EC inputs shown in thick, black solid lines). Proximal CA3, which receives stronger inputs from the DG (both upper and lower blades) coupled with minimal EC inputs, imposes the separated patterns on the CA3 attractor network. Through learning, the recurrent collaterals of pCA3 increase the strength of the attractor basins, resulting in pattern separation in pCA3 for Y and AU rats. In contrast, for AI rats, dysfunction of the EC inputs and the local inhibitory circuitry of the DG hilus are hypothesized to reduce the ability of the DG to separate the similar EC input patterns (indicated by the close distance between the DG outputs to CA3 shown in black, broken lines). The hyperactivity of pCA3 cells in AI rats may further increase the relative strength of the pCA3 to override the DG inputs and cause a single basin of attraction, resulting in pattern completion in pCA3. In distal CA3 (dCA3, right), there are weaker DG inputs (black solid lines) and stronger EC inputs (gray lines) compared to pCA3. The combined DG and EC inputs may impose initial patterns on dCA3 that are somewhat closer together and overlapping than those imposed in pCA3, and the stronger recurrent collateral system of dCA3 may merge the two attractor basins for a broader and deeper basin, resulting in pattern completion for Y and AU rats. In AI rats, weaker DG inputs (black, broken lines) and the possible hypoactivity of dCA3 cells may result in weaker attractor basins in dCA3 and prevent the merging of the attractor basins, resulting in two attractor states with relatively low energy barriers between them. (modified from Lee et al.) (B) Parallel processing streams within the hippocampus. Allocentric contextual information (dark orange) from MEC projects to distal CA1 (dCA1) and egocentric content information (yellow) from LEC projects to proximal CA1 (pCA1). Both MEC and LEC directly project to the DG as well as to CA3, with stronger projection to dCA3. The DG projects to CA3, with stronger projection to pCA3. The DG and pCA3, involved in pattern separation, are marked in light purple, and dCA3, with its strong recurrent circuitry, involved in pattern completion is marked in dark purple. Pattern-separated outputs from pCA3 preferentially project to dCA1, while pattern-completed outputs from dCA3 preferentially project to pCA1.