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Mapping of a non-spatial dimension by the hippocampal–entorhinal circuit

Abstract

During spatial navigation, neural activity in the hippocampus and the medial entorhinal cortex (MEC) is correlated to navigational variables such as location1,2, head direction3, speed4, and proximity to boundaries5. These activity patterns are thought to provide a map-like representation of physical space. However, the hippocampal–entorhinal circuit is involved not only in spatial navigation, but also in a variety of memory-guided behaviours6. The relationship between this general function and the specialized spatial activity patterns is unclear. A conceptual framework reconciling these views is that spatial representation is just one example of a more general mechanism for encoding continuous, task-relevant variables7,8,9,10. Here we tested this idea by recording from hippocampal and entorhinal neurons during a task that required rats to use a joystick to manipulate sound along a continuous frequency axis. We found neural representation of the entire behavioural task, including activity that formed discrete firing fields at particular sound frequencies. Neurons involved in this representation overlapped with the known spatial cell types in the circuit, such as place cells and grid cells. These results suggest that common circuit mechanisms in the hippocampal–entorhinal system are used to represent diverse behavioural tasks, possibly supporting cognitive processes beyond spatial navigation.

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Figure 1: Sound modulation task.
Figure 2: CA1 and MEC activity in the SMT.
Figure 3: Activity depends on behavioural context.
Figure 4: SMT-modulated and spatially modulated cells overlap.

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Acknowledgements

We thank A. Akrami, C. Constantinople, C. Domnisoru, J. Gauthier, A. Miri, K. Rajan, D. Rich, and B. Scott for suggestions, as well as S. Lowe for assistance with machining. The illustrations in Fig. 1a are by J. Kuhl. This work was supported by the Simons Foundation, NIH Grant 1K99NS093071 (D.A.) and the US Federal Work-Study program (R.N.).

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Authors

Contributions

D.A. and. D.W.T designed the experiments. D.A. and R.N. performed the experiments and analysed the data. D.A., R.N. and D.W.T. wrote the paper.

Corresponding authors

Correspondence to Dmitriy Aronov or David W. Tank.

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The authors declare no competing financial interests.

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Reviewer Information Nature thanks E. Buffalo, M. Mehta and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Figure 1 Behavioural model.

a, Model that tests whether joystick releases depended on sound frequency, the amount of elapsed time, or a combination of the two. Joystick release times are predicted at a fixed time lag (Δt) relative to the occurrence of a fixed sound frequency (f0). Schematic shows three trials that have different speeds of frequency traversal. Frequency f0 occurs at different times relative to the press of the joystick across these trials. However, the time lag is constant. b, Model fits of the frequency component f0 across all 189 behavioural sessions in nine rats. Red marks, median values for each of the rats. This frequency component accounted for most of the trial; indicated number is the median ± s.e.m. across rats. c, Model fits of the time lag component Δt across all behavioural sessions. This time lag component accounted for a small fraction of the trial; the lag might be largely explained by the expected reaction time (for example, 100–200 ms in pure-tone auditory discrimination tasks39) and the mechanics of the joystick (300–400 ms). In other words, the behaviour was consistent with the rats responding to a frequency of ~13.5 kHz (just before start of the target zone at 15 kHz), resulting in a detectable release of the joystick ~750 ms later.

Extended Data Figure 2 Histological verification of tetrode positions.

a, Representative fluorescent Nissl-stained parasagittal sections of MEC from one animal, ordered from the lateral-most to the medial-most section; the approximate mediolateral position of each section is indicated. Arrows indicate tetrode tip locations. Five of the shown tetrodes (with the exception of 3) had parts of their tracks in layers 2 and/or 3. Task-modulated cells in the SMT and grid cells during random foraging were found on all of these tetrodes. b, Representative parasagittal section of the hippocampus, showing two tetrodes in the CA1 pyramidal cell layer. Task-modulated cells during the passive playback + reward task were found on both of these tetrodes.

Extended Data Figure 3 Stability of firing.

a, Activity of a CA1 place cell on interleaved SMT and random foraging sessions. Data are plotted as in Fig. 4. Sessions immediately followed one another. Sessions 1 and 3 were 30 min long each, while sessions 2 and 4 were 15 min long each. b, Activity of an MEC grid cell, plotted as in a. Sessions 1 and 3 were 1 h long each, while sessions 2 and 4 were 20 min long each. Sessions 2 and 4 immediately followed sessions 1 and 3, respectively. The starts of sessions 1 and 3 were separated by 24 h. c, Summary of stability across all 882 SMT-modulated CA1 cells. For each cell, the Pearson correlation was measured between the PSTHs from the first halves of the SMT sessions and those from the second halves of the sessions. Orange, distribution of correlation values across cells. Grey, distribution of correlation values computed after shuffling spike times, averaged across 100 shuffles. d, Summary of the data from 597 MEC cells, plotted as in c. In CA1 and MEC, 95.7% and 97.2% of the cells had higher correlation values than in the shuffled data, respectively (P < 0.01).

Extended Data Figure 4 Analysis of theta modulation.

a, Examples of power spectral density (PSD) plots from two CA1 cells, showing a prominent theta oscillation. Black trace, median across trials. Shaded area shows estimated s.e.m. across trials. The position of the peak in the median PSD is indicated. b, Distribution of theta frequencies across all 56,496 trials in five rats with CA1 recordings. Red marks show median values for each of the rats. c, Phases of theta at which spikes were fired by the same neurons as in a, showing theta phase precession. Black dots, individual spikes plotted in time (linearly warped between the press and the release of the joystick) and theta phase. Each spike is plotted twice with a 2π phase offset. Red line, linear regression fit to the data. d, Slopes of the regression fits quantified in c for all 138 CA1 cells that had a significant correlation (P < 0.01) between theta phase and warped time. Negative slope indicates forward phase precession, as is typically observed during spatial navigation. e, Frequency of theta oscillations (mean ± s.e.m. across rats) quantified across trials that had different average ‘speeds’ of sound frequency traversal in the SMT. Red line shows linear regression fit; the slope of the fit was not significantly different from 0 (P = 0.70). Unlike in spatial navigation, theta frequency did not correlate to speed; this may imply that the relationship between theta and speed during navigation is dependent on locomotion-related signals.

Extended Data Figure 5 Statistics of firing fields in the SMT.

a, Number of firing fields per cell for all 2,208 CA1 cells. Error bars, 95% multinomial confidence intervals. The count includes fields before joystick press and after joystick release. However, MEC cells did occasionally have more than one field even during sound presentation (for example, cell 5 in Fig. 4b). b, Distribution of all 1,252 CA1 firing fields throughout the SMT. Each field is assigned a time according to the time of occurrence of its maximum firing rate. Time is linearly warped between the press and the release of the joystick. c, Field width as a function of field time within the task. Fields were sorted by their time in the task, and a rolling window of 100 fields was applied. The average field time within the task and the average field width were measured in this window (black trace). Blue band shows s.e.m. of field width within the rolling window. d, Field height (peak firing rate) as a function of field time within the task. Data are plotted as in c. Fields were concentrated near the press and the release of the joystick and were narrower during these times. eh, Statistics in MEC for 943 fields in 1,164 cells, plotted as in ad. MEC tended to have more fields per cell than CA1, but otherwise had similar statistics. A tightening of firing fields in the vicinity of joystick presses and releases may be due to a higher density of available sensory cues during these events. Alternatively, field tightening may result from the stronger salience of these events compared to the rest of the task.

Extended Data Figure 6 CA1 and MEC cells form sequences of activity along the sound frequency axis.

a, Firing rates of all 183 CA1 cells with at least one firing field in the SMT that was confined to the sound presentation period (between the press and the release of the joystick). Each row corresponds to one cell and is normalized by the maximum firing rate during the sound presentation period. Rows are sorted according to the frequency at which the maximum firing rate occurred. Each trial was binned into 150 frequency bins, which could vary in duration both within a trial and across trials. The firing rate was calculated separately in each bin using that bin’s duration, and the firing rates were averaged across trials and smoothed with a 3-point square window. Note that fields in the SMT did not progressively broaden during the delay period, as they typically do in time cells; this may be due to the fact that an informative sensory variable (sound frequency) was always available to the animal, preventing a drift in the neural code. b, Firing rates of 141 MEC cells, calculated and plotted as in a. c, Distribution of CA1 firing field widths, only for those 122 cells that were identified as ‘frequency-aligned’ by the electrophysiology model (Extended Data Fig. 8). Note that the entire trial was on average 3.1 octaves. d, Distribution of 109 MEC firing field widths, plotted as in c. Note that the longer tail compared to the CA1 data is partially due to grid cells from modules with wide spacing (Fig. 4e).

Extended Data Figure 7 Model for characterizing the alignment of neural activity to different task events in the SMT.

Grey traces, PSTHs across trials, sorted by duration into five groups. The same traces are overlaid below (black or red). For each cell, the six subplots are for different values of the three parameters (αpress, αrelease, αfrequency) indicated in the corner of each subplot). For each subplot, PSTHs are plotted as a function of β, defined as where is the normalized time relative to the press of the joystick, is the normalized time relative to the release of the joystick, and is the normalized sound frequency (see Supplementary Methods for details). For each cell, the subplot with the strongest alignment of PSTHs across trials is emphasized by red traces.

Extended Data Figure 8 Activity aligns to different task features in the SMT.

a, Traces are PSTHs across trials, sorted by duration into five groups. Each PSTH is normalized to its maximum. Red dots, 30% of maximum. Black lines, values of joystick press-aligned time tpress (cell 1), joystick release-aligned time trelease (cell 2) or sound frequency f (cell 3) that best fit the red symbols. These fits are for illustration purposes; the actual model maximized the cross-correlation of PSTHs by aligning them to a linear combination of tpress, trelease, and f. Cells shown are the same as in Extended Data Fig. 7. b, Fits of the model to all firing fields produced by CA1 neurons. Axes are coefficients indicating the relative contributions of tpress, trelease, and f to the optimal alignment of PSTHs. Numbered points are example cells shown in a. c, Contour plot of the density of points in b, illustrating three clusters. d, Distribution of fields belonging to each of the three clusters in c throughout the task. Time is linearly warped between the press and the release of the joystick. Error bars, 95% multinomial confidence intervals. Across all 411 fields from 341 recorded CA1 neurons with a peak of a firing field occurring during the sound presentation period, press-aligned, release-aligned, and frequency-aligned fields accounted for 26%, 23% and 51% of the population, respectively. eg, Same plots as in bd, but for 213 firing fields produced by 186 MEC neurons. In MEC, there was a larger fraction of frequency-aligned fields (17%, 20% and 63% for the three types; P < 0.01, χ2 test for comparison to CA1). The three clusters in c and f were not perfectly separated; in fact, some firing fields had significantly non-zero regression coefficients for more than one task parameter: 14% in CA1 and 21% in MEC (P < 0.01, bootstrap analysis).

Extended Data Figure 9 Activity of CA1 neurons in the passive playback + reward experiment.

a, Four examples of neurons in the PPR task, plotted as in Fig. 3. Firing fields spanned the entire behavioural task, but were wider than in the SMT, except possibly near the reward (for example, cell 4). b, Activity of all 44 cells whose firing rates were significantly modulated in the PPR task, plotted as in Fig. 2. Of the 21 cells that had firing fields during sound presentation, the fields of 14 were better aligned to sound frequency than to other task parameters.

Extended Data Figure 10 Overlap between spatial cell types and the SMT-modulated population.

a, Activity of spatial cell types that were also SMT-modulated. All plots are as in Fig. 2. be, Head direction cells overlap with SMT-modulated neurons, but head direction selectivity does not fully account for firing rate modulations in the SMT. This analysis was performed to account for the possibility that some SMT firing was due to subtle changes in head direction during the nosepoke or between the nosepoke and the lick-tube. b, Activity of all head direction cells that were also modulated in the SMT. c, Activity of all non-head direction cells that were also modulated in the SMT. d, Activity of three MEC cells in one rat. Cells 1 and 2 were simultaneously recorded. Left, activity in the SMT, plotted as in Fig. 3. Right, firing rate as a function of head direction during random foraging, plotted in polar coordinates. Each firing rate is scaled to its indicated maximum. Arrow, vector average of the head direction tuning curve. All three cells have a firing field at the release of the joystick. However, although cells 1 and 2 have similar head direction selectivity, cell 3 is not a head direction cell, suggesting that the firing field cannot be explained by head direction selectivity. e, Activity of two simultaneously recorded MEC cells, plotted as in d. Although the cells have similar head direction selectivity, they have highly dissimilar firing during the SMT. The total number of cells recorded in both tasks was 918 in CA1 and 881 in MEC, including 290 and 379 SMT-modulated cells, respectively. In CA1, there were 295 place cells, and in MEC there were 105 grid cells, 68 border cells, and 321 head direction cells. Overlaps of these cell types with SMT-modulated cells contained 74, 36, 42, and 163 cells, producing 104, 69, 78, and 295 firing fields, respectively.

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Aronov, D., Nevers, R. & Tank, D. Mapping of a non-spatial dimension by the hippocampal–entorhinal circuit. Nature 543, 719–722 (2017). https://doi.org/10.1038/nature21692

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