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Enhanced hippocampal theta rhythmicity and emergence of eta oscillation in virtual reality

Abstract

Hippocampal theta rhythm is a therapeutic target because of its vital role in neuroplasticity, learning and memory. Curiously, theta differs across species. Here we show that theta rhythmicity is greatly amplified when rats run in virtual reality. A novel eta rhythm emerged in the CA1 cell layer, primarily in interneurons. Thus, multisensory experience governs hippocampal rhythms. Virtual reality can be used to boost or control brain rhythms and to alter neural dynamics, wiring and plasticity.

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Fig. 1: Emergence of distinct ~4-Hz eta oscillation during running in VR.
Fig. 2: Theta is weakest and eta is strongest in the CA1 cell layer.
Fig. 3: Enhanced TR and eta and theta modulation of interneurons in VR.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

The software used for data acquisition and analysis are available using the web links provided in the Methods. PyClust is a modified version of http://redishlab.neuroscience.umn.edu/mclust/MClust.html.

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Acknowledgements

We thank P. Ravassard, A. Kees, L. Acharya and A. Hachisuka for providing the experimental data; Z. Aghajan and B. Willers for help with the analyses; and S. Dhingra, K. Choudhary and current and former Mehta lab members for discussions, careful reading of the manuscript and valuable comments. This study was funded by the W. M. Keck Foundation, an AT&T research grant, National Science Foundation grant no. 1550678 and National Institutes of Health grant no. 1U01MH115746, all to M.R.M. The findings were presented at Society for Neuroscience meetings (abstract nos. 263.02 (2016), 523.08 (2017), 508.07 (2018) and 083.03 (2019)).

Author information

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Authors

Contributions

K.S. and M.R.M. designed the study. M.R.M. advised on all aspects of the analysis and experiments. K.S. analyzed the data and generated the figures. K.S. and M.R.M. wrote the paper.

Corresponding authors

Correspondence to Karen Safaryan or Mayank R. Mehta.

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The authors declare no competing interests.

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Peer review information Nature Neuroscience thanks the anonymous reviewers 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

Extended Data Fig. 1 Additional examples of ~4 Hz eta oscillation during running in VR, but not in RW.

The data were recorded from rat #1 and rat #2. Similar format as Fig. 1. a-b, h-i, Traces of LFP, raw (grey), filtered in theta (6–10 Hz, cyan) and eta (2.5–5.5 Hz, magenta) bands during high-speed (above 15 cm/s) running on track (top, i) and at low-speeds (below 15 cm/s) (bottom, ii) recorded on the same tetrodes in the same day RW (a, h) and VR (b, i). c, j, Amplitude envelope distribution during high- (30–60 cm/s) and low- (5–15 cm/s) speed runs for the theta (left panel) and eta (right panel) bands in RW. Theta amplitude was significantly (rat #1, p < 10−10, X2 = 822.14; rat #2, p < 10−10, X2 = 218.0, KW test) larger at high speeds than low speeds, whereas eta amplitude was slightly smaller at high speeds (rat #1, p = 10−10, X2 = 49.5; rat #2, p < 10−10, X2 = 359.5, KW test). d, k, Similar to c, but for VR showing large and significant increase in both eta (rat #1, p < 10−10, X2 = 7942.7; rat #2, p < 10−10, X2 = 279.76, KW test) and theta (rat #1, p < 10−10, X2 = 5542.9; rat #2, p < 10−10, X2 = 259.14, KW test) amplitudes at higher speeds. e, f, l, m, Power spectra of the example LFPs in RW (blue) and VR (red) during running (e, l) and immobility (f, m). g, n, Power index, during run compared to stop, showing prominent peaks in both eta and theta bands in VR (red) and only in theta band in RW (blue). (*** p < 10−10).

Extended Data Fig. 2 Additional examples of ~4 Hz eta oscillation during running in VR.

The data were recorded from rat #5, rat #6 and rat #7. Similar format as Fig. 1. a, b, Left, Traces of LFP, raw (grey), filtered in theta (6–10 Hz, green) and eta (2.5–5.5 Hz, brown) bands during high-speed (above 15 cm/s) running on track (top) and at low-speeds (below 15 cm/s) (bottom) recorded in the VR. Middle, (bottom panel) Power spectra of the example LFPs in VR during running (red) and immobility (black), and (top panel) power index, during run compared to stop, showing prominent peaks in both eta and theta bands in VR (red). Right, Amplitude envelope distribution during high- (30–60 cm/s) and low- (5–15 cm/s) speed runs for the theta (top panel) and eta (bottom panel) bands in VR. Theta amplitude was significantly (rat #5, p < 10−10, X2 = 1430.5; rat #6, p < 10−10, X2 = 4357.1; rat #7, p < 10−10, X2 = 2661.0, KW test) larger at high speeds than low speeds, whereas eta amplitude was slightly smaller at high speeds (rat #5, p < 10−10, X2 = 3434.0; rat #6, p < 10−10, X2 = 12250.0; rat #7, p < 10−10, X2 = 1997.3, KW test).

Extended Data Fig. 3 Differential effect of speed on eta amplitude and theta frequency in RW and VR.

a, Running speed of the rat (top, black) and the corresponding LFP (same format as in Fig. 1a) in VR. Both theta and eta amplitudes increase with speed. b, Same tetrode measured in RW on the same day showing speed-dependent increase in theta, but not eta, amplitude. c,d, Individual LFP eta-cycle amplitude and corresponding speed in VR (c) and RW (d) for the entire session in a and b. The broken axis separates two speed ranges – below (outlined) and above 10 cm/s. Each small dot indicates one measurement. The square dots show mean and s.e.m. in each bin in RW (blue) and VR (red). A log speed scale was used for the speed range below 10 cm/s. Linear regression fits are shown separately for both speed ranges (black lines). e, Population averaged theta amplitude, showing strong increase with running speed in RW. Population averaged theta amplitude in VR first decreased at low speeds (0 vs 10 cm/s) and then increased comparable to RW (Supplementary Table 1). f, Same as 3e, but for theta frequency showed significant increase with running speed in RW, but in VR the frequency dropped at very low speeds (0 vs 10 cm/s), and then became speed-independent. g, Same as 3e, but for eta amplitude, showing decrease in eta amplitude with increasing running speed for RW, but sharp drop in eta amplitude at low speeds (0 vs 10 cm/s), and steady increase in amplitude at higher speeds in VR. h, Same as 3e, but for eta frequency, showing no clear dependence of eta frequency on running speed in both RW and VR. i, Individual eta-cycle amplitudes are positively correlated with speed above 10 cm/s across tetrodes in VR (0.09 ± 0.001, p < 10−10), but not in RW (−0.107 ± 0.005, p < 10−10). 7.5% and 43.1% of all tetrode showed significant increase in eta amplitude with running speed in RW and VR, respectively (p < 0.05). j, Individual eta-cycle amplitudes are negatively correlated with speed below 10 cm/s across tetrodes in VR (−0.095 ± 0.003, p < 10−10), but not in RW (0.002 ± 0.003, p = 0.1). Shaded areas and error bars denote s.e.m.

Extended Data Fig. 4 Running speed in the linear track in RW and VR.

a, Running speed (means ± SD) of the rats as a function of position on a 2.2-m-long linear track for RW (blue) and VR (red). Although the rats were faster in RW, their behavior was similar, reliably reducing speed before reaching the end of the track (n = 49 sessions in RW, n = 121 sessions in VR). b, Average speeds in RW (69.42 ± 0.27) were significantly greater (p < 10−10, χ2 = 2502.3, KW test) than in VR (47.00 ± 0.15). c, CV of running speeds in RW (0.59 ± 0.0023) were significantly greater (p < 10−10, χ2 = 2933.6, KW test) than in VR (0.35 ± 0.0012). d, Average speeds in RW (147.13 ± 0.02) were significantly greater (p < 10−10, χ2 = 2872.7, KW test) than in VR (81.48 ± 0.0046). Shaded areas in a denote s.e.m.

Extended Data Fig. 5 Eta-theta phase-phase coupling but not eta-theta amplitude- amplitude coupling is far greater in VR than in RW during running.

a, Example traces showing co-existence of eta and theta. Traces of LFP, raw (grey), filtered in theta (6–10 Hz, green) and eta (2.5–5.5 Hz, brown) bands are shown during high-speed (above 15 cm/s) running on track. b, Distributions of the eta-theta amplitude envelope correlation (AEC) during running (>5 cm/s, 0.27 ± 0.0019) and stops at goal location (0.16 ± 0.0017) in RW were significantly different (p < 10−10, X2 = 2178.2, KW test). Shaded area indicates significant correlations. c, Same as in b, but in VR. Distributions of theta-to-eta amplitude envelope correlation (AEC) during runs in track (>5 cm/s, 0.18 ± 0.0013) and stops at goal location (−0.02 ± 0.0011) in VR were significantly different (p < 10−10, X2 = 2499.4, KW test). d, Phase locking values (PLV) were computed as the mean vector length of the differences between instantaneous LFP theta and eta phases (See methods). The distribution of the LFP eta-to-theta PLV across the tetrodes was significantly smaller (p < 10−10, X2 = 331.56, KW test) in RW (0.039 ± 0.0006) than in VR (0.063 ± 0.0017). e, Distributions of eta-to-theta phase differences in RW (blue) and VR (red) for tetrodes with significant PLV. f, Eta-to-theta PLV for the same tetrodes in RW versus in VR recorded in the same day sessions, showed that 72% of tetrodes had greater eta-theta PLV in VR than RW. g, h, Relationship between SPW amplitude and polarity and (g) eta-to-theta amplitude envelope correlation (AEC) (for positive SPW n = 279, r = −0.05, p = 0.397, for negative SPW, n = 617, r = 0.155, p < 10−5), and (h) phase locking value (PLV) (for positive SPW n = 279, r = 0.18, p = 0.005, for negative SPW, n = 617, r = −0.3128, p < 10−10) in VR. Eta-theta phase-phase coupling is larger for tetrodes with larger magnitude SPW, for both +ve and –ve polarity SPW. The picture is reversed for the AEC. Number indicates max value. i, Scatter plot between eta-to-theta AEC and PLV in VR (r = −0.343, p < 10–10).

Extended Data Fig. 6 Prominent eta band peak appears only during running in VR on tetrodes with small SPW, independent of the planer position of the electrodes.

LFP power spectra for simultaneously recorded tetrodes are shown during running (red) and immobility (grey) in VR. Power spectra of the same tetrodes during running in RW are also shown (blue). Average z-scored sharp-waves computed from the baseline session preceding the VR session are shown for each tetrode (grey inset). Tetrode numbers are shown at left bottom corner of the power spectra. Center: Pictures of the bilateral cannulae with tetrode numbers (red). These are not sequential here because the numbers are determined by their sequential position in the electrode interface board.

Extended Data Fig. 7 Model fit of autocorrelograms of interneurons in RW and VR.

(a, b) Examples of interneurons’ autocorrelograms (grey) with TR1 values are shown along with fits using GMM in RW (a, top two rows, left, blue) and in VR (b, bottom two rows, left, red). The distribution of spikes’ theta (middle column) and eta (right column) phases are given. (c) Histograms of ACG rhythmicity decay in RW (blue, n = 36, 0.64 ± 0.04) and VR (red, n = 157, 1.4 ± 0.04) are significantly different (p < 10−10, χ² = 81.37). (d) Histograms of ACG decay constant in RW (blue, 8.4 ± 0.39) and VR (red, 9.8 ± 0.07) are shown (p < 10−5, χ² = 19.65). (e) Histograms of ACG theta period in RW (0.12 ± 0.015) and VR (0.138 ± 0.02) are significantly different (p < 10−10, χ² = 82.63). (f) Histograms of ACG peak widths in RW (0.65 ± 0.002) and VR (0.54 ± 0.0012) are significantly different (p = 1.1*10−7, χ² = 23.71). (g, h) Heat map of ACGs of spike trains sorted by increasing TR1 for putative interneurons recorded during running in RW (g) and VR (h). The ACGs are normalized by their first theta peak values. (i) The population average of autocorrelations shows greater theta rhythmicity in VR than in RW. (j) The histograms of the TR1 distributions show significant difference between RW (median = −0.09) and VR (median = −0.07) (p < 10−10, χ² = 57.02).

Extended Data Fig. 8 Theta rhythmicity index of the putative pyramidal cells and interneurons in RW and VR.

a-f Data from putative pyramidal cells. a, TR1 distributions in VR (−0.1 ± 0.0075, n = 355) is much greater (p < 10−10, χ2 = 72.83) than RW (−0.17 ± 0.014, n = 268) and. b, Difference of third-to-second peak of theta (TR2) in VR (−0.21 ± 0.007, n = 153) is much greater (p < 10−10, χ2 = 51.83) than RW (−0.32 ± 0.0081, n = 186). c, Difference of fourth-to-third theta peak (TR3) in VR (−0.21 ± 0.008, n = 201) is much greater (p < 10−9, χ2 = 33.58) than in RW (−0.36 ± 0.013, n = 114) and. d, Same as a, but model corrected ACG estimates show TR1 in VR (−0.14 ± 0.0091, n = 357) is much greater (p < 10−10, χ2 = 54.44) than in RW (−0.21 ± 0.014, n = 274) and. e, Difference of third-to-second peak (TR2) difference index (p = 2.5188e-05, χ2 = 17.75) between RW (−0.32 ± 0.0153, n = 252) and VR (−0.276 ± 0.009, n = 155). f, Difference of fourth-to-third peak (TR3) difference index (p = 0.002, χ2 = 9.58) between RW (−0.35 ± 0.014, n = 142) and VR (−0.27 ± 0.009, n = 76). g-l Similar to a-d but for interneurons. g, Significant difference of TR1 distributions (p < 10−10, χ2 = 47.56) cells between RW (−0.09 ± 0.004, n = 33) and VR (−0.05 ± 0.0033, n = 149). h, Difference of third-to-second peak (TR2) difference index (p = 0.49, χ2 = 0.47) between RW (−0.0767 ± 0.0031, n = 33) and VR (−0.078 ± 0.0035, n = 149). i, Difference of fourth-to-third peak (TR3) difference index (p = 0.13, χ2 = 2.18) between RW (−0.066 ± 0.006, n = 33) and VR (−0.05 ± 0.007, n = 148). j, Significant difference of TR1 distributions (p = 4.8071e-12, χ2 = 47.76) of putative pyramidal cells between RW (−0.215 ± 0.0097, n = 33) and VR (−0.116 ± 0.0048, n = 149). k, Difference of third-to-second peak (TR2) difference index (p < 10−5, χ2 = 16.29) between RW (−0.21 ± 0.0075, n = 33) and VR (−0.153 ± 0.0098, n = 149). l, Difference of fourth-to-third peak (TR3) difference index (p = 2.3933e-06, χ2 = 22.25) between RW (−0.21 ± 0.0187, n = 23) and VR (−0.115 ± 0.0076, n = 130). (***, P < 0.001).

Extended Data Fig. 9 Relationship between theta rhythmicity and theta and eta phase locking of place cells and interneurons in RW and VR.

(a, b) We quantified the relationship between TR1 and eta (r = −0.1, p = 0.28, partial Pearson correlation with number of spikes as controlling variable) and theta (r = 0.0032, p = 0.95) phase locking of place cells in RW. (c, d) The place cells with higher TR1 showed increasingly more eta (r = 0.22, p < 10−5), but not theta (r = 0.06, p = 0.2), phase locking in VR. (e, f) No systematic relationship was found between TR1 and (e) eta (r = −0.1, p = 0.28) or (f) theta (r = −0.15, p = 0.41) phase locking in RW for interneurons. (g, h) Instead, interneurons with higher TR1 showed increasingly more (g) eta (r = 0.19, p = 0.02) and (h) theta (r = 0.22, p = 0.01) phase locking in VR.

Supplementary information

Supplementary Information

Supplementary Figs. 1–9.

Reporting Summary

Supplementary Table 1

Population-averaged theta and eta amplitudes and frequencies are shown (mean ± s.e.m.) and are given in RW (blue, n = 991) and VR (red, n = 1,637) at 0, 10 and 50 cm s−1. Statistical significance provided using the non-parametric Kruskal–Wallis test.

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Safaryan, K., Mehta, M.R. Enhanced hippocampal theta rhythmicity and emergence of eta oscillation in virtual reality. Nat Neurosci 24, 1065–1070 (2021). https://doi.org/10.1038/s41593-021-00871-z

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