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Silencing CA3 disrupts temporal coding in the CA1 ensemble

Abstract

In addition to the place-cell rate code, hippocampal area CA1 employs a temporal code, both on the single-cell and ensemble level, to accurately represent space. Although there is clear evidence that this precise spike timing is organized by theta and gamma oscillations that are present in hippocampus, the circuit mechanisms underlying these temporal codes remain poorly understood. We found that the loss of CA3 input abolished temporal coding at the ensemble level in CA1 despite the persistence of both rate and temporal coding in individual neurons. Moreover, low gamma oscillations were present in CA1 despite the absence of CA3 input, but spikes associated with these periods carried significantly reduced spatial information. Our findings dissociate temporal coding at the single-cell (phase precession) and population (theta sequences) levels and suggest that CA3 input is crucial for temporal coordination of the CA1 ensemble code for space.

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Figure 1: LG oscillations persist in the absence of CA3 input to CA1.
Figure 2: Information coding during HG and LG periods.
Figure 3: Theta-related firing of CA1 principal cells.
Figure 4: Temporal coding at the ensemble level requires CA3 to CA1 input.

References

  1. 1

    Moser, E.I. et al. Grid cells and cortical representation. Nat. Rev. Neurosci. 15, 466–481 (2014).

    CAS  Google Scholar 

  2. 2

    Colgin, L.L. et al. Frequency of gamma oscillations routes flow of information in the hippocampus. Nature 462, 353–357 (2009).

    CAS  Google Scholar 

  3. 3

    Schomburg, E.W. et al. Theta phase segregation of input-specific gamma patterns in entorhinal-hippocampal networks. Neuron 84, 470–485 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4

    O'Keefe, J. & Dostrovsky, J. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res. 34, 171–175 (1971).

    CAS  Article  Google Scholar 

  5. 5

    O'Keefe, J. & Recce, M.L. Phase relationship between hippocampal place units and the EEG theta rhythm. Hippocampus 3, 317–330 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6

    Dragoi, G. & Buzsáki, G. Temporal encoding of place sequences by hippocampal cell assemblies. Neuron 50, 145–157 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7

    Feng, T., Silva, D. & Foster, D.J. Dissociation between the experience-dependent development of hippocampal theta sequences and single-trial phase precession. J. Neurosci. 35, 4890–4902 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8

    Foster, D.J. & Wilson, M.A. Hippocampal theta sequences. Hippocampus 17, 1093–1099 (2007).

    PubMed  PubMed Central  Google Scholar 

  9. 9

    Skaggs, W.E., McNaughton, B.L., Wilson, M.A. & Barnes, C.A. Theta phase precession in hippocampal neuronal populations and the compression of temporal sequences. Hippocampus 6, 149–172 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10

    Wang, Y., Romani, S., Lustig, B., Leonardo, A. & Pastalkova, E. Theta sequences are essential for internally generated hippocampal firing fields. Nat. Neurosci. 18, 282–288 (2015).

    CAS  Google Scholar 

  11. 11

    Schlesiger, M.I. et al. The medial entorhinal cortex is necessary for temporal organization of hippocampal neuronal activity. Nat. Neurosci. 18, 1123–1132 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12

    Nakashiba, T., Buhl, D.L., McHugh, T.J. & Tonegawa, S. Hippocampal CA3 output is crucial for ripple-associated reactivation and consolidation of memory. Neuron 62, 781–787 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13

    Nakashiba, T., Young, J.Z., McHugh, T.J., Buhl, D.L. & Tonegawa, S. Transgenic inhibition of synaptic transmission reveals role of CA3 output in hippocampal learning. Science 319, 1260–1264 (2008).

    CAS  Google Scholar 

  14. 14

    Csicsvari, J., Jamieson, B., Wise, K.D. & Buzsáki, G. Mechanisms of gamma oscillations in the hippocampus of the behaving rat. Neuron 37, 311–322 (2003).

    CAS  Google Scholar 

  15. 15

    Mizuseki, K., Sirota, A., Pastalkova, E. & Buzsáki, G. Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop. Neuron 64, 267–280 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16

    Buzsáki, G., Leung, L.W. & Vanderwolf, C.H. Cellular bases of hippocampal EEG in the behaving rat. Brain Res. 287, 139–171 (1983).

    Google Scholar 

  17. 17

    Vinck, M., Oostenveld, R., van Wingerden, M., Battaglia, F. & Pennartz, C.M. An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. Neuroimage 55, 1548–1565 (2011).

    PubMed  PubMed Central  Google Scholar 

  18. 18

    Ahmed, O.J. & Mehta, M.R. Running speed alters the frequency of hippocampal gamma oscillations. J. Neurosci. 32, 7373–7383 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19

    Zheng, C., Bieri, K.W., Trettel, S.G. & Colgin, L.L. The relationship between gamma frequency and running speed differs for slow and fast gamma rhythms in freely behaving rats. Hippocampus 25, 924–938 (2015).

    PubMed  PubMed Central  Google Scholar 

  20. 20

    Gupta, A.S., van der Meer, M.A., Touretzky, D.S. & Redish, A.D. Segmentation of spatial experience by hippocampal θ sequences. Nat. Neurosci. 15, 1032–1039 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21

    Farovik, A., Dupont, L.M. & Eichenbaum, H. Distinct roles for dorsal CA3 and CA1 in memory for sequential nonspatial events. Learn. Mem. 17, 12–17 (2010).

    PubMed  PubMed Central  Google Scholar 

  22. 22

    O'Keefe, J. & Burgess, N. Dual phase and rate coding in hippocampal place cells: theoretical significance and relationship to entorhinal grid cells. Hippocampus 15, 853–866 (2005).

    PubMed  PubMed Central  Google Scholar 

  23. 23

    Kamondi, A., Acsády, L., Wang, X.J. & Buzsáki, G. Theta oscillations in somata and dendrites of hippocampal pyramidal cells in vivo: activity-dependent phase-precession of action potentials. Hippocampus 8, 244–261 (1998).

    CAS  Google Scholar 

  24. 24

    Magee, J.C. Dendritic mechanisms of phase precession in hippocampal CA1 pyramidal neurons. J. Neurophysiol. 86, 528–532 (2001).

    CAS  Google Scholar 

  25. 25

    Chance, F.S. Hippocampal phase precession from dual input components. J. Neurosci. 32, 16693–16703 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26

    Johnson, A. & Redish, A.D. Neural ensembles in CA3 transiently encode paths forward of the animal at a decision point. J. Neurosci. 27, 12176–12189 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27

    Whittington, M.A., Traub, R.D. & Jefferys, J.G. Synchronized oscillations in interneuron networks driven by metabotropic glutamate receptor activation. Nature 373, 612–615 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28

    Lasztóczi, B. & Klausberger, T. Layer-specific GABAergic control of distinct gamma oscillations in the CA1 hippocampus. Neuron 81, 1126–1139 (2014).

    Google Scholar 

  29. 29

    Mann, E.O., Suckling, J.M., Hajos, N., Greenfield, S.A. & Paulsen, O. Perisomatic feedback inhibition underlies cholinergically induced fast network oscillations in the rat hippocampus in vitro. Neuron 45, 105–117 (2005).

    CAS  PubMed  Google Scholar 

  30. 30

    Bibbig, A. et al. Beta rhythms (15-20 Hz) generated by nonreciprocal communication in hippocampus. J. Neurophysiol. 97, 2812–2823 (2007).

    PubMed  Google Scholar 

  31. 31

    Jaramillo, J., Schmidt, R. & Kempter, R. Modeling inheritance of phase precession in the hippocampal formation. J. Neurosci. 34, 7715–7731 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32

    Hafting, T., Fyhn, M., Bonnevie, T., Moser, M.B. & Moser, E.I. Hippocampus-independent phase precession in entorhinal grid cells. Nature 453, 1248–1252 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33

    Climer, J.R., Newman, E.L. & Hasselmo, M.E. Phase coding by grid cells in unconstrained environments: two-dimensional phase precession. Eur. J. Neurosci. 38, 2526–2541 (2013).

    PubMed  PubMed Central  Google Scholar 

  34. 34

    Zheng, C., Bieri, K.W., Hsiao, Y.T. & Colgin, L.L. Spatial sequence coding differs during slow and fast gamma rhythms in the hippocampus. Neuron 89, 398–408 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35

    Knierim, J.J., Neunuebel, J.P. & Deshmukh, S.S. Functional correlates of the lateral and medial entorhinal cortex: objects, path integration and local-global reference frames. Phil. Trans. R. Soc. Lond. B 369, 20130369 (2014).

    Google Scholar 

  36. 36

    Schmitzer-Torbert, N., Jackson, J., Henze, D., Harris, K. & Redish, A.D. Quantitative measures of cluster quality for use in extracellular recordings. Neuroscience 131, 1–11 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37

    McHugh, T.J., Blum, K.I., Tsien, J.Z., Tonegawa, S. & Wilson, M.A. Impaired hippocampal representation of space in CA1-specific NMDAR1 knockout mice. Cell 87, 1339–1349 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38

    Senior, T.J., Huxter, J.R., Allen, K., O'Neill, J. & Csicsvari, J. Gamma oscillatory firing reveals distinct populations of pyramidal cells in the CA1 region of the hippocampus. J. Neurosci. 28, 2274–2286 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39

    Tort, A.B. et al. Dynamic cross-frequency couplings of local field potential oscillations in rat striatum and hippocampus during performance of a T-maze task. Proc. Natl. Acad. Sci. USA 105, 20517–20522 (2008).

    CAS  Google Scholar 

  40. 40

    Buhl, D.L., Harris, K.D., Hormuzdi, S.G., Monyer, H. & Buzsáki, G. Selective impairment of hippocampal gamma oscillations in connexin-36 knock-out mouse in vivo. J. Neurosci. 23, 1013–1018 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41

    Pfeiffer, B.E. & Foster, D.J. Hippocampal place-cell sequences depict future paths to remembered goals. Nature 497, 74–79 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42

    Berens, P. CircStat: A Matlab Toolbox for Circular Statistics. J. Stat. Softw. 31 http://dx.doi.org/10.18637/jss.v031.i10 (2009).

  43. 43

    Kempter, R., Leibold, C., Buzsáki, G., Diba, K. & Schmidt, R. Quantifying circular-linear associations: hippocampal phase precession. J. Neurosci. Methods 207, 113–124 (2012).

    Google Scholar 

  44. 44

    Geisler, C. et al. Temporal delays among place cells determine the frequency of population theta oscillations in the hippocampus. Proc. Natl. Acad. Sci. USA 107, 7957–7962 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    Oostenveld, R., Fries, P., Maris, E. & Schoffelen, J.M. FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell. Neurosci. 2011, 156869 (2011).

    Google Scholar 

Download references

Acknowledgements

We thank all members of the Laboratory for Circuit and Behavioral Physiology for discussions on the manuscript and for their support, the RIKEN Advanced Manufacturing Team for their assistance in microdrive production, and D.J. Foster and T. Feng for providing Matlab code for Bayesian decoding. This work was supported by RIKEN BSI (T.J.M.) and the Japan Society for the Promotion of Science (JSPS) Kakenhi program #26750378 (S.J.M.).

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S.J.M. and T.J.M. conceived the study and designed the experiments. S.J.M. performed the experiments and data analyses. S.J.M. and T.J.M. wrote the manuscript.

Corresponding author

Correspondence to Thomas J McHugh.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Population changes associated with loss of input from CA3 to CA1.

(a) Left panel depicts examples of wideband CA1 LFP (WB) during quiescent periods (black traces), below are band-pass filtered (90-250 Hz) epochs (RI) of the same data. The ripple detection algorithm reliably isolates high frequency oscillations depicted in red. Scale bar represents 100 ms and 300 µV/ (WB) 200 µV/ (RI). Examples of individual ripple-band filtered events (right panel) showing a clear difference in intrinsic frequency between control (dark blue) and mutant subjects (dark red), scale bar represents 20 ms and 500 µV. (b) Group data across genotypes (left) showing a significant reduction in intrinsic ripple frequency (P < 0.05; t-test), time course of ripple frequency transition following removal of doxycycline from the animals diet (middle panel), with no change observed in ripple duration (right) following ablation of CA3 output (P > 0.05; t-test). (c) Spike rate analysis revealed increases in CA3 spike rates were accompanied by corresponding increases in CA1 in CTR animals (left panel), the two sub-regions were correlated to a lesser degree following CA3 silencing. (d) Multiple examples of hippocampal immunofluorescence staining with VAMP2 antibody for control and mutant animals on a Dox free diet for 4 weeks. Each panel represents a single mouse, controls on the left, mutants on the right. (e) Average CA3 pyramidal cell spike probability triggered by peak power during CA1 ripple episodes (time zero).

Supplementary Figure 2 CA3 activity correlates temporally with CA1 low gamma oscillations in control mice.

(a) CA3 cells spike in advance of CA1 pyramidal cells. Spike probabilities across time of CA3 place cells, referenced to CA1 spike times (lined up at 0 ms) within single theta cycles. (b) Highest CA3 spike probability was observed just prior to maximal power of CA1 low gamma events. (c) When restricted to only CA1 low gamma events, CA3 spike probability remained maximal prior to CA1 firing (0 ms).

Supplementary Figure 3 CA1 spectral properties following CA3 silencing.

(a) Examples of CTR (left) and MT (right) wideband (WB) LFPs recorded from CA1 stratum pyramidale, below are the same data filtered in several frequency bands: theta (TH), low (LG) and high gamma (HG). Scale bar represents 125 ms and 300 µV/ (TH & WB) 100 µV/ (LG & HG). (b) Examples of unfiltered LFP recorded from CA1 stratum pyramidale in control (dark blue) and mutant mice (dark red) showing LG occurring predominantly at theta troughs, whilst HG occurs at earlier theta phases. Scale bar represents 100 ms and 300 µV. (c) Group data showing CA3-CA1 coherence between 2-100 Hz (left panel). Mean coherence across the theta (right panel), low gamma and high gamma ranges were not significantly different following CA3 silencing (P > 0.5; t-test), WPLI however was significantly reduced in the low and high gamma bands (P < 0.05; t-test). (d) Group data demonstrating average velocity was comparable across genotypes (P > 0.05; t-test). (e) Z-scored CA1 gamma power plotted as a function of running speed and averaged across mice, demonstrating that faster gamma frequencies are more pronounced at higher velocities.

Supplementary Figure 4 Spatial coding with and without CA3 output.

(a) Examples of place field firing rate maps in control (left, CTR) and mutant (right, MUT) mice, individual color plots are scaled from minimum (dark blue) to peak firing rate (red). Numbers above indicate maximal firing rates in Hertz. (b) Representative cells which were classified as having place fields at the extremities of the track. Note that the width and length of the track were scaled independently for presentation purposes.

Supplementary Figure 5 Spatial coding during low and high gamma periods.

(a) Examples of firing rate maps in control (left, CTR) and mutant (right, MUT) mice, color plots are scaled from minimum (dark blue) to peak firing rate (red) individually for each separate map. For each cell three maps are displayed: constructed from either all spikes (ALL), or from only spikes occurring during low (LG), or high (HG) gamma periods. Note that the width and length of the track were scaled independently for presentation purposes. (b) Mean numbers of spikes used for construction of place field maps (shown in A), does not differ significantly between gamma bands (P > 0.05; Wilcoxon Rank-sum). (c) Average decoding error with the control group sub-sampled to match total cell number across genotypes (P < 0.05; t-test). (d) Average decoding error with the control group sub-sampled to match total spike number across genotypes (P < 0.05; t-test). (e) Examples of partial session decoding from several control (left) and mutant (right) mice. Black lines indicate actual position from video telemetry, indicated in blue are decoded positions during low (LG) and high (HG) gamma epochs for control mice, while mutants are represented in red.

Supplementary Figure 6 Theta sequence detection is reliable even with reduced spatial coding.

(a) Spike probability histograms showing the theta phase of all spikes used for Bayesian decoding by genotype. (b) A control/mutant pair of decoded theta sequences. Prior to decoding place cells with the highest spatial information scores were excluded from the control animal, such that, the average spatial information scores across the genotypes were comparable (1.28±0.11 CTR, 1.33±0.12 MUT). (c) Quadrant probability scores for each subject together with the average spatial information across all cells used for decoding.

Supplementary Figure 7 Recording sites and place cell yield.

Total numbers of tetrodes located in stratum pyramidale per anatomical region (CA3/CA1) for each animal across both genotypes. Also indicated are the average number of place cells recorded for each tetrode in a specific region, with the variance shown in parentheses. The four animals indicated in red were included only for LFP analysis given that the numbers of cells were insufficient to achieve accurate spatial decoding.

Supplementary Figure 8 Schematic representation of position decoding analysis.

(a) For each mouse a whole session template was constructed from all place cells, by binning firing rates across the track into 100 evenly spaced bins. (b) Spike data were then segmented into 100 ms chunks across the whole session, and firing rates for each cell calculated within this period. (c) For each 100 ms time bin the Pearson correlation was calculated between firing rates for all cells with all of the template firing rate vectors for each spatial bin. The decoded position was judged to be the spatial bin in which the highest correlation value was observed.

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Middleton, S., McHugh, T. Silencing CA3 disrupts temporal coding in the CA1 ensemble. Nat Neurosci 19, 945–951 (2016). https://doi.org/10.1038/nn.4311

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