Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Matching storage and recall: hippocampal spike timing–dependent plasticity and phase response curves

Nature Neuroscience volume 8, pages 1677–1683 (2005)Cite this article

Abstract

Hippocampal area CA3 is widely considered to function as an autoassociative memory. However, it is insufficiently understood how it does so. In particular, the extensive experimental evidence for the importance of carefully regulated spiking times poses the question as to how spike timing–based dynamics may support memory functions. Here, we develop a normative theory of autoassociative memory encompassing such network dynamics. Our theory specifies the way that the synaptic plasticity rule of a memory constrains the form of neuronal interactions that will retrieve memories optimally. If memories are stored by spike timing–dependent plasticity, neuronal interactions should be formalized in terms of a phase response curve, indicating the effect of presynaptic spikes on the timing of postsynaptic spikes. We show through simulation that such memories are competent analog autoassociators and demonstrate directly that the attributes of phase response curves of CA3 pyramidal cells recorded in vitro qualitatively conform with the theory.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Normative theory of spike timing–based autoassociative memory.
Figure 2: Quality of memory retrieval in an optimally constructed spike timing–based autoassociative memory model: numerical simulations.
Figure 3: Experimental measurement of the PRC in CA3 hippocampal neurons.
Figure 4: Effect of EPSG amplitude on the PRC.

Similar content being viewed by others

References

  1. Squire, L.R. Memory and the hippocampus: a synthesis from findings with rats, monkeys, and humans. Psychol. Rev. 99, 195–231 (1992).

    Article  CAS  Google Scholar 

  2. Cohen, N.J. & Eichenbaum, H. Memory, Amnesia, and the Hippocampal System (MIT Press, Cambridge, Massachusetts, 1993).

    Google Scholar 

  3. Rolls, E.T. & Treves, A. Neural Networks and Brain Function (Oxford Univ. Press, Oxford, 1998).

    Google Scholar 

  4. Amaral, D.G., Ishizuka, N. & Claiborne, B. Neurons, numbers and the hippocampal network. Prog. Brain Res. 83, 1–11 (1990).

    Article  CAS  Google Scholar 

  5. Hopfield, J.J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. USA 79, 2554–2558 (1982).

    Article  CAS  Google Scholar 

  6. Baird, B. Bifurcation and learning in network models of oscillating cortex. Physica D. 42, 365–384 (1990).

    Article  Google Scholar 

  7. Wang, D.L., Buhmann, J. & von der Malsburg, C. Pattern segmentation in associative memory. Neural Comput. 2, 94–106 (1990).

    Article  Google Scholar 

  8. Li, Z. Modeling the sensory computations of the olfactory bulb. in Models of Neural Networks Vol. 2 (eds. Domany, E., van Hemmen, J.L. & Schulten, K.) 221–251 (Springer-Verlag, New York, 1995).

    Google Scholar 

  9. Hendin, O., Horn, D. & Tsodyks, M.V. Associative memory and segmentation in an oscillatory neural model of the olfactory bulb. J. Comput. Neurosci. 5, 157–169 (1998).

    Article  CAS  Google Scholar 

  10. Li, Z. & Hertz, J. Odour recognition and segmentation by a model olfactory bulb and cortex. Network 11, 83–102 (2000).

    Article  CAS  Google Scholar 

  11. Hasselmo, M.E., Bodelon, C. & Wyble, B.P. A proposed function for hippocampal theta rhythm: separate phases of encoding and retrieval enhance reversal of prior learning. Neural Comput. 14, 793–817 (2002).

    Article  Google Scholar 

  12. Scarpetta, S., Li, Z. & Hertz, J. Hebbian imprinting and retrieval in oscillatory neural networks. Neural Comput. 14, 2371–2396 (2002).

    Article  Google Scholar 

  13. Jensen, O. & Lisman, J. Hippocampal sequence-encoding driven by a cortical multi-item working memory buffer. Trends Neurosci. 28, 67–72 (2005).

    Article  CAS  Google Scholar 

  14. Hopfield, J.J. Neurons with graded response have collective computational properties like those of two-state neurons. Proc. Natl. Acad. Sci. USA 81, 3088–3092 (1984).

    Article  CAS  Google Scholar 

  15. Treves, A. Graded-response neurons and information encodings in autoassociative memories. Phys. Rev. A. 42, 2418–2430 (1990).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  17. Poe, G.R., Nitz, D.A., McNaughton, B.L. & Barnes, C.A. Experience-dependent phase-reversal of hippocampal neuron firing during REM sleep. Brain Res. 855, 176–180 (2000).

    Article  CAS  Google Scholar 

  18. 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).

    Article  CAS  Google Scholar 

  19. Harris, K.D., Csicsvári, J., Hirase, H., Dragoi, G. & Buzsáki, G. Organization of cell assemblies in the hippocampus. Nature 424, 552–556 (2003).

    Article  CAS  Google Scholar 

  20. Skaggs, W.E. & McNaughton, B.L. Replay of neuronal firing sequences in rat hippocampus during sleep following spatial experience. Science 271, 1870–1873 (1996).

    Article  CAS  Google Scholar 

  21. Nádasdy, Z., Hirase, H., Czurkó, A., Csicsvári, J. & Buzsáki, G. Replay and time compression of recurring spike sequences in the hippocampus. J. Neurosci. 19, 9497–9507 (1999).

    Article  Google Scholar 

  22. Louie, K. & Wilson, M.A. Temporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep. Neuron 29, 145–156 (2001).

    Article  CAS  Google Scholar 

  23. Paulsen, O. & Sejnowski, T.J. Natural patterns of activity and long-term synaptic plasticity. Curr. Opin. Neurobiol. 10, 172–179 (2000).

    Article  CAS  Google Scholar 

  24. Bi, G. & Poo, M.M. Synaptic modification by correlated activity: Hebb's postulate revisited. Annu. Rev. Neurosci. 24, 139–166 (2001).

    Article  CAS  Google Scholar 

  25. Rinzel, J. & Ermentrout, B. Analysis of neural excitability and oscillations. in Methods in Neuronal Modeling 2nd edn. (eds. Koch, C. & Segev, I.) 251–291 (MIT Press, Cambridge, Massachusetts, 1998).

    Google Scholar 

  26. Brown, E., Moehlis, J. & Holmes, P. On the phase reduction and response dynamics of neural oscillator populations. Neural Comput. 16, 673–715 (2004).

    Article  Google Scholar 

  27. Gutkin, B.S., Ermentrout, G.B. & Reyes, A. Phase response curves determine the responses of neurons to transient inputs. J. Neurophysiol. 94, 1623–1635 (2005).

    Article  Google Scholar 

  28. Guevara, M.R., Glass, L. & Shrier, A. Phase locking, period-doubling bifurcations, and irregular dynamics in periodically stimulated cardiac cells. Science 214, 1350–1353 (1981).

    Article  CAS  Google Scholar 

  29. Ermentrout, B. & Kopell, N. Learning of phase lags in coupled neural oscillators. Neural Comput. 6, 225–241 (1994).

    Article  Google Scholar 

  30. Lampl, I. & Yarom, Y. Subthreshold oscillations of the membrane potential: a functional synchronizing and timing device. J. Neurophysiol. 70, 2181–2186 (1993).

    Article  CAS  Google Scholar 

  31. Ermentrout, G.B. & Kopell, N. Fine structure of neural spiking and synchronization in the presence of conduction delays. Proc. Natl. Acad. Sci. USA 95, 1259–1264 (1998).

    Article  CAS  Google Scholar 

  32. MacKay, D.J.C. Maximum entropy connections: neural networks. in Maximum Entropy and Bayesian Methods, Laramie, 1990 (eds. Grandy, Jr, W.T. & Schick, L.H.) 237–244 (Kluwer, Dordrecht, The Netherlands, 1991).

    Chapter  Google Scholar 

  33. Sommer, F.T. & Dayan, P. Bayesian retrieval in associative memories with storage errors. IEEE Trans. Neural Netw. 9, 705–713 (1998).

    Article  CAS  Google Scholar 

  34. Bi, G.Q. & Poo, M.M. Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J. Neurosci. 18, 10464–10472 (1998).

    Article  CAS  Google Scholar 

  35. Buzsáki, G. Theta oscillations in the hippocampus. Neuron 33, 325–340 (2002).

    Article  Google Scholar 

  36. Buzsáki, G. & Draguhn, A. Neuronal oscillations in cortical networks. Science 304, 1926–1929 (2004).

    Article  Google Scholar 

  37. Abbott, L.F. & Nelson, S.B. Synaptic plasticity: taming the beast. Nat. Neurosci. 3, 1178–1183 (2000).

    Article  CAS  Google Scholar 

  38. Ermentrout, B. Type I membranes, phase resetting curves, and synchrony. Neural Comput. 8, 979–1001 (1996).

    Article  CAS  Google Scholar 

  39. Engel, A., Englisch, H. & Schütte, A. Improved retrieval in neural networks with external fields. Europhys. Lett. 8, 393–399 (1989).

    Article  Google Scholar 

  40. Reyes, A.D. & Fetz, F.E. Effects of transient depolarizing potentials on the firing rate of cat neocortical neurons. J. Neurophysiol. 69, 1673–1683 (1993).

    Article  CAS  Google Scholar 

  41. Hasselmo, M.E. Neuromodulation: acetylcholine and memory consolidation. Trends Cogn. Sci. 3, 351–359 (1999).

    Article  CAS  Google Scholar 

  42. Froemke, R.C. & Dan, Y. Spike-timing-dependent synaptic modification induced by natural spike trains. Nature 416, 433–438 (2002).

    Article  CAS  Google Scholar 

  43. Sjostrom, P.J., Turrigiano, G.G. & Nelson, S.B. Rate, timing, and cooperativity jointly determine cortical synaptic plasticity. Neuron 32, 1149–1164 (2001).

    Article  CAS  Google Scholar 

  44. Lengyel, M., Szatmáry, Z. & Érdi, P. Dynamically detuned oscillations account for the coupled rate and temporal code of place cell firing. Hippocampus 13, 700–714 (2003).

    Article  Google Scholar 

  45. Huxter, J., Burgess, N. & O'Keefe, J. Independent rate and temporal coding in hippocampal pyramidal cells. Nature 425, 828–832 (2003).

    Article  CAS  Google Scholar 

  46. Huhn, Z., Orbán, G., Érdi, P. & Lengyel, M. Theta oscillation-coupled dendritic spiking integrates inputs on a long time scale. Hippocampus 15, 950–962 (2005).

    Article  Google Scholar 

  47. Siapas, A.G. & Wilson, M.A. Coordinated interactions between hippocampal ripples and cortical spindles during slow-wave sleep. Neuron 21, 1123–1128 (1998).

    Article  CAS  Google Scholar 

  48. Sirota, A., Csicsvári, J., Buhl, D. & Buzsáki, G. Communication between neocortex and hippocampus during sleep in rodents. Proc. Natl. Acad. Sci. USA 100, 2065–2069 (2003).

    Article  CAS  Google Scholar 

  49. Csicsvári, J., Hirase, H., Czurkó, A., Mamiya, A. & Buzsáki, G. Oscillatory coupling of hippocampal pyramidal cells and interneurons in the behaving rat. J. Neurosci. 19, 274–287 (1999).

    Article  Google Scholar 

  50. Siapas, A.G., Lubenov, E.V. & Wilson, M.A. Prefrontal phase locking to hippocampal theta oscillations. Neuron 46, 141–151 (2005).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank B. Gutkin, D. MacKay and E. Shea-Brown for valuable discussions and E.O. Mann and D. McLelland for their help with Igor procedures. This work was supported by the Gatsby Charitable Foundation (M.L., P.D.), the European Bayesian-Inspired Brain and Artefacts project (M.L., P.D.), the Biotechnology and Biological Sciences Research Council (J.K., O.P.), the Kwanjung Educational Foundation, Korea (J.K.) and the Oxford University Clarendon Fund (J.K.).

Author information

Authors and Affiliations

  1. Gatsby Computational Neuroscience Unit, University College London, 17 Queen Square, London, WC1N 3AR, UK

    Máté Lengyel & Peter Dayan

  2. University Laboratory of Physiology, Oxford University, Parks Road, Oxford, OX1 3PT, UK

    Jeehyun Kwag & Ole Paulsen

Authors
  1. Máté Lengyel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jeehyun Kwag
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ole Paulsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Peter Dayan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Máté Lengyel.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

Recall performance in adversarial settings. (PDF 185 kb)

Supplementary Fig. 2

Consequences of a broad, smoothly varying STDP curve on the optimal coupling function and phase response curves. (PDF 165 kb)

Supplementary Fig. 3

Effect of increased oscillatory frequency on the PRC. (PDF 359 kb)

Supplementary Fig. 4

Burst-based PRCs. (PDF 448 kb)

Supplementary Methods (PDF 29 kb)

Supplementary Note (PDF 76 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lengyel, M., Kwag, J., Paulsen, O. et al. Matching storage and recall: hippocampal spike timing–dependent plasticity and phase response curves. Nat Neurosci 8, 1677–1683 (2005). https://doi.org/10.1038/nn1561

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn1561

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing