Skip to main content

Different Frequency-Dependent Properties Between Dorsal and Ventral Hippocampal Synapses

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10512))

Abstract

The hippocampus is a brain region crucially involved in various cognitive functions including learning and memory processes. The hippocampal functions are performed by specific computations of its intrinsic neural circuitry in combination with interaction of the hippocampus with other brain regions. Therefore, the hippocampus has been conceived as a key network to studying and understanding the fundamental neural computations that supports higher brain functions. The hippocampus-involving functions are segregated along the longitudinal axis of the hippocampus. Importantly, it has been recently revealed that the local hippocampal circuit presents significant specializations between the two opposite poles or segments of the structure, namely between the dorsal and the ventral hippocampus suggesting that distinct neural processing may support the different functions performed by the hippocampus segments. The signal processing by neural networks crucially involves synaptic computations. In this study, we examined the synaptic dynamics of the dorsal and ventral synapses under conditions of different activation frequencies. We found that under consecutive activation the dorsal synapses display strong facilitation at a wide range of frequencies (1-40 Hz) while in ventral synapses the facilitation is restricted only to low activation frequency (1 Hz) and it lasted very shortly during activation. Thus, ventral synapses are mostly depressing. This evidence suggests that the dorsal hippocampal synaptic circuit presents wide-band filtering characteristics while the ventral are depressing low-pass synapses. The differing synaptic properties of the dorsal and the ventral hippocampus may underlie the higher ability for long-term plasticity of the dorsal hippocampus and the initiation of basic endogenous network oscillation in the ventral hippocampus.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Morris, R.G.: Theories of Hippocampal Function. In: Andersen, P., Morris, R., Amaral, D., Bliss, T., O’Keefe, J. (eds.) The Hippocampus Book, pp. 581–713. Oxford University Oress, Oxford (2007)

    Google Scholar 

  2. Strange, B.A., Witter, M.P., Lein, E.S., Moser, E.I.: Functional organization of the hippocampal longitudinal axis. Nat. Rev. Neurosci. 15, 655–669 (2014)

    Article  Google Scholar 

  3. Marr, D.: Simple memory: a theory for archicortex. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 262, 23–81 (1971)

    Article  Google Scholar 

  4. Burgess, N.: Computational models of the spatial and mnemonic functions of the hippocampus. In: Andersen, P., Morris, R., Amaral, D., Bliss, T., O’Keefe, J. (eds.) The Hippocampus Book, pp. 715–749. Oxford University Press, Oxford (2007)

    Google Scholar 

  5. Risold, P.Y., Swanson, L.W.: Structural evidence for functional domains in the rat hippocampus. Science 272, 1484–1486 (1996)

    Article  Google Scholar 

  6. Andersen, P., Soleng, A.F., Raastad, M.: The hippocampal lamella hypothesis revisited. Brain Research 886, 165–171 (2000)

    Article  Google Scholar 

  7. Papatheodoropoulos, C.: Electrophysiological evidence for long-axis intrinsic diversification of the hippocampus. Frontiers in Bioscience (Landmark Ed.) 23, 109–145 (2018)

    Article  Google Scholar 

  8. Eichenbaum, H., Amaral, D.G., Buffalo, E.A., Buzsaki, G., Cohen, N., Davachi, L., Frank, L., Heckers, S., Morris, R.G., Moser, E.I., Nadel, L., O’Keefe, J., Preston, A., Ranganath, C., Silva, A., Witter, M.: Hippocampus at 25. Hippocampus 26, 1238–1249 (2016)

    Article  Google Scholar 

  9. Bliss, T.V., Collingridge, G.L., Morris, R.: Synaptic plasticity in the hippocampus. In: Andersen, P., Morris, R., Amaral, D., Bliss, T., O’Keefe, J. (eds.) The Hippocampus Book, pp. 343–474 (2007)

    Google Scholar 

  10. Morris, R.G.: Long-term potentiation and memory. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 358, 643–647 (2003)

    Article  Google Scholar 

  11. Abbott, L.F., Regehr, W.G.: Synaptic Computation. Nature 431, 796–803 (2004)

    Article  Google Scholar 

  12. Regehr, W.G.: Short-term presynaptic plasticity. Cold Spring Harbor Perspectives in Biology 4, a005702 (2012)

    Article  Google Scholar 

  13. Lindner, B., Gangloff, D., Longtin, A., Lewis, J.E.: Broadband coding with dynamic synapses. The Journal of Neuroscience: the Official Journal of the Society for Neuroscience 29, 2076–2088 (2009)

    Article  Google Scholar 

  14. Lisman, J.E.: Bursts as a unit of neural information: making unreliable synapses reliable. Trends in Neurosciences 20, 38–43 (1997)

    Article  Google Scholar 

  15. Abbott, L.F., Varela, J.A., Sen, K., Nelson, S.B.: Synaptic depression and cortical gain control. Science 275, 220–224 (1997)

    Article  Google Scholar 

  16. Dobrunz, L.E., Stevens, C.F.: Heterogeneity of release probability, facilitation, and depletion at central synapses. Neuron 18, 995–1008 (1997)

    Article  Google Scholar 

  17. Raastad, M., Storm, J.F., Andersen, P.: Putative Single Quantum and Single Fibre Excitatory Postsynaptic Currents Show Similar Amplitude Range and Variability in Rat Hippocampal Slices. The European Journal of Neuroscience 4, 113–117 (1992)

    Article  Google Scholar 

  18. Rosenbaum, R., Rubin, J., Doiron, B.: Short term synaptic depression imposes a frequency dependent filter on synaptic information transfer. PLoS Computational Biology 8, e1002557 (2012)

    Article  MathSciNet  Google Scholar 

  19. Papatheodoropoulos, C., Kostopoulos, G.: Decreased ability of rat temporal hippocampal CA1 region to produce long-term potentiation. Neuroscience Letters 279, 177–180 (2000)

    Article  Google Scholar 

  20. Buzsaki, G.: Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning. Hippocampus 25, 1073–1188 (2015)

    Article  Google Scholar 

  21. Mizunuma, M., Norimoto, H., Tao, K., Egawa, T., Hanaoka, K., Sakaguchi, T., Hioki, H., Kaneko, T., Yamaguchi, S., Nagano, T., Matsuki, N., Ikegaya, Y.: Unbalanced excitability underlies offline reactivation of behaviorally activated neurons. Nature Neuroscience 17, 503–505 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Costas Papatheodoropoulos .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Papatheodoropoulos, C. (2017). Different Frequency-Dependent Properties Between Dorsal and Ventral Hippocampal Synapses. In: Frasson, C., Kostopoulos, G. (eds) Brain Function Assessment in Learning. BFAL 2017. Lecture Notes in Computer Science(), vol 10512. Springer, Cham. https://doi.org/10.1007/978-3-319-67615-9_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67615-9_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67614-2

  • Online ISBN: 978-3-319-67615-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics