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The engram formation and the global oscillations of CA3

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Abstract

The investigation on the conditions which cause global population oscillatory activities in neural fields, originated some years ago with reference to a kinetic theory of neural systems, as been further deepened in this paper. In particular, the genesis of sharp waves and of some rhythmic activities, such as theta and gamma rhythms, of the hippocampal CA3 field, behaviorally important for their links to learning and memory, has been analyzed with more details. To this aim, the modeling-computational framework previously devised for the study of activities in large neural fields, has been enhanced in such a way that a greater number of biological features, extended dendritic trees—in particular, could be taken into account. By using that methodology, a two-dimensional model of the entire CA3 field has been described and its activity, as it results from the several external inputs impinging on it, has been simulated. As a consequence of these investigations, some hypotheses have been elaborated about the possible function of global oscillatory activities of neural populations of Hippocampus in the engram formation.

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References

  • Amaral DG, Ishizuka N, Claiborne B (1990) Neurons, number and the hippocampal network. In: Storm-Mathisen J, Zimmer J, Otterson OP (eds) Progress in brain research, vol 83. Elsevier, Amsterdam, pp 1–11

    Google Scholar 

  • Angel E, Bellman R (1972) Dynamic programming and partial differential equations. Academic Press, New York

    Google Scholar 

  • Borisyuk RM, Borisyuk GN (1997) Information coding on the basis of synchronization of neuronal activity. Biosystems 40:3–10

    Article  PubMed  CAS  Google Scholar 

  • Buzsaki G (1986) Hippocampal sharp waves: their origin and significance. Brain Res 398:242–252

    Article  PubMed  CAS  Google Scholar 

  • Buzsaki G, Chrobak JJ (1995) Temporal structure in spatially organized neuronal ensembles: a role for interneuronal networks. Curr Opin Neurobiol 5:504–510

    Article  PubMed  CAS  Google Scholar 

  • Cohen NJ, Eichenbaum H (1993) Memory, amnesia, and the hippocampal system. The MIT Press, Cambridge

    Google Scholar 

  • Csicsvari J, Hirase H, Czurko A, Mamiya A, Buzsaki G (1999) Oscillatory coupling of hippocampal pyramidal cells and interneurons in the behaving rat. J Neurosci 19:274–287

    PubMed  CAS  Google Scholar 

  • Draguhn A, Traub RD, Bibbig A, Schmitz D (2000) Ripple (approximately 200-Hz) oscillations in temporal structures. J Clin Neurophysiol 17:361–376

    Article  PubMed  CAS  Google Scholar 

  • Gulyas AI, Seress L, Toth K, Acsady L, Antal M, Freund TF (1991) Septal gabaergic neurons innervate inhibitory interneurons in the hippocampus of the macaque monkey. Neurosci 41:381–390

    Article  CAS  Google Scholar 

  • Howe AG, Levy WB (2007) A hippocampal model predicts a fluctuating phase transition when learning certain trace conditioning paradigms. Cogn Neurodyn 1:143–155

    Article  PubMed  Google Scholar 

  • Ishizuka N, Weber J, Amaral DG (1990) Organization of intra-hippocampal projections originating from CA3 pyramidal cells in the rat. J Comp Neurol 295:580–623

    Article  PubMed  CAS  Google Scholar 

  • Kandel A, Buzsaki G (1997) Cellular-synaptic generation of sleep spindles, spike-and-wave discharges, and evoked thalamocortical responses in the neocortex of the rat. J Neurosci 17:6783–6797

    PubMed  CAS  Google Scholar 

  • Milner B (1972) Disorders of learning and memory after temporal lobe lesions in man. Clinical Neurosurg 19:421–446

    CAS  Google Scholar 

  • Mishkin M (1982) A memory system in the monkey. Philos Trans R Soc Lond B298:85–95

    Article  Google Scholar 

  • Molter C, Sato N, Yamaguchi Y (2007) Reactivation of behavioral activity during Sharp Waves: a computational model for two stage hippocampal dynamics. Hippocampus 17:201–209

    Article  PubMed  Google Scholar 

  • Orbán G, Kiss T, Erdi P (2006) Intrinsic and synaptic mechanisms determining the timing of neuron population activity during hippocampal theta oscillation. J Neurophysiol 96:2889–2904

    Article  PubMed  Google Scholar 

  • Paxinos G, Watson C (1986) The rat brain in stereotaxic coordinates. Academic Press, San Diego

    Google Scholar 

  • Scoville WB, Milner B (1957) Loss of recent memory after bilateral hippocampal lesions. J Neurol Psychiatry 20:11–21

    Article  CAS  Google Scholar 

  • Squire LR, Shimamura AP, Amaral DG (1989) Memory and the hippocampus. In: Byrne JH, Berry WO (eds) Neural models of plasticity. Academic Press, San Diego, pp 208–239

    Google Scholar 

  • Traub RD, Cunningham MO, Gloveli T, LeBeau FE, Bibbig A, Buhl EH, Whittington MA (2003) GABA-enhanced collective behavior in neuronal axons underlies persistent gamma-frequency oscillations. Proc Natl Acad Sci USA 100:11047–11052

    Article  PubMed  CAS  Google Scholar 

  • Ventriglia F (1974) Kinetic approach to neural systems. I. Bull Math Biol 36:534–544

    Google Scholar 

  • Ventriglia F (1990) Activity in cortical-like neural systems: short-range effects and attention phenomena. Bull Math Biol 52:397–429

    PubMed  CAS  Google Scholar 

  • Ventriglia F (1994) Towards a kinetic theory of cortical-like neural fields. In: Ventriglia F (eds) Neural modeling and neural networks. Pergamon Press, Oxford, pp 217–249

    Google Scholar 

  • Ventriglia F (1998) Computational experiments support a competitive function in the CA3 region of the hippocampus. Bull Math Biol 60:373–407

    Article  PubMed  CAS  Google Scholar 

  • Ventriglia F (2005) Coding by neural population oscillations? In: De Gregorio M, Di Maio V, Frucci M, Musio C (eds) Brain, vision and artificial intelligence. LNCS 3704. Springer, Berlin, pp 78–88

  • Ventriglia F (2006) Global rhythmic activities in hippocampal fields and neural coding. BioSystems 86:38–45

    Article  PubMed  Google Scholar 

  • Ventriglia F, Di Maio V (2005) Neural code and irregular spike trains. In: De Gregorio M, Di Maio V, Frucci M, Musio C (eds) Brain, vision and artificial intelligence. LNCS 3704. Springer, Berlin, pp 89–98

  • Vertes RP (1986) Brainstem modulations of hippocampus: anatomy, physiology, and significance. In: Isaacson RL, Pribram KL (eds) The hippocampus, vol 4. Plenum Press, New York, pp 41–75

    Google Scholar 

  • Wagatsuma H, Yamaguchi Y (2007) Neural dynamics of the cognitive map in the hippocampus. Cogn Neurodyn 1:119–141

    Article  PubMed  Google Scholar 

  • West MJ (1990) Stereological studies of the hippocampus: a comparison of the hippocampal subdivisions of diverse species including hedgehogs, laboratory rodents, wild mice and men. In: Storm-Mathisen J, Zimmer J, Otterson OP (eds) Progress in brain research, vol 83. Elsevier, Amsterdam, pp 13–36

    Google Scholar 

  • Vinogradova OS (2001) Hippocampus as comparator: role of the two input and two output systems of the hippocampus in selection and registration of information. Hippocampus 11:578–598

    Article  PubMed  CAS  Google Scholar 

  • Wilson MA, McNaughton B (1993) Dynamics of the hippocampal ensemble code for space. Science 261:1055–1058

    Article  PubMed  CAS  Google Scholar 

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Correspondence to Francesco Ventriglia.

Appendix

Appendix

The following values have been utilized for the basic neuronal parameters in the above reported computer simulations. The resting levels \(e_{rs^{\prime}}\) of different neurons were: e rp = 0.34 (corresponding to −75 mV)—pyramidal neurons, e rf = 0.67 (corresponding to −62.5 mV)—fast inhibitory neurons, e rs = 0.34 (corresponding to −75 mV)—slow inhibitory neurons. The periods of absolute refractoriness and the synaptic delays were: τ p = 15 ms, τ f = τ s = 1.75 ms and t 0p = t 0f = t 0s = 0.5 ms, respectively. The slow-IPSP onset time had value \(\bar{t}_{s} = 30\,{\rm ms}.\) The long-distance impulses in the absorption-free zone assumed a constant velocity v′ = 60 cm/s.

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Ventriglia, F. The engram formation and the global oscillations of CA3. Cogn Neurodyn 2, 335–345 (2008). https://doi.org/10.1007/s11571-008-9057-x

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