Abstract
Ideally detailed neuron models should make use of morphological and electrophysiological data from the same cell. However, this rarely happens. Typically a modeler will choose a cell morphology from a public database, assign standard values for R a, C m, and other parameters and then do the modeling study. The assumption is that the model will produce results representative of what might be obtained experimentally. To test this assumption we developed models of CA1 hippocampal pyramidal neurons using 4 different morphologies obtained from 3 public databases. The multiple run fitter in NEURON was used to fit parameter values in each of the 4 morphological models to match experimental data recorded from 19 CA1 pyramidal cells. Fits with fixed standard parameter values produced results that were generally not representative of our experimental data. However, when parameter values were allowed to vary, excellent fits were obtained in almost all cases, but the fitted parameter values were very different among the 4 reconstructions and did not match standard values. The differences in fitted values can be explained by very different diameters, total lengths, membrane areas and volumes among the reconstructed cells, reflecting either cell heterogeneity or issues with the reconstruction data. The fitted values compensated for these differences to make the database cells and experimental cells more similar electrotonically. We conclude that models using fully reconstructed morphologies need to be calibrated with experimental data (even when morphological and electrophysiological data come from the same cell), model results should be generated with multiple reconstructions, morphological and experimental cells should come from the same strain of animal at the same age, and blind use of standard parameter values in models that use reconstruction data may not produce representative experimental results.
Similar content being viewed by others
References
Ambros-Ingerson J, Holmes WR (2005) Analysis and comparison of morphological reconstructions of hippocampal field CA1 pyramidal cells. Hippocampus 15: 302–315.
Ascher P, Nowak L (1988) The role of divalent cations in N-methyl-D-aspartate responses of mouse central neurons in culture. J. Physiol. Lond. 399: 247–266.
Blanton MG, Lo Turco J, Kriegstein AR (1989) Whole cell recording from neurons in slices of reptilian and mammalian cerebral cortex. J. Neurosci. Methods 30: 203–210.
Cannon RC, Turner DA, Pyapali GK, Wheal HV (1998) An online archive of reconstructed hippocampal neurons. J. Neurosci. Methods 4: 49–54.
Cannon RC, Howell FW, Goddard NH, DeSchutter E (2002) Non-curated distributed databases for experimental data and models in neuroscience. Network: Comput. Neural Syst. 13: 415–428.
Chitwood RA, Hubbard A, Jaffe DB (1999) Passive electrotonic properties of rat hippocampal CA3 interneurones. J. Physiol. Lond. 515: 743–756.
Gasparini S, DiFrancesco D (1997) Action of the hyperpolarization-activated current (Ih) blocker ZD 7288 in hippocampal CA1 neurons. Pflugers Arch. 435: 99–106.
Grover LM (1998) Evidence for postsynaptic induction and expression of NMDA receptor independent LTP. J. Neurophysiol. 79: 1167–1182.
Grover LM, Chen Y (1999) Evidence for involvement of group II/III metabotropic glutamate receptors in NMDA receptor-independent long-term potentiation. J. Neurophysiol. 82: 2956–2969.
Harris KM, Jensen FE, Tsao B (1992) Three-dimensional structure of dendritic spines and synapses in rat hippocampus (CA1) at postnatal day 15 and adult ages: Implications for the maturation of synaptic physiology and long-term potentiation. J. Neurosci. 12(7): 2685–2705
Harris NC, Constanti A (1995) Mechanism of block by ZD 7288 of the hyperpolarization-activated inward rectifying current in guinea pig substantia nigra neurons in vitro. J. Neurophysiol. 74: 2366–2378.
Hausser M, Mel B (2003) Dendrites: Bug or feature? Curr. Opin. Neurobiol. 13: 372–383.
Hines M, Carnevale NT (1997) The NEURON simulation environment. Neural Comput. 9: 1179–1209.
Hoffman DA, Magee JC, Colbert CM, Johnston D (1997) K+ channel regulation of signal propagation in dendrites of hippocampal pyramidal neurons. Nature 387: 869–875.
Holmes WR (1995) Modeling the effect of diffusion and uptake on NMDA and non-NMDA receptor saturation. Biophys. J. 69(5): 1734–1747.
Ishizuka N, Cowan WM, Amaryl DG (1995) A quantitative analysis of the dendritic organization of pyramidal cells in the rat hippocampus. J. Comp. Neurol. 362: 17–45.
Jaeger D (2001) Accurate reconstruction of neuronal morphology. In E. DeSchutter, ed. Computational Neuroscience: Realistic Modeling for Experimentalists. CRC Press, Boca Raton, FL, pp 159–178.
Jaffe DB, Carnevale NT (1999) Passive normalization of synaptic integration influenced by dendritic architecture. J. Neurophysiol. 82: 3268–3285.
Krichmar JL, Nasuto SJ, Scorcioni R, Washington SD, Ascoli GA (2002) Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: A simulation study. Brain Res. 941: 11–28.
Maccaferri G, Mangoni M, Lazzari A, DiFrancesco D (1993) Properties of the hyperpolarization-activated current in rat hippocampal CA1 pyramidal cells. J. Neurophysiol. 69: 2129–2136.
Magee JC (1998) Dendritic hyperpolarization-activated currents modify the integrative properties of hippocampal CA1 pyramidal neurons. J. Neurosci. 18(19): 7613–7624.
Magee JC (1999) Voltage-gated ion channels in dendrites. In G Stuart, N Spruston, M Hausser, eds. Dendrites. Oxford Univ. Press, New York, NY, pp. 139–160.
Mainen ZF, Sejnowski TJ (1996) Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382: 363–366.
Major G, Larkman AU, Jonas P, Sakmann B, Jack JJB (1994) Detailed passive cable models of whole-cell recorded CA3 pyramidal neurons in rat hippocampal slices. J. Neurosci. 14: 4613–4638.
Megias M, Emri A, Freund TF, Gulyas AI (2001) Total number and distribution of inhibitory and excitatory synapses on hippocampal CA1 pyramidal cells. Neuroscience 102: 527–540.
Migliore M, Hoffman DA, Magee JC, Johnston D (1999) Role of an A-type K+ conductance in the back-propagation of action potentials in the dendrites of hippocampal pyramidal neurons. J. Computat. Neurosci. 7: 5–15.
Otis TS, DeKoninck Y, Mody I (1993) Characterization of synaptically elicited GABAB responses using patch-clamp recordings in rat hippocampus slices. J. Physiol. (Lond.) 463: 391–407.
Poirazi P, Brannon T, Mel BW (2003) Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell. Neuron 37: 977–987.
Pyapali GK, Sik A, Penttonen M, Buzsaki G, Turner DA (1998) Dendritic properties of hippocampal CA1 pyramidal neurons in the rat: intracellular staining in vivo and in vitro. J. Comp. Neurol. 391: 335–352.
Rall W (1969) Time constants and electrotonic length of membrane cylinders and neurons. Biophys. J. 9: 1483–1508.
Rall W, Burke RE, Holmes WR, Jack JJB, Redman SJ, Segev I (1992) Matching dendritic neuron models to experimental data. Phys. Rev. 72 (4, Suppl): S159–S186.
Roth A, Hausser M (2001) Compartmental models of rat cerebellar Purkinje cells based on simultaneous somatic and dendritic patch-clamp recordings. J. Physiol. Lond. 535: 445–472.
Schaefer AT, Larkum ME, Sakmann B, Roth A (2003) Coincidence detection in pyramidal neurons is tuned by their branching pattern. J. Neurophysiol. 89: 3143–3154.
Schiller J, Major G, Koester HJ, Schiller Y (2000) NMDA spikes in basal dendrites of cortical pyramidal neurons. Nature 404: 285–289.
Scorcioni R, Lazarewicz MT, Ascoli GA (2004) Hippocampal pyramidal cells: Differences between anatomical classes and reconstructing laboratories. J. Comp. Neurol. 473: 177–193.
Segev I, London M (2000) Untangling dendrites with quantitative models. Science 290: 744–750.
Shen GY, Chen WR, Midtgaard J, Shepherd GM, Hines ML (1999) Computational analysis of action potential initiation in mitral cell soma and dendrites based on dual patch recordings. J. Neurophysiol. 82: 3006–3020.
Stratford K, Mason A, Larkman G, Major G, Jack JJB (1989) The modeling of pyramidal neurons in the visual cortex. In R Durbin, C Miall, G Mitchison, eds. The Computing Neuron. Addison-Wesley, Reading, MA, pp. 296–321.
Stuart G, Spruston N (1998) Determinants of voltage attenuation in neocortical pyramidal neuron dendrites. J. Neurosci. 18(10): 3501–3510.
Szilagy T, De Schutter E (2004) Effects of variability in anatomical reconstruction techniques on models of synaptic integration by dendrites: A comparison of three Internet archives. Eur. J. Neurosci. 19(5): 1257–1266.
van Ooyen A, Duijnhouwer J, Remme MWH, van Pelt J (2002) The effect of dendritic topology on firing patterns in model neurons. Network: Comput. Neural. Syst. 13: 311–325.
Vasilyev DV, Barish ME (2002) Postnatal development of hyperpolarization-activated excitatory current Ih in mouse hippocampal pyramidal neurons. J. Neurosci. 22(20): 8992–9004.
Vetter P, Roth A, Hausser M (2001) Propagation of action potentials in dendrites depends on dendritic morphology. J. Neurophysiol. 85: 926–937.
Wei DS, Mei YA, Bagal A, Kao JP, Thompson SM, Tang CM (2001) Compartmentalized and binary behavior of terminal dendrites in hippocampal pyramidal neurons. Science 293: 2272–2275.
Zhu JJ (2000) Maturation of layer 5 neocortical pyramidal neurons: amplifying salient layer 1 and layer 4 inputs by Ca2+ action potentials in adult rat tuft dendrites. J. Physiol. Lond. 526: 571–587.
Author information
Authors and Affiliations
Corresponding author
Additional information
Action Editor: Steve Redman
Rights and permissions
About this article
Cite this article
Holmes, W.R., Ambros-Ingerson, J. & Grover, L.M. Fitting experimental data to models that use morphological data from public databases. J Comput Neurosci 20, 349–365 (2006). https://doi.org/10.1007/s10827-006-7189-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10827-006-7189-8