• DocumentCode
    953999
  • Title

    Modeling the Nonlinear Properties of the in vitro Hippocampal Perforant Path-Dentate System Using Multielectrode Array Technology

  • Author

    Dimoka, Angelika ; Courellis, Spiros H. ; Gholmieh, Ghassan I. ; Marmarelis, Vasilis Z. ; Berger, Theodore W.

  • Author_Institution
    California Univ., Riverside
  • Volume
    55
  • Issue
    2
  • fYear
    2008
  • Firstpage
    693
  • Lastpage
    702
  • Abstract
    A modeling approach to characterize the nonlinear dynamic transformations of the dentate gyrus of the hippocampus is presented and experimentally validated. The dentate gyrus is the first region of the hippocampus which receives and integrates sensory information via the perforant path. The perforant path is composed of two distinct pathways: (1) the lateral path and (2) the medial perforant path. The proposed approach examines and captures the short-term dynamic characteristics of these two pathways using a nonparametric, third-order Poisson-Volterra model. The nonlinear characteristics of the two pathways are represented by Poisson-Volterra kernels, which are quantitative descriptors of the nonlinear dynamic transformations. The kernels were computed with experimental data from in vitro hippocampal slices. The electrophysiological activity was measured with custom-made multielectrode arrays, which allowed selective stimulation with random impulse trains and simultaneous recordings of extracellular field potential activity. The results demonstrate that this mathematically rigorous approach is suitable for the multipathway complexity of the hippocampus and yields interpretable models that have excellent predictive capabilities. The resulting models not only accurately predict previously reported electrophysiological descriptors, such as paired pulses, but more important, can be used to predict the electrophysiological activity of dentate granule cells to arbitrary stimulation patterns at the perforant path.
  • Keywords
    Volterra series; bioelectric potentials; biomedical electrodes; brain; cellular biophysics; mean square error methods; neurophysiology; nonparametric statistics; stochastic processes; Laguerre expansion; dentate granule cell; dentate gyrus; electrophysiological activity; extracellular field potential activity; hippocampal perforant path-dentate system; multielectrode array; multipathway complexity; nonlinear dynamic transformation; nonparametric model; random impulse train; selective stimulation; sensory information integration; synaptic transmission; third-order Poisson-Volterra model; Biological materials; Biomedical engineering; Biomedical materials; Biomedical measurements; Brain modeling; Electrophysiology; Face; Hippocampus; In vitro; Kernel; Nonlinear dynamical systems; Predictive models; Viterbi algorithm; Dentate Gyrus; Dentate gyrus; Hippocampus, , , , , ,; Kernel; Laguerre Expansion; Laguerre expansion; Multi Electrode; Multi Input; Poisson-Volterra; Volterra kernel; electrophysiology; hippocampus; multielectrode arrays; nonlinear modeling; perforant path; synaptic transmission; Action Potentials; Cerebellar Nuclei; Computer Simulation; Hippocampus; Microelectrodes; Models, Neurological; Nerve Net; Nonlinear Dynamics; Perforant Pathway;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2007.908075
  • Filename
    4360136