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Overcoming-dispersion-trains

This repository provides COMSOL and MATLAB model files discussed in the paper: "Method for overcoming temporal dispersion in unmyelinated nerves to image them with Electrical Impedance Tomography (EIT)", I Tarotin et al.

List of the attached files:

Modelling:

  • Cfibre_model_fin_RepdZ.mph: FEM model of a mammalian C fibre, COMSOL
  • Cfibre_model_fin_RepdZ_cuff.mph: FEM model of a mammalian C fibre with the cuff (see the paper), COMSOL
  • dZ_trains_FEM.mat: MATLAB database with the dZ trains simulated with the FEM model of the single C fibre with the cuff
  • ap_dZ_shape_C_cuff.mat: MATLAB database with single AP and dZ simulated with the FEM model with the cuff
  • Model_matching_with_experiment.m: MATLAB code used for adjustment of the created statistical model to the experimental recordings
  • FullStatModel_clean.m: MATLAB code of the developed statistical model

Processing/plotting of the obtained experimental data:

  • post_processing_single_clean.m: Post processing of the data recorded with stimulation by continuous (single) pulses
  • post_processing_trains_clean.m: Post processing of the data recorded with stimulation by series (trains) of pulses
  • plot_singledZ_clean.m: Plotting the processed single spikes data
  • plot_traindZ_clean.m: Plotting the processed trains data
  • plot_CAP_w: Plotting CAPs

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