MAT model: Made-to-order spiking neuron model

This page was created by Ryota Kobayashi in collaboration with Yasuhiro Tsubo and Shigeru Shinomoto
based on a neuron model published in Frontiers in Computational Neuroscience 2009.

Web application for predicting spike times of a cortical neuron

1. Input Parameters of MAT model

    Typical parameters for Regular Spiking (RS), Intrinsic Bursting (IB), Fast Spiking (FS) neurons:
        .
      α 1 : ,   α 2 : ,   ω : .

2. Copy-and-paste Sampling interval and Input Current  

    Sampling interval:   [ms],
    Input Current [nA]:

3. Predicting Spike Times using MAT model  

  Input Current: I   (Total   [ms])
  Model Potential: V

4. Data Sheet of the predicted spike times

   

Model Equations

1. The model potential V

2. The spike threshold θ ,

3. Condition for Spike Generation,

 

A Sample MATLAB-code

1. Download MAT_current.m.

2. This code simulates the MAT neurons in response to the constant current, and generates Figure 5B in the original paper (Kobayashi, Tsubo, and Shinomoto, 2009). Please note that the voltage is shifted -65 mV.

A Sample C-code

1. Download MAT.c.

2. Prepare an input current file "current.txt".
      This file should be named as "current.txt", and consist of a column, i.e. Current [nA].
      The sampling interval is assumed to be 0.1 [ms]. An example: current.txt.

3. Compile the program:   "gcc MAT.c -lm -o MAT.o"

4. Run the program:   "./MAT.o α1 α2 ω"
      For the RS neuron, you can run the C program with "./MAT.o 37 2.0 19".

5. Two output files: "voltage.txt" and "spiketime.txt".
      voltage.txt: Time[ms], Voltage[mV]
      spiketime.txt: SpikeTime[ms].

Original Paper

Kobayashi R, Tsubo Y, and Shinomoto S.
Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold.
Frontiers in Computational Neuroscience 3:9 (2009)

If you have any questions, or have suggestions for improving the programs, please contact  Shigeru Shinomoto, who is conducting these studies.