File: tutorial_2_hybrid_nets.rst

package info (click to toggle)
neuron 8.2.6-2
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid
  • size: 34,760 kB
  • sloc: cpp: 149,571; python: 58,465; ansic: 50,329; sh: 3,510; xml: 213; pascal: 51; makefile: 35; sed: 5
file content (47 lines) | stat: -rw-r--r-- 1,391 bytes parent folder | download | duplicates (3)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
.. _tutorial_2_hybrid_nets:

Tutorial 2 : Making Hybrid Nets
=========

Outline
-------

:ref:`Example of a hybrid network <example_hybrid_network>`

:ref:`Step 1. Define the types of cells <step_1_define_type_of_cell>`

    A. We need a class of cells that can supply afferent spikes.

    B. We need a "motoneuron" or "M cell" class.

        1. :ref:`Specifying the anatomical and biophysical properties of the M cell class <step_1_define_type_of_cell>`

        2. :ref:`Specifying what kinds of synapses can be attached to an M cell <step_1_define_type_of_cell2>`

        3. :ref:`Placing synapses on the M cell <step_1_define_type_of_cell3>`

:ref:`Step 2. Create each cell in the network <step_2_create_each_cell>`

    A. We need a Network Builder

    B. We need an instance of each of our three cell types.

:ref:`Step 3. Connect the cells. <step_3_connect_the_cells>`

    A. Network architecture

    B. :ref:`Parameters <step_3_connect_the_cells_continued>`

:ref:`Run a simulation and plot the input and output spike trains <run_simulation_plot_input_output2>`

.. toctree::
    :hidden:

    example_hybrid_network.rst
    step_1_define_type_of_cell.rst
    step_1_define_type_of_cell2.rst
    step_1_define_type_of_cell3.rst
    step_2_create_each_cell.rst
    step_3_connect_the_cells.rst
    step_3_connect_the_cells_continued.rst
    run_simulation_plot_input_output2.rst