{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fig2b, left, I-V curve, simple model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from neuron import h\n",
    "import numpy as np\n",
    "import os.path\n",
    "import sys\n",
    "sys.path.append('../../libs/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# compile neuron channels\n",
    "!cd ../../data/morphology && nrnivmodl && cd -"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load model\n",
    "# works only on linux\n",
    "model = '../../data/morphology/soma_axon.hoc'\n",
    "dllpath = '../../data/morphology/x86_64/.libs/libnrnmech.so'\n",
    "h.nrn_load_dll(dllpath)\n",
    "h.load_file(model)\n",
    "h.init_cell()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# parameters\n",
    "# I-V related\n",
    "volt_range = [-65, -50]\n",
    "no_pts = 15\n",
    "keep_soma_Na = True\n",
    "\n",
    "# simulation\n",
    "h.tstart = 0.\n",
    "h.tstop = 20.\n",
    "h.dt = 0.001\n",
    "rm = 30000.\n",
    "st_dur1 = 2.\n",
    "st_dur2 = 3.\n",
    "v_init = -70\n",
    "\n",
    "# morphology \n",
    "h.soma.L = 30.\n",
    "h.soma.diam = 20.\n",
    "h.soma.nseg = 6\n",
    "h.soma.g_pas = 1./rm\n",
    "h.soma.cm = 0.75\n",
    "\n",
    "h.axon.L = 50.\n",
    "h.axon.diam =1.\n",
    "h.axon.nseg = 10\n",
    "h.axon.g_pas = 1./rm\n",
    "h.axon.cm = 0.75 * 0.75\n",
    "\n",
    "# general\n",
    "h.rm = rm\n",
    "h.v_init = v_init\n",
    "h.ra = 150 \n",
    "h.c_m = 0.75\n",
    "h.xn = 1 \n",
    "\n",
    "# potassium\n",
    "h.Ek = -80. # mV # Fig2: = 80; Fig4b:\n",
    "h.gk = 1600.\n",
    "h.gkm = 0.3\n",
    "h.soma.gbar_kv = 1600/5.\n",
    "h.axon.gbar_kv = 1600.\n",
    "\n",
    "# sodium\n",
    "h.Ena = 60.\n",
    "h.gna = 8000.\n",
    "h.gkm_soma = 0.3 \n",
    "if keep_soma_Na:\n",
    "    h.soma.gbar_na = 0.1*8000\n",
    "else:\n",
    "    h.soma.gbar_na = 0.\n",
    "h.axon.gbar_na = 8000.\n",
    "            \n",
    "# calcium (set no calcium in the model)\n",
    "h.gca = 0.\n",
    "h.gkca = 0.\n",
    "h.gca_soma = 0.\n",
    "h.gkca_soma = 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# calculate current using p/n protocol\n",
    "\n",
    "from apkink import protocols as pp\n",
    "i_soma_pn = pp.pn_protocol(v_memb=v_init)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/maja/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:14: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n"
     ]
    }
   ],
   "source": [
    "# calculate I-V for different holding volt\n",
    "\n",
    "volt_space = np.linspace(volt_range[0], volt_range[1], no_pts)\n",
    "i_space = np.zeros([no_pts])\n",
    "m_axon_space = np.zeros([no_pts])\n",
    "\n",
    "for idx,volt in enumerate(volt_space): \n",
    "    # create stimulation\n",
    "    i_val, m_axon_val = pp.i_v_protocol(volt,v_memb=v_init,st_dur1=st_dur1,st_dur2=st_dur2)\n",
    "    \n",
    "    p_v_value = i_soma_pn*((volt-(v_init))/5.) \n",
    "    i_soma = i_val - p_v_value\n",
    "    peak = min(i_soma[(st_dur1+st_dur2+0.2)/h.dt:(st_dur1+st_dur2+3.0)/h.dt])\n",
    "    \n",
    "    i_space[idx] = peak\n",
    "    m_axon_space[idx] = np.max(m_axon_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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OlTQXOJysM8QXIuKagsNqWx5tIm1OUm1g4kRY9JLL49bO+jojssa43Jc2jzjR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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fadaf003f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the figure\n",
    "import matplotlib.pylab as plt\n",
    "%matplotlib inline\n",
    "plt.subplot(1,2,1)\n",
    "\n",
    "plt.plot(volt_space, i_space)\n",
    "plt.ylabel('current (nA)')\n",
    "plt.xlabel('voltage (mV)')\n",
    "plt.subplot(1,2,2)\n",
    "plt.plot(volt_space, m_axon_space)\n",
    "plt.ylim([-.1,1.1])\n",
    "plt.ylabel('fraction of open Na+ channels')\n",
    "plt.xlabel('voltage (mV)')\n",
    "plt.tight_layout()"
   ]
  }
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