From 97aa879466b7a081ef7d59fc4213436ecabf4e98 Mon Sep 17 00:00:00 2001
From: ejayromero <44366753+ejayromero@users.noreply.github.com>
Date: Thu, 15 Aug 2024 09:08:32 +0200
Subject: [PATCH] Example 7 proposition (#194)

* First commit for example 7

* Minor details

* add some comments

* modification following PR comments

* cleaned version of previous commit

* additional cleaning of comments
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 examples/README.rst                           |    2 +
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 create mode 100644 examples/7-Extra-Simulation/Multiple-protocols.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Additional stimulation protocols\n",
+    "This notebook shows different ways to apply what was seen in previous examples. The goal is to show how to use it and modifiy it for particular cases.\n",
+    "\n",
+    "The examples are:\n",
+    "\n",
+    "1. Negative and rheobase step current\n",
+    "2. Multiple negative step current\n",
+    "3. IV-curve resulting from previous example.\n",
+    "4. Multiple positive step current\n",
+    "5. FI-curve resulting from previous example\n",
+    "6. Voltage sag vs distance from soma on multiple dendrites positions\n",
+    "7. A modified EPSP which compared Psp ratio vs distance to soma on multiple dendrites positions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compiling mechanisms"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/home/eromero/BBP/.venv/bin/nrnivmodl:10: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html\n",
+      "  from pkg_resources import working_set\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/home/eromero/BBP/BlueCelluLab/examples/7-Extra-Simulation\n",
+      "Mod files: \"../mechanisms/../mechanisms/Ca.mod\" \"../mechanisms/../mechanisms/CaDynamics_DC0.mod\" \"../mechanisms/../mechanisms/CaDynamics_E2.mod\" \"../mechanisms/../mechanisms/Ca_HVA.mod\" \"../mechanisms/../mechanisms/Ca_HVA2.mod\" \"../mechanisms/../mechanisms/Ca_LVAst.mod\" \"../mechanisms/../mechanisms/DetAMPANMDA.mod\" \"../mechanisms/../mechanisms/DetGABAAB.mod\" \"../mechanisms/../mechanisms/GluSynapse.mod\" \"../mechanisms/../mechanisms/Ih.mod\" \"../mechanisms/../mechanisms/Im.mod\" \"../mechanisms/../mechanisms/K_Pst.mod\" \"../mechanisms/../mechanisms/K_Tst.mod\" \"../mechanisms/../mechanisms/KdShu2007.mod\" \"../mechanisms/../mechanisms/NaTa_t.mod\" \"../mechanisms/../mechanisms/NaTg.mod\" \"../mechanisms/../mechanisms/NaTs2_t.mod\" \"../mechanisms/../mechanisms/Nap_Et2.mod\" \"../mechanisms/../mechanisms/ProbAMPANMDA_EMS.mod\" \"../mechanisms/../mechanisms/ProbGABAAB_EMS.mod\" \"../mechanisms/../mechanisms/SK_E2.mod\" \"../mechanisms/../mechanisms/SKv3_1.mod\" \"../mechanisms/../mechanisms/StochKv.mod\" \"../mechanisms/../mechanisms/StochKv3.mod\" \"../mechanisms/../mechanisms/TTXDynamicsSwitch.mod\" \"../mechanisms/../mechanisms/VecStim.mod\" \"../mechanisms/../mechanisms/gap.mod\" \"../mechanisms/../mechanisms/netstim_inhpoisson.mod\"\n",
+      "\n",
+      " -> \u001b[32mCompiling\u001b[0m mod_func.cpp\n",
+      " => \u001b[32mLINKING\u001b[0m shared library ./libnrnmech.so\n",
+      "Successfully created x86_64/special\n"
+     ]
+    }
+   ],
+   "source": [
+    "!nrnivmodl ../mechanisms"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Reminder**: The compiled mechanisms need to be provided before importing bluecellulab."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "sns.set_style('darkgrid')\n",
+    "import numpy as np\n",
+    "\n",
+    "from pathlib import Path\n",
+    "\n",
+    "from matplotlib import pyplot as plt\n",
+    "from matplotlib.pyplot import get_cmap\n",
+    "\n",
+    "import neuron\n",
+    "from bluecellulab import Cell\n",
+    "from bluecellulab.simulation import Simulation\n",
+    "from bluecellulab.simulation.neuron_globals import NeuronGlobals\n",
+    "from bluecellulab.tools import search_threshold_current\n",
+    "from bluecellulab.circuit.circuit_access import EmodelProperties\n",
+    "\n",
+    "\n",
+    "from bluecellulab.stimulus import StimulusFactory"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Loading the cell"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define the base directory\n",
+    "base_dir = Path(\"../1-singlecell/\")\n",
+    "\n",
+    "# Define the hoc and morphology files\n",
+    "hoc_file = base_dir / \"hoc\" / \"cADpyr_L2TPC.hoc\"\n",
+    "morph_file = base_dir / \"morphology\" / \"rr110330_C3_idA.asc\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "emodel_properties = EmodelProperties(threshold_current=0.03203125,\n",
+    "                                     holding_current=-0.11,\n",
+    "                                     AIS_scaler=1.11)\n",
+    "cell = Cell(hoc_file, morph_file, template_format=\"v6\", emodel_properties=emodel_properties)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Reset function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def reset_cell(hoc_file, morph_file, emodel_properties):\n",
+    "    \"\"\" Resets the cell for new stimulation\n",
+    "        Input:\n",
+    "            hoc_file: hoc file path\n",
+    "            morph_file: morphology file path\n",
+    "            emodel_properties: EmodelPropeties\n",
+    "        Output:\n",
+    "            cell: neuron\n",
+    "            sim: Simulation\n",
+    "    \"\"\"\n",
+    "    cell = Cell(hoc_file, morph_file, template_format=\"v6\", emodel_properties=emodel_properties)\n",
+    "    sim =Simulation()\n",
+    "    sim.add_cell(cell)\n",
+    "    return cell, sim"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Stimulations\n",
+    "### Stimulation function for each protocols\n",
+    "For protocols 1, 5 and 6, the stimulation parameters are based on [Beaulieu-Laroche 2021.](https://www.nature.com/articles/s41586-021-04072-3) to match the experimental protocols for an eventual comparison."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_stim(axs, time, voltage, stim_amp, duration, stim):\n",
+    "    \"\"\" Plot stimulation\n",
+    "        Input:\n",
+    "            axs: subplot axes\n",
+    "            time: int in ms\n",
+    "            voltage: voltage response in mV\n",
+    "            stim_amp: float in nA\n",
+    "            duration: int in ms\n",
+    "            stim: StimulusFactory\n",
+    "        Output:\n",
+    "            None\n",
+    "    \"\"\"\n",
+    "    # Plot voltage over time on the first subplot\n",
+    "    axs[0].plot(time, voltage, marker='.', label=f'{stim_amp}nA', markersize=2)\n",
+    "    axs[0].set_title('Time vs Voltage')\n",
+    "    axs[0].set_xlabel(\"Time [ms]\")\n",
+    "    axs[0].set_ylabel(\"Voltage [mV]\")\n",
+    "    axs[0].set_xlim(left=0)  # Make the plot start from 0 on the x-axis\n",
+    "    # axs[0].legend(bbox_to_anchor=(1, 0.5), loc='center left')\n",
+    "\n",
+    "    # Plot injected current over time on the second subplot\n",
+    "    axs[1].plot(stim.time, stim.current, label=f'{stim_amp:.3f}nA', drawstyle='steps-post', markersize=2, markeredgewidth=1)\n",
+    "    axs[1].set_title('Time vs Injected Current')\n",
+    "    axs[1].set_xlabel(\"Time [ms]\")\n",
+    "    axs[1].set_ylabel(\"Injected Current [nA]\")\n",
+    "    axs[1].set_xlim(left=0)  # Make the plot start from 0 on the x-axis\n",
+    "    # axs[1].legend(bbox_to_anchor=(1, 0.5), loc='center left')\n",
+    "\n",
+    "def step_current_stim(duration, stim_start, stim_delay, stim_amp, hoc_file, morph_file, emodel_properties, segment = 'soma', spike = False):\n",
+    "    \"\"\" generate a step current and plot it\n",
+    "        Input:\n",
+    "            duration: int\n",
+    "            stim_start: int in ms\n",
+    "            stim_delay: int in ms\n",
+    "            amp: float in nA\n",
+    "        Output:\n",
+    "            step: StimulusFactory.step\n",
+    "            time: int in ms\n",
+    "            voltage: voltage response in mV\n",
+    "    \"\"\"\n",
+    "    # reset cell\n",
+    "    cell, sim = reset_cell(hoc_file, morph_file, emodel_properties)\n",
+    "    # set stimulus type, here step\n",
+    "    stim_factory = StimulusFactory(dt=0.1)\n",
+    "    if segment == 'soma':\n",
+    "        cell.start_recording_spikes(None, location='soma', threshold=-10)\n",
+    "    step = stim_factory.step(pre_delay=stim_start, duration= duration, post_delay=stim_delay, amplitude=stim_amp)\n",
+    "    if segment != 'soma':\n",
+    "        neuron_section = cell.sections[segment]\n",
+    "        cell.add_voltage_recording(neuron_section, 0.5)\n",
+    "        cell.inject_current_waveform(t_content= step.time, i_content= step.current, section=neuron_section, segx=0.5)\n",
+    "    else:\n",
+    "        neuron_section = cell.soma\n",
+    "        cell.inject_current_waveform(t_content= step.time, i_content= step.current)\n",
+    "    #stimulation\n",
+    "    complete_duration = stim_start + duration + stim_delay\n",
+    "    sim.run(complete_duration, cvode=False)\n",
+    "    print(\"Done.\")\n",
+    "    \n",
+    "    time = cell.get_time()\n",
+    "    if segment != 'soma':\n",
+    "        voltage = cell.get_voltage_recording(neuron_section, 0.5)\n",
+    "        return step, time, voltage\n",
+    "    else:\n",
+    "        voltage = cell.get_soma_voltage()\n",
+    "        spikes = cell.get_recorded_spikes(location=\"soma\", threshold=-10)\n",
+    "        if spike:\n",
+    "            return step, time, voltage, spikes\n",
+    "        else:\n",
+    "            return step, time, voltage\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1. Step current injection for rheobase and negative step current \n",
+    "The rheobase is the minimum current amplitude that triggers an action potential. The negative step current is a protocol that is used to study the adaptation of the cell to a hyperpolarizing current. The stimulation parameters are based on [Beaulieu-Laroche 2021.](https://www.nature.com/articles/s41586-021-04072-3)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "duration = 500 # duration for 1 stimulation in [ms]\n",
+    "stim_start = 100 # delay before stimulation in [ms]\n",
+    "stim_delay = 100 # delay after stimulation in [ms]\n",
+    "rheobase = search_threshold_current(\n",
+    "        template_name = hoc_file,\n",
+    "        morphology_path = morph_file,\n",
+    "        template_format = \"v6\",\n",
+    "        emodel_properties = emodel_properties,\n",
+    "        hyp_level = 0,\n",
+    "        inj_start = stim_start,\n",
+    "        inj_stop = stim_start + duration,\n",
+    "        min_current = 0.001,\n",
+    "        max_current = 0.5,\n",
+    "        current_precision = 0.001\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "list_amp = [-.5, rheobase] # [nA]\n",
+    "a_section = 5\n",
+    "segment = f'apic[{a_section}]'\n",
+    "\n",
+    "steps = []\n",
+    "times = []\n",
+    "times_soma = []\n",
+    "voltages = []\n",
+    "voltages_soma = []\n",
+    "spikes = []\n",
+    "fig, axs = plt.subplots(2, 1, figsize=(8, 6), sharex = True)  # 2 rows, 1 column, wider figure\n",
+    "fig.suptitle(f\"Step current stimulation with spike detection\")\n",
+    "for amp in list_amp:\n",
+    "    step, time_soma, voltage_soma = step_current_stim(duration, stim_start, stim_delay, amp, hoc_file, morph_file, emodel_properties, segment = 'soma', spike=False)\n",
+    "    step, time, voltage, spike = step_current_stim(duration, stim_start, stim_delay, amp, hoc_file, morph_file, emodel_properties, spike=True)\n",
+    "    plot_stim(axs, time_soma, voltage_soma, amp, duration, step)\n",
+    "    # add spikes to the plot as dashed lines\n",
+    "    for spik in spike:\n",
+    "        axs[0].axvline(spik, c=\"r\", linestyle=\"--\")\n",
+    "    spikes.append(spike)\n",
+    "    steps.append(step)\n",
+    "    times.append(time)\n",
+    "    times_soma.append(time_soma)\n",
+    "    voltages.append(voltage)\n",
+    "    voltages_soma.append(voltage_soma)\n",
+    "plt.tight_layout()  # Adjusts subplot params so that subplots fit into the figure area\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2. Multiple negative step current injections\n",
+    "This multiple negative step current injections protocol is used to study the adaptation of the cell to a hyperpolarizing current."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "duration = 500 # duration for 1 stimulation in [ms]\n",
+    "stim_start = 100 # delay before stimulation in [ms]\n",
+    "stim_delay = 100 # delay after stimulation in [ms]\n",
+    "list_amp = np.linspace(rheobase-2, rheobase-.01, 20) # [nA]\n",
+    "\n",
+    "steps = []\n",
+    "times = []\n",
+    "voltages = []\n",
+    "# spikes = []\n",
+    "fig, axs = plt.subplots(2, 1, figsize=(8, 6), sharex = True)  # 2 rows, 1 column, wider figure\n",
+    "fig.suptitle(f'Multiple subthreshold step current stimulation')\n",
+    "for amp in list_amp:\n",
+    "    step, time, voltage = step_current_stim(duration, stim_start, stim_delay, amp, hoc_file, morph_file, emodel_properties)\n",
+    "    plot_stim(axs, time, voltage, amp, duration, step)\n",
+    "    # spikes.append(spike)\n",
+    "    steps.append(step)\n",
+    "    times.append(time)\n",
+    "    voltages.append(voltage)\n",
+    "plt.tight_layout()  # Adjusts subplot params so that subplots fit into the figure area\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3. IV Plot\n",
+    "With the previous data obtain in multiple negative step current injections, we can plot the IV curve."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def steady_state_voltage_stimend(stim_start, duration, voltage, t):\n",
+    "    \"\"\" steady_state_voltage_stimend\n",
+    "        Calculate the steady state voltage at the end of the stimulation\n",
+    "        Input:\n",
+    "            stim_start: int in ms\n",
+    "            duration: int in ms\n",
+    "            voltage: voltage response in mV\n",
+    "            t: int in ms\n",
+    "        Output:\n",
+    "            steady_state: float in mV\n",
+    "    \"\"\"\n",
+    "    stim_end = stim_start + duration\n",
+    "    begin_time = stim_end - 0.1 * duration\n",
+    "    end_time = stim_end\n",
+    "    steady_state = np.mean(voltage[np.where((t < end_time) & (t >= begin_time))])\n",
+    "    return steady_state\n",
+    "\n",
+    "def plot_IV(stim_start, duration, voltages, times, list_amp):\n",
+    "    \"\"\" plot_IV\n",
+    "        Plot the I-V curve\n",
+    "        Input:\n",
+    "            stim_start: int in ms\n",
+    "            duration: int in ms\n",
+    "            voltages: list of voltage responses in mV\n",
+    "            times: list of time in ms\n",
+    "            list_amp: list of injected current in nA\n",
+    "        Output:\n",
+    "            steady_states: list of steady state voltage in mV\n",
+    "    \"\"\"\n",
+    "    steady_states = []\n",
+    "    for voltage, t in zip(voltages, times):\n",
+    "        steady_state = steady_state_voltage_stimend(stim_start, duration, voltage, t)\n",
+    "        steady_states.append(steady_state)\n",
+    "    sns.set(font_scale=1.5)\n",
+    "    plt.plot(steady_states, list_amp, marker='o')\n",
+    "    plt.title(\"I-V curve\")\n",
+    "    plt.ylabel(\"Injected current [nA]\")\n",
+    "    plt.xlabel(\"Steady state voltage [mV]\")\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()\n",
+    "    return steady_states"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "steady_states = plot_IV(stim_start, duration, voltages, times, list_amp)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4. Multiple positive step current injections\n",
+    "This multiple positive step current injections protocol is used to study the adaptation of the cell to a depolarizing current."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "duration = 500 # duration for 1 stimulation in [ms]\n",
+    "stim_start = 100 # delay before stimulation in [ms]\n",
+    "stim_end = 100 # delay after stimulation in [ms]\n",
+    "list_amp = np.linspace(rheobase, 0.8, 20)\n",
+    "\n",
+    "steps = []\n",
+    "times = []\n",
+    "voltages = []\n",
+    "spikes  = []\n",
+    "fig, axs = plt.subplots(2, 1, figsize=(10, 8), sharex = True)  # 2 rows, 1 column, wider figure\n",
+    "fig.suptitle(f'Multiple positive step current stimulation')\n",
+    "for amp in list_amp:\n",
+    "    step, time, voltage, spike = step_current_stim(duration, stim_start, stim_end, amp, hoc_file, morph_file, emodel_properties, segment = 'soma', spike=True)\n",
+    "    plot_stim(axs, time, voltage, amp, duration, step)\n",
+    "    spikes.append(spike)\n",
+    "    steps.append(step)\n",
+    "    times.append(time)\n",
+    "    voltages.append(voltage)\n",
+    "plt.tight_layout()  # Adjusts subplot params so that subplots fit into the figure area\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 5. FI curve\n",
+    "With the previous data obtain in multiple positive step current injections, we can plot the FI curve."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_FI(list_amp, spikes):\n",
+    "    \"\"\" plot_FI\n",
+    "        Plot the F-I curve\n",
+    "        Input:\n",
+    "            list_amp: list of float\n",
+    "            spikes: list of all spikes for each amplitude\n",
+    "        Output:\n",
+    "            spike_count: list of spike count for each amplitude\n",
+    "    \"\"\"\n",
+    "    spike_count = [len(spike) for spike in spikes]\n",
+    "    plt.plot(list_amp, spike_count, marker='o')\n",
+    "    plt.title(\"F-I curve\")\n",
+    "    plt.xlabel(\"Current (nA)\")\n",
+    "    plt.ylabel(\"Spike count\")\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()\n",
+    "    return spike_count"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "spike_count = plot_FI(list_amp, spikes)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 6. Voltage Sag accross different distances\n",
+    "This protocol is used to study the voltage sag of the cell at different distances from the soma. The stimulation parameters are based on [Beaulieu-Laroche 2021.](https://www.nature.com/articles/s41586-021-04072-3)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_all_distance(all_section, cell):\n",
+    "    \"\"\" get_all_distance\n",
+    "        Calculate the distance to soma for all sections\n",
+    "        Input:\n",
+    "            all_section: list of cell.sections\n",
+    "            cell: neuron\n",
+    "        Output:\n",
+    "            all_distance: dictionary\n",
+    "    \"\"\"\n",
+    "    print('Getting all distances')\n",
+    "    all_distance = {}\n",
+    "    for section in all_section:\n",
+    "        distance_to_soma = neuron.h.distance(cell.soma(0.5), section)\n",
+    "        # store in dictionary: key = section name, value = distance to soma\n",
+    "        all_distance[section] = distance_to_soma\n",
+    "    return all_distance\n",
+    "\n",
+    "def sample_elements(dist_dict, min_dist):\n",
+    "    \"\"\" sample_elements\n",
+    "        Sample elements from dict\n",
+    "        Input:\n",
+    "            dist_dict: dict\n",
+    "            min_dist: int\n",
+    "        Output:\n",
+    "            sampled_distance: dict\n",
+    "    \"\"\"\n",
+    "    # sort dictionary by value\n",
+    "    sorted_dict = dict(sorted(dist_dict.items(), key=lambda item: item[1]))\n",
+    "    sampled_distance = {}\n",
+    "    # get first element of all_distance\n",
+    "    first_section = list(sorted_dict.keys())[0]\n",
+    "    sampled_distance[first_section] = sorted_dict[first_section]\n",
+    "    \n",
+    "    for section, distance in sorted_dict.items():\n",
+    "        if distance - sorted_dict[first_section] > min_dist:\n",
+    "            sampled_distance[section] = distance\n",
+    "            first_section = section\n",
+    "\n",
+    "    return sampled_distance\n",
+    "\n",
+    "def get_best_sample(all_distance, max_size):\n",
+    "    \"\"\" get_best_sample\n",
+    "        Get the best sample\n",
+    "        Input:\n",
+    "            all_distance: dict\n",
+    "            max_size: int\n",
+    "        Output:\n",
+    "            sampled_distance: list\n",
+    "    \"\"\"\n",
+    "    if len(all_distance) <= max_size:\n",
+    "        return list(all_distance.keys())\n",
+    "    else:\n",
+    "        # using sample_elements function find the min_dist which gives ~max_size with max 50 iterations\n",
+    "        i = 0\n",
+    "        sampled_distance = sample_elements(all_distance, i)\n",
+    "        \n",
+    "        while len(sampled_distance) > max_size:\n",
+    "            sampled_distance = sample_elements(all_distance, i)\n",
+    "            i += 1\n",
+    "        print(len(sampled_distance))\n",
+    "        print(i)\n",
+    "        # for i in range(0, 500, 1):\n",
+    "        #     sampled_distance = sample_elements(all_distance, i)\n",
+    "        #     if len(sampled_distance) <= max_size:\n",
+    "        #         print(len(sampled_distance))\n",
+    "        #         print(i)\n",
+    "        #         break\n",
+    "        return list(sampled_distance.keys())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The following part is if the cell have too many dendrites or a too skewed morphology. It ables to get a fix number of equidistant stimulation points."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Getting all distances\n",
+      "Getting all distances\n",
+      "25\n",
+      "5\n",
+      "25\n",
+      "12\n"
+     ]
+    }
+   ],
+   "source": [
+    "cell, sim = reset_cell(hoc_file, morph_file, emodel_properties)\n",
+    "number_of_sections = 25\n",
+    "\n",
+    "all_segments_dend = []\n",
+    "all_segments_apic = []\n",
+    "for section in cell.sections:\n",
+    "    for sec in cell.sections[section]:\n",
+    "        if \"dend\" in str(sec):\n",
+    "            all_segments_dend.append(sec)\n",
+    "        if \"apic\" in str(sec):\n",
+    "            all_segments_apic.append(sec)\n",
+    "\n",
+    "all_segments = all_segments_dend + all_segments_apic\n",
+    "\n",
+    "all_distances_dend = get_all_distance(all_segments_dend, cell)\n",
+    "all_distances_apic = get_all_distance(all_segments_apic, cell)\n",
+    "\n",
+    "sampled_all_section_dend = get_best_sample(all_distances_dend, number_of_sections)\n",
+    "sampled_all_section_apic = get_best_sample(all_distances_apic, number_of_sections)\n",
+    "\n",
+    "sampled_all_section = sampled_all_section_dend + sampled_all_section_apic\n",
+    "sampled_all_section = [str(sec) for sec in sampled_all_section]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's now apply a negative step current at multiple points of the dendrites."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11797310 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11797310\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde119340a0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde119340a0\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11797610 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11797610\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11797610 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11797610\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796830 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796830\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796890 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796890\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796830 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796830\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11797310 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11797310\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796980 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796980\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796950 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796950\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde117978e0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde117978e0\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11795180 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11795180\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde117975e0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde117975e0\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796890 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796890\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11795180 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11795180\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "exp(700.189) out of range, returning exp(700)\n",
+      "exp(700.527) out of range, returning exp(700)\n",
+      "exp(700.863) out of range, returning exp(700)\n",
+      "exp(701.198) out of range, returning exp(700)\n",
+      "No more errno warnings during this execution\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11794640 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11794640\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796950 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796950\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde117975e0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde117975e0\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796fb0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796fb0\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11795180 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11795180\n",
+      "                                                      ^\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Done.\n",
+      "Done.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ----------------------- V Sage simulation ------------------------------\n",
+    "duration = 500 # duration for 1 stimulation in [ms]\n",
+    "stim_start = 100 # delay before stimulation in [ms]\n",
+    "stim_end = 100 # delay after stimulation in [ms]\n",
+    "stim_amp = -.5 # [nA]\n",
+    "\n",
+    "v_sag_times = []\n",
+    "v_sag_voltages = []\n",
+    "v_sag_voltages_soma = []\n",
+    "all_distance = []\n",
+    "# getting all distances\n",
+    "for section in sampled_all_section:\n",
+    "    a_section = cell.sections[section.split('.')[1].split('(')[0]]\n",
+    "    record_pos = float(section.split('(')[1].split(')')[0])\n",
+    "    distance_to_soma = neuron.h.distance(cell.soma(0.5), a_section(record_pos))\n",
+    "    all_distance.append(distance_to_soma)\n",
+    "# getting traces and simulating\n",
+    "for section in sampled_all_section:\n",
+    "    cell, sim = reset_cell(hoc_file=hoc_file, morph_file=morph_file, emodel_properties=emodel_properties)\n",
+    "    a_section = cell.sections[section.split('.')[1].split('(')[0]]\n",
+    "    record_pos = float(section.split('(')[1].split(')')[0])\n",
+    "    cell.add_voltage_recording(a_section, record_pos)\n",
+    "    # set stimulus type, here step\n",
+    "    stim_factory = StimulusFactory(dt=0.1)\n",
+    "    step = stim_factory.step(pre_delay=stim_start, duration= duration, post_delay=stim_end, amplitude=stim_amp)\n",
+    "    cell.inject_current_waveform(t_content = step.time, i_content = step.current, section = a_section, segx = record_pos)\n",
+    "    complete_duration = stim_start + duration + stim_end\n",
+    "    sim.run(complete_duration, cvode=False)\n",
+    "    print(\"Done.\")\n",
+    "    time , voltage, voltage_soma = cell.get_time(), cell.get_voltage_recording(a_section, record_pos), cell.get_soma_voltage()\n",
+    "    v_sag_times.append(time)\n",
+    "    v_sag_voltages.append(voltage)\n",
+    "    v_sag_voltages_soma.append(voltage_soma)\n",
+    "#----------------------- V Sag data in dendrite ------------------------------\n",
+    "v_sags = []\n",
+    "steady_state_voltages = []\n",
+    "peak_currents = []\n",
+    "for voltage, t in zip(v_sag_voltages, v_sag_times):\n",
+    "    steady_state = steady_state_voltage_stimend(stim_start, duration, voltage, t)\n",
+    "    peak_current = min(voltage)\n",
+    "    v_sag = steady_state/ peak_current * 100\n",
+    "    v_sags.append(v_sag)\n",
+    "    steady_state_voltages.append(steady_state)\n",
+    "    peak_currents.append(peak_current)\n",
+    "\n",
+    "sampled_all_section = list(map(str, sampled_all_section))\n",
+    "# plot steady state voltage vs time and peak current vs time\n",
+    "df_sag = pd.DataFrame({'Steady state voltage': steady_state_voltages, 'Peak current': peak_currents, 'V sag': v_sags})\n",
+    "df_sag['Distance to soma'] = all_distance\n",
+    "df_sag['Section'] = sampled_all_section\n",
+    "    \n",
+    "dict_sag = {'time': v_sag_times, 'voltage': v_sag_voltages, 'distance': all_distance, 'section': sampled_all_section}\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_6012/24051413.py:3: UserWarning: Ignoring `palette` because no `hue` variable has been assigned.\n",
+      "  sns.scatterplot(data=df_sag, x='Distance to soma', y='V sag', palette='viridis')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 6))\n",
+    "plt.title('V sag vs Distance to soma')\n",
+    "sns.scatterplot(data=df_sag, x='Distance to soma', y='V sag', palette='viridis')\n",
+    "plt.xlabel('Distance to soma [um]')\n",
+    "plt.ylabel('V sag [%]')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7. EPSP accross different distances\n",
+    "This protocol is used to study the EPSP of the cell at different distances from the soma. It is an adaptation of example [4-epsp](../4-epsp/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def EPSP(cell, sim, a_section, record_pos):\n",
+    "    \"\"\" EPSP\n",
+    "        Calculate the EPSP ratio by stimulating for 1 section\n",
+    "        Input:\n",
+    "            cell: neuron\n",
+    "            sim: Simulation\n",
+    "            a_section: list of sections\n",
+    "            record_pos: float pos in section\n",
+    "        Output:\n",
+    "            cell: neuron\n",
+    "            sim: Simulation\n",
+    "            current_vector: neuron.h.Vector()\n",
+    "            dendrite_max_epsp_index: int\n",
+    "            soma_max_epsp_index: int\n",
+    "            dendrite_max_epsp: float\n",
+    "            soma_max_epsp: float\n",
+    "            dendrite_psp_amplitude: float in mV\n",
+    "            soma_psp_amplitude: float in mV\n",
+    "            dendrite_voltage_base: float in mV\n",
+    "            soma_voltage_base: float in mV\n",
+    "            \n",
+    "    \"\"\"\n",
+    "    # set recording\n",
+    "    cell.add_voltage_recording(a_section, record_pos)\n",
+    "    \n",
+    "    # synapse and current recording\n",
+    "    onset = 300.0\n",
+    "    tau = 10.0\n",
+    "    gmax = 0.0001\n",
+    "    e = 0.0\n",
+    "    synapse = cell.add_alpha_synapse(onset, tau, gmax, e, section=a_section)\n",
+    "    \n",
+    "    current_vector = neuron.h.Vector()\n",
+    "    _ = current_vector.record(synapse._ref_i)\n",
+    "    # simulation\n",
+    "    duration = 450\n",
+    "    dt = 0.1\n",
+    "    neuron_globals = NeuronGlobals.get_instance()\n",
+    "    neuron_globals.temperature = 34.0\n",
+    "    neuron_globals.v_init = -70.0\n",
+    "    sim.run(duration, cvode=False, dt=dt)\n",
+    "    \n",
+    "    voltage = cell.get_voltage_recording(a_section, record_pos)\n",
+    "    soma_voltage = cell.get_soma_voltage()\n",
+    "\n",
+    "    voltage_base_offset = 100\n",
+    "    voltage_base_start_index = int(voltage_base_offset / dt)\n",
+    "    protocol_start_index = int(onset / dt)\n",
+    "    protocol_end_index = int((duration) / dt)  # extending till end of simulation\n",
+    "\n",
+    "    dendrite_voltage_base = np.median(voltage[voltage_base_start_index:protocol_start_index])\n",
+    "    soma_voltage_base = np.median(soma_voltage[voltage_base_start_index:protocol_start_index])\n",
+    "\n",
+    "\n",
+    "\n",
+    "    dendrite_max_epsp = max(voltage[protocol_start_index:protocol_end_index])\n",
+    "    soma_max_epsp = max(soma_voltage[protocol_start_index:protocol_end_index])\n",
+    "    dendrite_psp_amplitude = dendrite_max_epsp - dendrite_voltage_base\n",
+    "    soma_psp_amplitude = soma_max_epsp - soma_voltage_base\n",
+    "\n",
+    "    dendrite_max_epsp_index = np.argmax(voltage[protocol_start_index:protocol_end_index]) + protocol_start_index\n",
+    "    soma_max_epsp_index = np.argmax(soma_voltage[protocol_start_index:protocol_end_index]) + protocol_start_index\n",
+    "\n",
+    "    return cell, sim, current_vector, dendrite_max_epsp_index, soma_max_epsp_index, dendrite_max_epsp, soma_max_epsp, dendrite_psp_amplitude, soma_psp_amplitude, dendrite_voltage_base, soma_voltage_base \n",
+    "\n",
+    "def EPSP_data(dendrite_psp_amplitude, soma_psp_amplitude, dendrite_max_epsp_index, soma_max_epsp_index, dt):\n",
+    "    \"\"\" EPSP_data\n",
+    "        Calculate the EPSP ratio by stimulating for all sections\n",
+    "        Input:\n",
+    "            dendrite_psp_amplitude: float\n",
+    "            soma_psp_amplitude: float\n",
+    "            dendrite_max_epsp_index: int\n",
+    "            soma_max_epsp_index: int\n",
+    "            dt: float\n",
+    "        Output:\n",
+    "            psp ratio: float\n",
+    "            delay: float in ms\n",
+    "    \"\"\"\n",
+    "    psp_amplitude_ratio = dendrite_psp_amplitude / soma_psp_amplitude\n",
+    "    delay = (soma_max_epsp_index - dendrite_max_epsp_index) * dt\n",
+    "\n",
+    "    return psp_amplitude_ratio, delay"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The following part is if the cell have too many dendrites or a too skewed morphology. It ables to get a fix number of equidistant stimulation points as it is done in the previous example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Getting all distances\n",
+      "Getting all distances\n",
+      "25\n",
+      "5\n",
+      "25\n",
+      "12\n"
+     ]
+    }
+   ],
+   "source": [
+    "all_segments_dend = []\n",
+    "all_segments_apic = []\n",
+    "for section in cell.sections:\n",
+    "    for sec in cell.sections[section]:\n",
+    "        if \"dend\" in str(sec):\n",
+    "            all_segments_dend.append(sec)\n",
+    "        if \"apic\" in str(sec):\n",
+    "            all_segments_apic.append(sec)\n",
+    "\n",
+    "all_segments = all_segments_dend + all_segments_apic\n",
+    "\n",
+    "all_distances_dend = get_all_distance(all_segments_dend, cell)\n",
+    "all_distances_apic = get_all_distance(all_segments_apic, cell)\n",
+    "\n",
+    "sampled_all_section_dend = get_best_sample(all_distances_dend, number_of_sections)\n",
+    "sampled_all_section_apic = get_best_sample(all_distances_apic, number_of_sections)\n",
+    "\n",
+    "sampled_all_section = sampled_all_section_dend + sampled_all_section_apic\n",
+    "sampled_all_section = [str(sec) for sec in sampled_all_section]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now apply the epsp protocol at multiple points of the dendrites."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796d40 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796d40\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796890 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796890\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796fb0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796fb0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde119343d0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde119343d0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796fe0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796fe0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796d40 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796d40\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11797e50 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11797e50\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796d40 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796d40\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11797e50 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11797e50\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796d40 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796d40\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796d40 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796d40\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796d40 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796d40\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11797e50 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11797e50\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde1174c280 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174c280\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde117a3a30 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde117a3a30\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796fb0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796fb0\n",
+      "                                                      ^\n",
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+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174c940\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796fb0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796fb0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde118869e0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde118869e0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796fe0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796fe0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde1174c940 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174c940\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11795180 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11795180\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde119343d0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde119343d0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796fe0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796fe0\n",
+      "                                                      ^\n",
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+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174eda0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde1174ecb0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174ecb0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11885750 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11885750\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde118869e0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde118869e0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11796d40 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11796d40\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde1174c280 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174c280\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde11797e50 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde11797e50\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde1174c940 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174c940\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde1174fcd0 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174fcd0\n",
+      "                                                      ^\n",
+      "NEURON: cADpyr_L2TPC_bluecellulab_0x7fde1174ec20 : a template cannot be redefined\n",
+      " near line 24\n",
+      " begintemplate cADpyr_L2TPC_bluecellulab_0x7fde1174ec20\n",
+      "                                                      ^\n"
+     ]
+    }
+   ],
+   "source": [
+    "all_dendrite_max_epsp_index = []\n",
+    "all_soma_max_epsp_index = []\n",
+    "all_dendrite_max_epsp = []\n",
+    "all_soma_max_epsp = []\n",
+    "all_dendrite_psp_amplitude = []\n",
+    "all_soma_psp_amplitude = []\n",
+    "all_dendrite_voltage_base = []\n",
+    "all_soma_voltage_base = []\n",
+    "\n",
+    "all_psp_amplitude_ratio = []\n",
+    "all_delay = []\n",
+    "all_time = []\n",
+    "all_voltage = []\n",
+    "all_soma_voltage = []\n",
+    "all_distance = []\n",
+    "\n",
+    "\n",
+    "for section in sampled_all_section:\n",
+    "    a_section = cell.sections[section.split('.')[1].split('(')[0]]\n",
+    "    record_pos = float(section.split('(')[1].split(')')[0])\n",
+    "    distance_to_soma = neuron.h.distance(cell.soma(0.5), a_section(record_pos))\n",
+    "    all_distance.append(distance_to_soma)\n",
+    "\n",
+    "for section in sampled_all_section:\n",
+    "    cell, sim = reset_cell(hoc_file=hoc_file, morph_file=morph_file, emodel_properties=emodel_properties)\n",
+    "    a_section = cell.sections[section.split('.')[1].split('(')[0]]\n",
+    "    record_pos = float(section.split('(')[1].split(')')[0])\n",
+    "    # gettting values\n",
+    "    cell, sim, current_vector, dendrite_max_epsp_index, soma_max_epsp_index, dendrite_max_epsp, soma_max_epsp, dendrite_psp_amplitude, soma_psp_amplitude, dendrite_voltage_base, soma_voltage_base = EPSP(cell, sim, a_section, record_pos)\n",
+    "    psp_amplitude_ratio, delay = EPSP_data(dendrite_psp_amplitude, soma_psp_amplitude, dendrite_max_epsp_index, soma_max_epsp_index, 0.1)\n",
+    "    time = cell.get_time()\n",
+    "    voltage = cell.get_voltage_recording(a_section, record_pos)\n",
+    "    soma_voltage = cell.get_soma_voltage()\n",
+    "\n",
+    "    # append all in corresponding list\n",
+    "    all_dendrite_max_epsp_index.append(dendrite_max_epsp_index)\n",
+    "    all_soma_max_epsp_index.append(soma_max_epsp_index)\n",
+    "    all_dendrite_max_epsp.append(dendrite_max_epsp)\n",
+    "    all_soma_max_epsp.append(soma_max_epsp)\n",
+    "    all_dendrite_psp_amplitude.append(dendrite_psp_amplitude)\n",
+    "    all_soma_psp_amplitude.append(soma_psp_amplitude)\n",
+    "    all_dendrite_voltage_base.append(dendrite_voltage_base)\n",
+    "    all_soma_voltage_base.append(soma_voltage_base)\n",
+    "    all_psp_amplitude_ratio.append(psp_amplitude_ratio)\n",
+    "    all_delay.append(delay)\n",
+    "    all_time.append(time)\n",
+    "    all_voltage.append(voltage)\n",
+    "    all_soma_voltage.append(soma_voltage)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_epsp = pd.DataFrame({'Dendrite max EPSP index': all_dendrite_max_epsp_index, 'Soma max EPSP index': all_soma_max_epsp_index, 'Dendrite max EPSP': all_dendrite_max_epsp, 'Soma max EPSP': all_soma_max_epsp, 'Dendrite PSP amplitude': all_dendrite_psp_amplitude, 'Soma PSP amplitude': all_soma_psp_amplitude, 'Dendrite voltage base': all_dendrite_voltage_base, 'Soma voltage base': all_soma_voltage_base, 'PSP amplitude ratio': all_psp_amplitude_ratio, 'Delay': all_delay, 'Time': all_time, 'Voltage': all_voltage, 'Soma voltage': all_soma_voltage, 'Distance to soma': all_distance})\n",
+    "df_epsp['Section'] = sampled_all_section\n",
+    "# set true if apical\n",
+    "df_epsp['Dendrite'] = df_epsp['Section'].str.contains('apic')\n",
+    "df_epsp['Dendrite'] = df_epsp['Dendrite'].apply(lambda x: 'Apical' if x == True else 'Basal')\n",
+    "\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "plt.title('PSP amplitude ratio vs Distance to soma')\n",
+    "sns.scatterplot(data=df_epsp, x='Distance to soma', y='PSP amplitude ratio', hue = 'Dendrite')\n",
+    "plt.xlabel('Distance to soma [um]')\n",
+    "plt.ylabel('PSP amplitude ratio')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/README.rst b/examples/README.rst
index b1c768a5..89d98706 100644
--- a/examples/README.rst
+++ b/examples/README.rst
@@ -23,3 +23,5 @@ BlueCelluLab's usage examples
      - Exploring the stimuli available at BlueCelluLab
    * - `stimuli-sequence.ipynb <6-stimuli-sequence/stimuli-sequence.ipynb>`_
      - Simulating a sequence of stimuli on a cell in parallel
+   * - `Multiple-protocols.ipynb <7-Extra-Simutlation/Multiple-protocols.ipynb>`_
+     - Simulating multiple protocols on a cell using previous examples