Lesson-1-What-is-Fear/What-is-Fear.ipynb

{
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    {
      "cell_type": "markdown",
      "id": "66d7c4d1",
      "metadata": {
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      "source": [
        "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/cyneuro/Fear-Lesson-Plans/blob/master/Lesson-1-What-is-Fear/What-is-Fear.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "N0uPS_8nwbuR",
      "metadata": {
        "id": "N0uPS_8nwbuR"
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      "source": [
        "# 1-Cell Amygdala Salivation Model\n",
        "## Before we get into 'what is fear', we will be talking about a famous example of conditioning with Pavlov's dogs. View the video below detailing the experiment.\n",
        "*   ### STEP 1. The neurons in amygdala of dogs (and humans) fire very low normally, e.g., 0.1-0.5 Hz. However, in the state of salivation, they fire at a high rate, e.g., 5 Hz.\n",
        "*   ### STEP 2. In the Pavlovian bell salivation conditioning paradigm (that is covered in the powerpoint and video), the neural pathway carrying the bell information to the amygdala strengthens with repeated conditioning. That is, the synaptic strength (weight) of the connection increases till the bell itself is capable of firing the amygdala(and causing salivation)\n",
        "*   ### STEP 3. You are given a model of an amygdala neuron, with knobs to change the following: (i) synaptic strength of the connection, (ii) delay from start when the bell begins, and (iii) the duration of the bell.\n",
        "## The model being used:\n",
        "\n",
        "![Bell-tone+Neuron.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "id": "pH7ZJ8S4xmMf",
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "id": "pH7ZJ8S4xmMf",
        "outputId": "78895c3f-5883-4036-a94c-99f27dfdc5bf"
      },
      "outputs": [
        {
          "data": {
            "image/jpeg": 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",
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"400\"\n",
              "            height=\"300\"\n",
              "            src=\"https://www.youtube.com/embed/jd7Jdug5SRc\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "            \n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7fcf171fb790>"
            ]
          },
          "execution_count": 1,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#@title Run cell to load video\n",
        "\n",
        "from IPython.display import YouTubeVideo\n",
        "YouTubeVideo('jd7Jdug5SRc')"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "v3jHwXi2yBu7",
      "metadata": {
        "id": "v3jHwXi2yBu7"
      },
      "source": [
        "---\n",
        "### CHALLENGE - Assume the baseline firing rate, i.e., in the absence of salivation is **0.5 Hz**. And that the firing rate when salivating is **5 Hz**. Your task is to manipulate the three knobs below to find the settings that results in a NO-SALIVATION state, and the SAILVATION state.  Report the values of the parameters bell strength, delay and duration, that you used to arrive at your results.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "id": "6656c992",
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6656c992",
        "outputId": "af59000a-afc5-43af-cc12-6189698b1003"
      },
      "outputs": [],
      "source": [
        "#@title download files\n",
        "import os\n",
        "RunningInCOLAB = 'google.colab' in str(get_ipython())  # checks to see if we are in google colab\n",
        "if RunningInCOLAB:                                     # installs packages and repo if in colab\n",
        "    !pip install ipywidgets &> /dev/null\n",
        "    !pip install neuron &> /dev/null\n",
        "    !pip install bmtk &> /dev/null\n",
        "\n",
        "    !git clone https://github.com/cyneuro/Fear-Lesson-Plans &> /dev/null\n",
        "    %cd Fear-Lesson-Plans/Lesson-1-What-is-Fear/\n",
        "\n",
        "if(os.path.exists('x86_64')==False):\n",
        "    os.system('nrnivmodl modfiles')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "xyK-gwdD1E5H",
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "a1bf18075b3247af9a2dffe5798971cd",
            "90ae86969778452597e1b3411a6f8ed7",
            "1123f9953633489c8f9b1a1ba6aa9e22",
            "0d91087f016e468f9dbe77b29231d87f",
            "525f8f811f0b4e9cae90715086608e68",
            "0c96b2e6a70c4bf4b058a2c0f40b9c0d",
            "5c7e1daaa77d490aad5a139b5221bfa9",
            "a87311d7d06a48f19f738ce779833bba",
            "95e7888b94a44aef931ce9f8ecbf54fb",
            "13503a9ff0554aa9b5ad022eebb7f8ad"
          ]
        },
        "id": "xyK-gwdD1E5H",
        "outputId": "223c0522-e2e5-481b-ff6d-a3340a81063c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Running Model!\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2eb5cf43b8aa46aea4d5a73030639d99",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "HBox(children=(VBox(children=(FloatSlider(value=2.5, description='Input Strength:', min=2.5, step=1.0, style=S…"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Number of spikes: 3\n",
            "Firing rate: 0.667 Hz\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title run model\n",
        "from neuron import h\n",
        "from neuron.units import ms, mV\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from bmtk.utils.reports.spike_trains import PoissonSpikeGenerator\n",
        "import ipywidgets as widgets\n",
        "from IPython.display import display, clear_output\n",
        "\n",
        "seed = 1234\n",
        "rng = np.random.default_rng(seed)\n",
        "np.random.seed(seed)\n",
        "\n",
        "def generate_poisson_spikes(syn_number, start_time, end_time, hz):\n",
        "    spikes = PoissonSpikeGenerator(population='spikes')\n",
        "    spikes.add(node_ids=range(syn_number), firing_rate=hz, times=(start_time, end_time))\n",
        "    return spikes\n",
        "\n",
        "def run_model(b):\n",
        "    clear_output()\n",
        "    print(\"Running Model!\")\n",
        "    PN_weight_val = PN_weight_slider.value\n",
        "    display(controls_box)\n",
        "    model(PN_weight=PN_weight_val, PV_weight=1)\n",
        "\n",
        "def model(PN_weight=None, PV_weight=None):\n",
        "    seed = 1234\n",
        "    rng = np.random.default_rng(seed)\n",
        "    np.random.seed(seed)\n",
        "    h.load_file('stdrun.hoc')\n",
        "    h.load_file('PN_cells.hoc')  # reads in template\n",
        "    cell = h.PN_C()  # cell from template file\n",
        "\n",
        "    h.dt = 0.1  # time step (resolution) of the simulation in ms\n",
        "    h.tstop = 5000  # how long to run the simulation in ms\n",
        "    h.v_init = -65  # initial membrane potential in mV\n",
        "\n",
        "    exc_syn_num = 23  # from amygdala paper\n",
        "    inh_syn_num = 43  # from amygdala paper\n",
        "\n",
        "    PN_spikes = generate_poisson_spikes(exc_syn_num, start_time=0.5, end_time=5, hz=10)\n",
        "    PV_spikes = generate_poisson_spikes(inh_syn_num, start_time=0.5, end_time=5, hz=5)\n",
        "\n",
        "    for i in range(exc_syn_num):  # for every excitatory synapse(PN2PN):\n",
        "        conn_exc = h.AMPA_NMDA_STP(cell.dend[0](0.9))  # create syn on apical dendrite\n",
        "        conn_exc.e = 0\n",
        "        spikes_exc = PN_spikes.get_times(node_id=i)  # original version of creating spike trains\n",
        "        v_spikes_exc = h.Vector(spikes_exc)  # make vector based on the spike train\n",
        "        vec_stim_exc = h.VecStim()  # have vecstim play it\n",
        "        vec_stim_exc.play(v_spikes_exc)\n",
        "        nc_exc = h.NetCon(vec_stim_exc, conn_exc, 1, 1, PN_weight)\n",
        "\n",
        "    for i in range(inh_syn_num):\n",
        "        conn_inh = h.Exp2Syn(cell.dend[0](0.5))\n",
        "        conn_inh.e = -75\n",
        "        spikes_inh = PV_spikes.get_times(node_id=i)\n",
        "        v_spikes_inh = h.Vector(spikes_inh)\n",
        "        vec_stim_inh = h.VecStim()\n",
        "        vec_stim_inh.play(v_spikes_inh)\n",
        "        nc_exc2 = h.NetCon(vec_stim_inh, conn_inh, 1, 1, PV_weight)\n",
        "\n",
        "    # Setup recording of spike times\n",
        "    spike_times = h.Vector()\n",
        "    spike_detector = h.NetCon(cell.soma[0](0.5)._ref_v, None, sec=cell.soma[0])\n",
        "    # Set the voltage threshold for spike detection\n",
        "    spike_detector.threshold = -15  # Set the threshold to -15 mV\n",
        "    spike_detector.record(spike_times)\n",
        "\n",
        "    t = h.Vector()  # Vectors are used to record data in the simulation\n",
        "    Soma_v = h.Vector()\n",
        "\n",
        "    t.record(h._ref_t)  # dereferences and records data\n",
        "    Soma_v.record(cell.soma[0](0.5)._ref_v)\n",
        "\n",
        "    h.finitialize(h.v_init * mV)  # runs sims\n",
        "    h.continuerun(h.tstop * ms)\n",
        "\n",
        "    fig, ax = plt.subplots(1, 1, sharex=True, figsize=(12, 8))\n",
        "\n",
        "    # Convert spike times to a NumPy array\n",
        "    try:\n",
        "        spike_times_array = np.array(spike_times)\n",
        "    except:\n",
        "        spike_times_array = np.zeros(1)\n",
        "\n",
        "    # Calculate number of spikes\n",
        "    num_spikes = len(spike_times_array)\n",
        "\n",
        "    # Calculate firing rate (spikes per second)\n",
        "    if h.tstop > 0:\n",
        "        firing_rate = round(num_spikes / (4500 / 1000),3)  # Convert to seconds\n",
        "    else:\n",
        "        firing_rate = 0.0\n",
        "\n",
        "    # Print results\n",
        "    print(\"Number of spikes:\", num_spikes)\n",
        "    print(\"Firing rate:\", firing_rate, \"Hz\")\n",
        "\n",
        "    ax.plot(t, Soma_v)\n",
        "    plt.show()\n",
        "\n",
        "# Create sliders\n",
        "PN_weight_slider = widgets.FloatSlider(value=2.5, min=2.5, max=100.0, step=1, description='Input Strength:',style=dict(description_width='initial'))\n",
        "\n",
        "# Create Run button\n",
        "run_button = widgets.Button(description=\"Run\")\n",
        "run_button.on_click(run_model)\n",
        "\n",
        "# Arrange widgets using HBox and VBox\n",
        "slider_box = widgets.VBox([PN_weight_slider])\n",
        "controls_box = widgets.HBox([slider_box, run_button])\n",
        "\n",
        "# Display widgets\n",
        "display(controls_box)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "kbPYphAenFnB",
      "metadata": {
        "id": "kbPYphAenFnB"
      },
      "source": [
        "# 1-Cell Amygdala Fear Model\n",
        "## This Colab illustrates 'what is fear?'. In mammals, a region of the brain called the 'amygdala' has been found to be the fear center. For instance, you have two almond sized amygdalas in the two hemispheres of your brain.\n",
        "*   ### STEP 1. The neurons in amygdala of rodents (and humans) fire very low normally, e.g., 0.1-0.5 Hz. However, in the state of fear, they fire at a very high rate, e.g., 7 Hz.\n",
        "*   ### STEP 2. In the Pavlovian tone fear conditioning paradigm (that is covered in the powerpoint), the neural pathway carrying the tone information to the amygdala strengthens with repeated conditioning. That is, the synaptic strength (weight) of the connection increases till the tone itself is capable of firing the amygdala.\n",
        "*   ### STEP 3. You are given a model of an amygdala neuron, with knobs to change the following: (i) synaptic strength of the connection, (ii) delay from start when the tone begins, and (iii) the duration of the tone.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "e0fZeHydbUa9",
      "metadata": {
        "id": "e0fZeHydbUa9"
      },
      "source": [
        "# The model being used:\n",
        "\n",
        "![thumbnail_Tone+neuron.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "RLS3kQ4pcPDl",
      "metadata": {
        "id": "RLS3kQ4pcPDl"
      },
      "source": [
        "---\n",
        "\n",
        "### CHALLENGE - Assume the baseline firing rate, i.e., in the absence of fear is **0.5 Hz**. And that the firing rate when fearful is **7 Hz**. Your task is to manipulate the three knobs below to find the settings that results in a NO-FEAR state, and the FEAR state.  Report the values of the parameters tone strength, delay and duration, that you used to arrive at your results."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "c7943016",
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "7140fb75d9184a11a02edef3d30cfc0e",
            "ff1368c53db4437b8879a0cc855b1c22",
            "0f5aaf060a8443d39889b625ba605116",
            "e23ad47685ed4f6391cab53e3e262960",
            "c19e58457da74916ba31ca6f51ed0b40",
            "355382affeec48b4a062f0da025dd477",
            "89cb271db16e45c8a5f88ed9895e4bf0",
            "9a29f43f373e459898856f70759bea0e",
            "51e9cde183664e36a64341c1667feb56",
            "8ef2fa80faf74d87bad4938812e74417"
          ]
        },
        "id": "c7943016",
        "outputId": "56a25237-e730-418d-9c42-4bb2fa450935",
        "pycharm": {
          "name": "#%%\n"
        }
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Running Model!\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2eb5cf43b8aa46aea4d5a73030639d99",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "HBox(children=(VBox(children=(FloatSlider(value=33.5, description='Input Strength:', min=2.5, step=1.0, style=…"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Number of spikes: 33\n",
            "Firing rate: 7.333 Hz\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title run model\n",
        "from neuron import h\n",
        "from neuron.units import ms, mV\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from bmtk.utils.reports.spike_trains import PoissonSpikeGenerator\n",
        "import ipywidgets as widgets\n",
        "from IPython.display import display, clear_output\n",
        "\n",
        "seed = 1234\n",
        "rng = np.random.default_rng(seed)\n",
        "np.random.seed(seed)\n",
        "\n",
        "def generate_poisson_spikes(syn_number, start_time, end_time, hz):\n",
        "    spikes = PoissonSpikeGenerator(population='spikes')\n",
        "    spikes.add(node_ids=range(syn_number), firing_rate=hz, times=(start_time, end_time))\n",
        "    return spikes\n",
        "\n",
        "def run_model(b):\n",
        "    clear_output()\n",
        "    print(\"Running Model!\")\n",
        "    PN_weight_val = PN_weight_slider.value\n",
        "    display(controls_box)\n",
        "    model(PN_weight=PN_weight_val, PV_weight=1)\n",
        "\n",
        "def model(PN_weight=None, PV_weight=None):\n",
        "    seed = 1234\n",
        "    rng = np.random.default_rng(seed)\n",
        "    np.random.seed(seed)\n",
        "    h.load_file('stdrun.hoc')\n",
        "    h.load_file('PN_cells.hoc')  # reads in template\n",
        "    cell = h.PN_C()  # cell from template file\n",
        "\n",
        "    h.dt = 0.1  # time step (resolution) of the simulation in ms\n",
        "    h.tstop = 5000  # how long to run the simulation in ms\n",
        "    h.v_init = -65  # initial membrane potential in mV\n",
        "\n",
        "    exc_syn_num = 23  # from amygdala paper\n",
        "    inh_syn_num = 43  # from amygdala paper\n",
        "\n",
        "    PN_spikes = generate_poisson_spikes(exc_syn_num, start_time=0.5, end_time=5, hz=10)\n",
        "    PV_spikes = generate_poisson_spikes(inh_syn_num, start_time=0.5, end_time=5, hz=5)\n",
        "\n",
        "    for i in range(exc_syn_num):  # for every excitatory synapse(PN2PN):\n",
        "        conn_exc = h.AMPA_NMDA_STP(cell.dend[0](0.9))  # create syn on apical dendrite\n",
        "        conn_exc.e = 0\n",
        "        spikes_exc = PN_spikes.get_times(node_id=i)  # original version of creating spike trains\n",
        "        v_spikes_exc = h.Vector(spikes_exc)  # make vector based on the spike train\n",
        "        vec_stim_exc = h.VecStim()  # have vecstim play it\n",
        "        vec_stim_exc.play(v_spikes_exc)\n",
        "        nc_exc = h.NetCon(vec_stim_exc, conn_exc, 1, 1, PN_weight)\n",
        "\n",
        "    for i in range(inh_syn_num):\n",
        "        conn_inh = h.Exp2Syn(cell.dend[0](0.5))\n",
        "        conn_inh.e = -75\n",
        "        spikes_inh = PV_spikes.get_times(node_id=i)\n",
        "        v_spikes_inh = h.Vector(spikes_inh)\n",
        "        vec_stim_inh = h.VecStim()\n",
        "        vec_stim_inh.play(v_spikes_inh)\n",
        "        nc_exc2 = h.NetCon(vec_stim_inh, conn_inh, 1, 1, PV_weight)\n",
        "\n",
        "    # Setup recording of spike times\n",
        "    spike_times = h.Vector()\n",
        "    spike_detector = h.NetCon(cell.soma[0](0.5)._ref_v, None, sec=cell.soma[0])\n",
        "    # Set the voltage threshold for spike detection\n",
        "    spike_detector.threshold = -15  # Set the threshold to -15 mV\n",
        "    spike_detector.record(spike_times)\n",
        "\n",
        "    t = h.Vector()  # Vectors are used to record data in the simulation\n",
        "    Soma_v = h.Vector()\n",
        "\n",
        "    t.record(h._ref_t)  # dereferences and records data\n",
        "    Soma_v.record(cell.soma[0](0.5)._ref_v)\n",
        "\n",
        "    h.finitialize(h.v_init * mV)  # runs sims\n",
        "    h.continuerun(h.tstop * ms)\n",
        "\n",
        "    fig, ax = plt.subplots(1, 1, sharex=True, figsize=(12, 8))\n",
        "\n",
        "    # Convert spike times to a NumPy array\n",
        "    try:\n",
        "        spike_times_array = np.array(spike_times)\n",
        "    except:\n",
        "        spike_times_array = np.zeros(1)\n",
        "\n",
        "    # Calculate number of spikes\n",
        "    num_spikes = len(spike_times_array)\n",
        "\n",
        "    # Calculate firing rate (spikes per second)\n",
        "    if h.tstop > 0:\n",
        "        firing_rate =  round(num_spikes / (4500 / 1000),3)\n",
        "    else:\n",
        "        firing_rate = 0.0\n",
        "\n",
        "    # Print results\n",
        "    print(\"Number of spikes:\", num_spikes)\n",
        "    print(\"Firing rate:\", firing_rate, \"Hz\")\n",
        "\n",
        "    ax.plot(t, Soma_v)\n",
        "    plt.show()\n",
        "\n",
        "# Create sliders\n",
        "PN_weight_slider = widgets.FloatSlider(value=2.5, min=2.5, max=100.0, step=1, description='Input Strength:',style=dict(description_width='initial'))\n",
        "\n",
        "# Create Run button\n",
        "run_button = widgets.Button(description=\"Run\")\n",
        "run_button.on_click(run_model)\n",
        "\n",
        "# Arrange widgets using HBox and VBox\n",
        "slider_box = widgets.VBox([PN_weight_slider])\n",
        "controls_box = widgets.HBox([slider_box, run_button])\n",
        "\n",
        "# Display widgets\n",
        "display(controls_box)\n"
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