Lesson-2-How-do-Tone-Shock-pair/Intro-to-Tone-Shock.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "id": "0345fdc9",
      "metadata": {},
      "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-2-How-do-Tone-Shock-pair/Intro-to-Tone-Shock.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "evdVr4AmwXOk",
      "metadata": {
        "id": "evdVr4AmwXOk"
      },
      "source": [
        "# What is Tone and Shock\n",
        "## Below is a more in depth 1-cell model of the amygdala. Here we will see how the timing of the tone and shock is imperative for us to learn. Remember, the tone is what is learned like the bell with Pavlov while the shock is equivalent to the food. For a refresher on the Pavlov experiment and how it works, watch the video below."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "id": "pH7ZJ8S4xmMf",
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 322
        },
        "id": "pH7ZJ8S4xmMf",
        "outputId": "0af0b2a2-0a81-4b04-84e0-630d5720826d"
      },
      "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 0x7fde4bad8b80>"
            ]
          },
          "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": "Lfhb3O8NPzcR",
      "metadata": {
        "id": "Lfhb3O8NPzcR",
        "pycharm": {
          "name": "#%% md\n"
        }
      },
      "source": [
        "## The model is a PN cell with tone and shock inputs as shown below:"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "EYYAZ1KFfCzv",
      "metadata": {
        "id": "EYYAZ1KFfCzv"
      },
      "source": [
        "![tone+shock neuron.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAN8AAAC6CAYAAAAuwJjFAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAACqWSURBVHhe7Z0JfExX//+/RPY9sggSiUjEEhRFlYdWF/Wrlq7a/nh+1VX30qcP+jwP1UX5o60WraIttbRVPKhaaittUQSxJMgmksgm+57I/37O3Du5E5NkJpm5c2fmvL3uy71n7jJzcz/3+z3fc873tKkTIA6Hozhtxf85HI7CcMvHMQtllTWUX1JFBSWVwnqtWFbLtj3dHMnT1ZGVAaz7ezuTv5eLWGIfcPFxTEJWfjldySml3KJKtg7xGYtD2zbUwdeVgrD4uFB4B0/xE9uEi4/TYjLyyuhyZjElXytukdiaw9nRQRCgB4UFetikELn4OEZRWV1LZ5Lz6fyVgkYFB8vl6+FE7T3rXUlYNZRLFJdXU3FZNVvHebIKKiivqILSBUHrA0Ls3tmbbonwIzfndmKpdcPFxzEISXRxKflsXQ7qcOFBntQt2FNHYC0lVxBh8rUSSswsYvVGORBxZCcvGhjpr1NvtEa4+DhNUnujjmIv5wmiK9ARHSxRt46eFCEIrmN7N7HU9BQI4jt/pZAuZxTdZGl7dfGhQd0DhO9inUF7Lj5OoyBwsv/MNSYACYguJsyHYsL9FH3o8RKITyukU0nXte4qgAs6tGeA8CLwEkssA2RUVVVFzs7OYknzcPFxbgIP+vFLeRSbmCeWaEQ3oFt7Zm3g+lmShKuF7Puh3igRGuBOI/t0sEh98MiRI/Tzzz9TmzZtaM6cOWJp83DxcXSAldt5Ml3H2iHQMbi7v6oCHY29IEb1C2ZCNCc3btygtm3b0tmzZ+m9996jpKQkunTpEhUWFtKPP/5IjzzyiLhn03DxcbSkZJXQAcHNlOp2EBusSYiZH+bWkFVQTn+ez2H/SwztESi4xb7ilumoqamh/Px8unDhAn388cd08OBBKigoYC6nRHBwMGVkZIhbTcPFx2Ecv5RLJwRLIoE61PBeQeRkJcEMfd8fLw5TucixsbH0+++/07Fjx2j9+vVMiHAz9cln9uzZNGvWLHGrcbj47By4b3tjMyk5q1gsMZ/lMDcNLTfaGMcODmnVC+TEiRP01Vdf0cWLF5kAYekMITMzkzp06CBu6YeLz46B8HYL9bu0nFK27STUme7p35E6+pmv6cDcoK66O7a+ztoeAhxkuACrq6upoqKCrly5wqwXrF1paSkVF9e/nAwB9T7U/5qCi89OaSg8NFjfL1gJa2+4BlXVN2jbsTTWYwYYIkDI4Pz583TmzBnaunUrbdiwQfyk5Rw6dIiGDRsmbt0MF58dohFeRgPhdbYJ4UnUC7CSbbf3cm5UgKjHbdy4kZKTk+mXX35hls4U9O7dm+Li4sStm+His0MgPNSPgC0KT0KfAMfdFkptqI41FcTHx9M777zD/keE0tD6nDEsXbqUpkyZIm7pYh2hLI7J+OtiLqUKwkMM0MuGhQdg5WDt/AXR4ffm5pfRD7tjmTv4+OOPU79+/WjLli3M3TSl8FxcXMjJyYnCwsIoJyeHtQvqo0WWD2HWhx56iLZt2yaWNM24ceNo8+bN4hbHUiRmFtO+05lsHQ/mg0NCycfdiW3bMrCAn363m87EHqP400fo9J97qbpat8N2a5CaHBwcHGjs2LGsre/OO+9kQZeioiLy8tLf9Y2Lz07ILiin7ceusvoeGD2gk6obz03FyZMn6YcffqA/jxyl2FNnqLjwuviJaYDQ3N3daciQIUxskZGR1K1bN2b5msNkdb5Vq1bRM888w9YRokVDI0cd4M3/4+EUKhdHBQyJDqDeYdbXjmcMcPVmzpxJy5cvZ+vo+mUKYN1qa2spIiKCnnrqKQoNDaWRI0eybWPhdT474Eh8jlZ4PUJ9bF54AAGVTp06sfqXKYTn5ubGrNuYMWNYM8T+/fvppZdeYganJcIDiopv3759NHr0aOYjS0uPHj1o3rx5VFamO4IZlhSfe3h4sErrrl27yM/PT3vcpEmTbjpGAvsOHDhQuy+GeeAmpaSkiHvYD1dzSuliuubhQ/0OVs9eePHFF2nQoEFMgC3B09OTHB0d6bHHHqMvvviCFi9ezAI0CNaEhIRQUFCQuGcLgdtpClauXAn3lS2C2ymW1jNjxgzt5/qW/v3715WWlop7159P8J3rBgwYcNP+WARfuy47O1s8oq6uurq6burUqXr3xdJwf1unsrq27rv9iXVf7UxgS1Z+mfiJ/SC8iOuEepje56GxJTo6uu7555+ve//99+tSU1PZecrLy9n/pkQRy3f48GGaO3cuW4+JiWFDMYRrsy48iA4BVIznz5/P1uVggCL616E9Bo2fOAY+NsD23r172TpYvXo1LVq0iK1L++M6O3fuZGXYFm4qW7cHjgruZoXgbiLM3q+rHwX6tD7Fg7Vxzz330F133dVoxFGiXbt2rGng22+/pWXLlrGhQniGUKcDLbWeTcIkaAIas3ywRoLAWDms2NGjR8VPNCQlJdX5+vqyz+WWqSlLqu8z+XX0WcTGPrNVMvLK6lbsvMiWjYdS6mpqb4if2B8XLlyou/XWW+uEKoj2uWm4tHVwqPvHP/5RV1JSIh5lfsxu+dAscfr0abYO/zk8PJytSyBUC98aoFMruvg0R1RUlLhG2nPLrwMLFxgYqK3z4bqGNovYCkcTcsQ1oqE9Ay0++tySCG4kCdUacnVt3PLfqK2l7du3s36dSmF28WFohdQjvHv37qxNRA7Mfd++fcWtliO/jr2DXCfXiyqZuxkW5EHBfvbnbiLCiaoMxHTvvfeyCGVlpaabWWNgkCz6dmL4kBKYXXxyy5aQkMCskpzmLGNLwFtOqu81XAS3ggICbDfiV1Vzg2KTrhOU5+DQhqV/sAY+Wbufrma1vosXYgSffvopvfXWW/Tyyy/Tgw8+SLt372ZiRPtcc+zctYvlY8GzYm7MLj65ZdPnVjZnGQ1FLnIEdLDYI7GJ17VtetEhPuRhJf02j8SlCOLLF7eMAx2jd+zYQe+++y7rYfLGG2/QN998wxIbGUtOdjYL0GEcn7lRRHzoXgbwVkIP73PnzrHttLQ0ev3111leDIDIJxozWwKiUVLimobXAfgDoY3RlnvewOrFp2msh6tzOxoY2Z6t2xoY7ArLhL8verFMnTqVnn32Wfa3RTQcwKMylrZtHdj/p8+cYZ2vy8vr88KYA7OLD6BBXN6kgHFOCIQgjCsFQiZPntxqYXzwwQfaZgj5dbCgMR+N77bMpfRCunGjjtX1+oRZPsWfqYEY0Gy1du1a9jyheoGGb9TT4EE1Bv7+QMqpCQ8JS5cuXWj48OE0ePBg+vszL9Ad9z9Bz7w1jx77+0t0//33M8NhTswivobdbfAjNm3axMz5gAEDxFINI0aMYJ2uV65cKZYYR69evcQ1jfXbs2cPa6dp7Dq2avnQYRpZpYEmpbo3W7cWikoqyMvj5rY0WDnU39FHE4KAS/nCCy+wehk8nIYxBCmiiTY79IjC6AL0cnnzzTeZlVyyZAl99913LADz119/0YoVK5h7uuTThfTs1Dl0+93jaeBdT1C3qB4sBmFOTNaxmmNZkq4V08G4a2y9VxdfGhRlHYEWiWFPL6INH02mzkE+bBtj7H777TdKTU1lnSekdHyICUBwXbt2ZdFL/A8r5uvry1I24HFGUxTcTnToAN7e3uw4lMEQYB/JGso5l5pPxy7msnUl7iEXn42w9UgaXS+uZFbvkWFhQp1PU3+xFm7/vwW08JV7qIO/F61bt45VGyAWpGFAP12s33333WxUAaoQEBw8HQTpcnNzyd/fnwX0WmOt4D1sZKM/asmpXVt6fES4WV13Lj4bIKewgn4+dpWthwZ60J19m05Zp0aGTppPi6eOpeRLZ5mw0DCO5gFEyhENR5kSnMCkMMmaAOCwXoFmnQNCkYALx7wki/lYQM9Q66rrSSDTWEzPSDZIG1Fp1NmkJiqlhAd6hmjcXiC/r+ZAR3zvfL6NKquMC9EqdQxQ+7UsBWaGBWjTw7TK1gjutbNTO+ZWWhK46x3EHkHpuWXMBTUXOuI7eOIS5eQbp3aljgFqv5YlwEyuFVW1hPhB1w4eYqn9grrhAw88wAIqiHg3NuazKTDJJ+4nlsuZRWKpYUybNs3ga3O308qRUgACTFRp6zQckC0NlG6JyBoD879LgRb5/TU1OuLzcnelolLjWvWVOgao/VpKg+ic5HL6eTqTt5VmIoOHEeDbvNVGdoNRo0bpdJZAWx/KkU/FVEB4CFwBRJALS02X6UyOrvg8XFhjpzEodQxQ+7WU5lp+ubZHi7nnpDMnUn2vKdDYjr6bAD1bpAHZaP+bMWMGa1A3JWGB7uy+YoFrbw6422nFZMoeCltPAyjvgI+uZVLPJnSo//DDDxvtIYVMB3fccYfWRV24cKH4ST3oY/zaa69pXVksEx+9n079+Sv7XH6fG+7b2DnlSPmIsKxZs0YsbSA+mH5jgwxKHQPUfi2lSb8uPBTCqxkJcOF22jLyUStISSJ/iBsDDfUIvhw4cIBtw0XFUCP5JCgYZYMmjc8++0ws0fDbbwfp4/9MoSMHttO1gnKNi69nX5wT3dYw34M+cAyuCWCxH374YbYOdMQH029seF2pY4Dar6UkJRU1Ql0Ec5KjfmLdgRYMJeoc1HQ6Q/RmQT5YgAcenfVhdfRlvpODETXojoapm9EFDXz//ffsf0RGpVE1SHJ79OhR5spiZISUu2XVwplUkH+dufiff/65dt/Nmzdr94Vl1Qc6gqOjP46B8DBSQj5qh7udVkqW8DBIdZIgHzMk91EhGPmCfp6SiCDC6dOns219lgcPPEZA4IHHIO2nn36alUMwECxcSIySAKg3ogM2QFpASei1gkBzM9MoNbOAzWQEkLtTGiaHfTFgQDpWDhIw4VroV4p9Gg6X425nI7T0OKXIkNVDOra33sksjWXixImUnZ3NRq7IRYjRC8jvagzp6enasaToziZHyhNUU1NN2YL44i+nauucUs+bpoDL++WXX7J19EnVlz1B1+10FFytaiPdOoWOAWq/lpLkizOvoleLq5N1daJuLRiZgIS4ECEG0gK4lvI0kqamuMy45gZYXQx9Aki0q2+yTe52WiGo/BcJD0Mbwef082xd2962g3H03Jy1FDbmPzrLfS8vEfeoB2UN95v0r29p7Y6/xD1aBnK3SEOJjAEiHD9+vLhlPEgnL1lPZDqQIyVRcnR0osCOIYRJvqQhCFLOoebA4G6p7oiR9g0ts474Ogf60NVs45LYKHUMUPu1lCK/uD4LFyZ81AcSEh0503Qaxo+/20s//xZL9w0Jodg1z+osF5KzxL3qQVnD/R4f1Y1OXUikaQt/EvcyD6ib9enTh1kRCdTZpETLCIJgbJ8xoL4mTdu8YMECbb1RHqHs3qMnhYRHkV9AMPW/dTArQ74YaV98h0cffVSvZcPAXtQ5ASwzBvLK4ZbPCrleUi8+bzf9lg8JiSZM/5ot+kS49PuDVFxSRHNfGkl3DAgTS41naJ8Qmvl/Q6lHqCfN/Oy/Yql5wNg+WDqpzUyehkQeMDEUWM63336brUMcSCeB80LEUlTz8yVLycnZlXX4fnLyK2xf1DGlffEdpECMPjC5ipRCBU0k8sCQbp1PoVC+kuF/Ja+lFMVl9d/L37vpSCeE11CE+F1rf/mLnrynJ9s2BWOHR7a4Mzrq1qhjNwUeYkQMhw4dKpZoQHqQU6dOtTg9CCwfIpLI7SkHgR0ETUYMu40NrAWdIvuxJgspTxBAoAZWc8KECWKJLhA4UhnCvYVopWkTgM5gWvxxPll3gDZ8pAnJGoJSxwC1XwuuHhZz8+zj91J4SAcqKS2nuct+EEsNY0ifcLolqhOlC/WPd58dLpbezC0TV1DKjjnilgbU8eBqNsaXm2PJxdWL3nhKf7tXY0j3zNjjlOLX2AzWtIM+nxNGGufaNgV3O60QX29P4bXZhvKLdJMHGQJeKqt/PkpDe3cUS0zH0JhOdOC4MtmelYTlPhXud61gpsqrTDe+j7udjdDS45TAx1vT476gyHgXz8vdhdoLx3f0N32vmI4BnibJOq023JzrXeIKEz4TOm4nbtyE6avo8NeathNDUOoYoPZrKUFpRQ39909NYtjoEG/q301/YtyGgRaIbvK429hy53Of0ob3xwkibHzUe0vcToDj4Nrqo2fXDux7NATf8/Z+EfTqEyPEEnWRlFnMZvcFf+sdRJ1N1Imdu51WRkkF+nNqkL+RGwMPO+pSh7+Zyv7HNnrv5BY23h+ypaAh2t3Vid54cqTeBc03+igqqyQXwdNQKy6yTgzoU2sqdMSn1Hg5JcfYKXktJSgtr//jN9WzRZ/oJNCgnZGj6SplSjJyiym0gy+zfPoWWF18l4YLLKKvl3q7yMnnuygT58EwBbriE/5ARaVGPtwKHQPUfi0lKK8WKvxij2p318atxfJ/P8EebPyOhnQLDaDUDONykxhCQkoe9YywvrSFzcEsn3jPzRZw4agfaeQ6FtcWumqTHxxKGw/EUxWEbELW77lAz4zTbYczBHgY8DTUCtr5pHteaU7xKWVdlLRISl7L3Jjij4863y3RIXTgRKpY0nqOX8gkb083wYUMFksMB/cY91rNSA3tpuRm8SlUr1KyLqbktcwNOlWbgoVTH6Y9x6/ST/vije6xLwfWc9eRRPpqaxx99R/TJTFSG45KiI+jfiQXyN2l5RFCtGMumTGBkq6V0/+8+T1rIpAvXu43d9hGWcP9/vbiGjocl00rZv2v6q1Xa5Dueaks2txq0M4nZ+n3v9VVVFaLW4ah1DFA7dcyN4fOZtWtP5DEFlvhvpeX1p1LzBC31MnPx9LYPd965IpY0np0Gtk56mff6WuUXaDJJzphROvnr1cDDacHUyPSfYe3MXZwiFjaOrjbaaWYc+oqjjJw8VkZ7QTRQXZocmgJUvoJjnHcuHFDW+8zFVx8Voa8q5OhoD/otiNp9MWOhFYFacxFWAdfOnTsvLilTjAZjanh4rM2pNevsDT3QGQXVNDK3Zfo+cV/UGzSdZp8T6RZ2qtaAwbf5mVl0Oqf9lBimmZKZlUi3nMXE874y8VnZci012ibX8LVQlq46RwTHSxeoI8rTXuol+qEB+Yt30KTgi/SjIg4mrlovViqPqR73q6t6e4hF5+V4dbEm/fQ2Sz656oTbME6wHRX70+6RZXuJoYSXbkUT+M7X6NB/sXUsTaVNu5qXSY0cwHX3dRw8Vkx1TU3qEpYdh5PZ5bu2MVcuiXCT9sEEejjolrhYaDyu4t/pNlRZ8USomld42nl97tVnazYlD1duPisDBeWaEjjBOFtDAGOHtiJuZU+Hk5074BObC5xjfD6q1J44JNvf6ExfonU1bN+DkR/52p6rnMCvfvZj2KJOtBYPc09b0nAqzG4+KwMDCNqIzwHWEora3TE1TvUh9JzS9mEmRAeBKhGzidl0p9HTtCkUM2IfDljgrOo8OollglNLUjTbmNxN2AAs6Fw8VkZ8j9+ZXUtnbycJ24RDY4OoF0nM2jGYzGqFR6YufB7FmBxdkAe6JuZ3f0ss35qyaGDl5yEmwk9CS4+K0P642NQ5xc/J9CmP+qtx9mUfHpoaCgLsqiVtdv/pGiHVOrr23i9rpNbJY0PTGWuqRqQN+lwy2fHoFvZVcG1/OWvqxQe5MECKhJRnb1VLTwEUpau200zonTnRdAHXFK4pnBRLU25YPk0Nb7WjSRpCBefFRLg7cKyaCF7mRw1tuPJmbloA82MvNCouykH+8yOOk3TPtLMdWBJysRmBrz4eMDFDkEQRSKykxcFCHW6CqHOh2inNbD7zwtUl3OZRnXQzIdnCNFeZTTILZVWbdJMYGkpijCGTzB7nm71iZRMAReflYC63dVcTbo/P4/6ga4FpervKM3a9D7/iWZH17fpGcrUbpdp5ca9Fmv7w8utuEwzgJaLz45AA7oE2vE6+2vS6+EhkOogBVYwSmHOkk30XJdE1o5nLMz9jD4nuJ9rxBJlKS6v1t5r+UvPFHDxqRT0yZy6/JiOACXae9Y/BPmy6cLUSGx8Gp2LO0sTQjLEEuMZHlBInqUptG1/rFiiHHlF9feXWz4bB+Pt5qw7TYfPZ9P0x/roDaKgi5O7Cx6ENjrThakNTReyH2h29zixpOXM6HaOPv7mZ8WzyRUxl1Nj+3zcWzcLcEO4+FTG4bNZFNXJi+ZNHqB1M/WBrmTocVFYVqXaoMvKjQdpkGsyC5y0Friskzol0rzlW8USZSgU6tS4z67ODiaNdALVia+mto6++D2D/Gb+Tm3ePMiWkZ+fonOZxk+HZY2MHRJiUG4WX0F8EjmF6kpvCDA2b9vuw/RyeKJY0nrgusKFhSurBGhclwJafjJX31SoTnz/3JZEUzZeonzZnAQHEwvpXzvqZ9yxNeBmypsSDCHIt36GIQyaVRsYm9dUF7KW8mH0GZq5YL0iXc+yxERVINiv8RmdWoqqxJecV05fH7vG1mfd24XqPh5B1Qv+RsseiSQ/E1d21QQimcb2TEH9Q+pqdk32kKgBjMnD2DyM0TM1GAVxl18qLVu3RywxH7myYAs6Npga1db5ogM19Z12Dm3oxds70sonujOXdNqWROaKjl+p22a06mgmKx+w8AQVVdTQAyvOkvNbv9EfyYX02qZLWhd20toLVCbrq7fvYj6N/uKM9vOG++Cahp4rLb9C51x95h+nY6m6E5LgBXPn4ljq96/9bB+c94s/W9aFKlB4IBAKKBd+rylnz2kNaI/DmDyMzTMXz4Ym0a4Dx8yediIzr4zdXy9XR4OmYzMWVYkv2MuZPMWR2n9fF0/z9l7RebghxF7BGlHuEUSTI7ZxQSBb4jS9+8f2ak9ujppzVAnlty8+RZ8dqg9zrzmeTU+tucDWK6pv0NPrE2hXgm6vC/k+Eoaca5jwufxccUI9FS609BsOJxXS8HlHyTk/n8pq8GfVnPetrUk0e2cK2zYGNnIBpxGWDOFBUQNSWoiWtOkZClxZc6edQKClulZwmYV7G2QGlxOoSnwujm1p+eNRbB0P5fTtyeT+z8P0jCAQ6QF+sn8Qhfo4U2nVDdp7UTMFcZpQ58GD7SSIc0wPP1YmgbLNk3sx93XqiM6s7EpBJTsf0vD9+54udOqtAczFxbL6yWi2j1zcEjjX0Tdu0TnXjgvXmXXLFFyU4spacndqS9nv3cbOtXdKH8Fd1rwx8YL4f9suUrTbDbqtfwhd/Ggk22fnCzHk69qOFuxPu+l6zRHkU/9QXMu3vOuJMXhZiedZWghzA5c2vDaJjZIwBxnX619mwbL6tSlRndt5b7QfXfnPYHp1eP2E/auEeuDwz04xwUCgj/QNYOXfx2az//dfLmABmt7B7myRM+OuUBoX48+s5vg+/qwsIbtMEK8gPqHs3mhfWim4rFJ0dZJgcRsD5xrUxYsd94rw/SAavCSS8uoDHngp/E34rrDaQ8K8aM+UvuTm5MBeEH9mVdH+QgeatS9D65qO/jKOffdq4TzJsvMYAtr7UBeB8cstrDBLejtDYW16n/3IxuIpxbTIi7Tyh1/N0vUsLbuU3VdMQOprhkgnUGWdL8TXhRY/FEkZs4fQC7dpppw6ebWEtp7VuJaSiGB1UA/TcTmNaIuRXEW4kvLoaksIb+9KW5/tzQQZn12utdpydxJXMHWLXCibH1zje17JtlzuE4y9wxg8jMVTCs92NfRK2CWTp524Xix4RoIXg3sa7Odutuzgqg24gGBvZ/pkfDfmZoJ4wWKBgSGerAxW57+CIE+nl+h1OZvjeFoxc0EldxJu4KFX+4mfGs+wrt50/cPb6cL0W7WWe+6vV3SCLvJryZdKwZWFVTWWTv71D0dajmXqfU2lhTA35kg7Ib+PIQHmm65aVeJDva1hg/rBxAImECBFQOF6zhrdha3P35fGPtfnchqKoyAId8Fiol62+UzjETRJSNjvc9Faoo43KsqHffe7l51m3z06yI3mj43QviDglkrBJGzjPFIdFudCpwIcK5UZA4QX3F64L4L+iiuqWaBAaTDmbnbUaZO36RmKKdNOIBfq1Tzh+RPuJ5pyzNG4LqEq8V0U3jhoUO89/7hOnQiM692eJvQPZOvgjm4+zMWTMNblBJ28ndg5UE/DNR3f+o0WHbwqfnozEM7gT2J19rs7ypcCxN4mv14s0H5317cPsZeCJE75C2OLYK3hkmI/nAsR0eut6KMZKrydNY6n8tYPY+0w5s4UXchaClzdCUGJNG/FdrGk5WAmopoazbwMGpfefKhKfJMGdmAN6gM6e4glsHau9NH94bR2Yg+xREOIjwtz80BLXE4gr6cBnGf5Y1FaN7ch79wVqhMImjyog/Z7DRFcRnx3+QthRIS34GL214pz8uBgFt2U/z5cE+eBu2vsy0PC38tFELfm2JSs4hZPomIsrE1v41425s7STAq7Kri+sa1OO5Fwtb6KEBpoXvFZ9fx8aHCHBeovPMyteXibAm7hQ1+fo23n8livm9mjw8RP1MWl9EI6f6WQrfcO86GIYOPrj8by3L9X0Li2vxo1Ot2cxBe50YzE2+mX5W+JJcYBl/3AGU0zSbCfGw3qrgnsmQtVB1yaQt4VrSUup60RGuihDbxcTjd9t66GYGydU/4l1QgPwPUd7plCS9ftFUuMQ271unc2/8vLasUnte2hTvXysHpX0F5xFtzOsCBN/1DkdsmUNRKbGoypw9g6jLFTGxhFsfGXw3Q1S9MBw1BKyqu19wxWz9vEY/f0waeFtiHQv3PPSU33Nzw8I/t0YOum5p2Pf6DInF9aNTrdnBzK8aY1pXfQ6nlTxJLmOZtSQImZGssHdxMCNDdWa/k4N4POv9JDg/oLUsebGlOkhTA3xqadwL2ShIeXlhLCA9zy2Rh4kDA9GNqrEAG9u39HamvCHhrj31hGsRctn8jWECI6etPeFdPErcY5ciFHO3bvth4BhPkMlYCLzwaRu1A9Q70pspNucl21ETbmP5SyY464pSyo5x1L0HSsUCLCKYe7nTZIZCdPbbsfIniYUIVzM2gPvSA2zwAlIpxyuPhsEEQ+uwkCBHA/YQk5N3MxvYjl5QRoF1UiwimHi89GCQ/y1D5MmFjFHMEXawZ148sZGtccQ7PgLSgNF5+NgiBL33BfcUtTD+Tupwa4m7GJ15lXAHp38WHegtJw8dkwGATavbMm2IKG99jL19m6oWimQ7Y94G7C8gFkA0DvIEvAxWfjIAGvr4cztW3ThuX3TMtp3v1EKsLFWy+w7Nm2BtLrJ2YWs/sBa3dLN+M75JsKLj4bB+5nvwhfcnBowzIvx6XkNzq/A8S2cvclen7xHzQ4yr/JjNnWCNxuWH+0ruFe9LKQuynBxWcHeLk5UY8Qb/bA4cE7cSmPzbYqgclYNhxMpleWHmETtEy8M4LN725LoJ7HfndVDbsPYUEeFGLm8XrNwcVnJyApb5cgT+HBa8PEduJyHnsgdx5PpxcESwfxoY4H0T08TDPo15aITbrOUr/j9/t7u1DPUB/xE8vBxWdH9BSsn7+XM3vzxyXn0/Of/UFf7EhgoXYAgSJ7tq2BAAtGqON3IzVE/27tTdrlrqVw8dkReOB8PZ3oTHIB5RVXUUwXX7qtZyATHSb6n/FYjOrndTcWtOUlZRaTUOMlJwcHujXSnxwd1PEbufjsjMiO3vTagz1oREwQm9vdSRDkacElg/BYBmwbIlEUHowccq327erLXjJqgYvPDkFdb2CUP5uDoKCsmgYKbhjqQrYEmhOSrpWw3+UgWLp+EX6srqcmuPjsDNTx0IaHTMwxXf1Yli48mOjdjyBMDeYnsGLwYolPK2RTruF9giaWfoLFQ5IptcHFZycgkvmv1bGsLe+1BzQZ164Jgpv6UC82CBcWokD4DMNrpM7G1kZV9Q06mXid0jG7kGjx+ob7UXsVCg9w8dkJm/5IpfAOHqxuJ9V70PXMy82RuaDSNNPohgYLKJ8Y0hrA9NjHLuVQkfA/foezU1vq3w3CM1/S29bCB9NyGDeExwAh+WvX60XXwc+VugV7UjszRwdbM5gW3/tKdilbsA7wQukd5qv6yC23fDbMT4dTDZ5uGn0dowVL2K0jGuKFt7KwZOWX018Xcym3SH3TToOismrWayU1u4TqhH/4zp383Vgd1hqaTLj4bBi4me4uxk2n3dnfnW6JaE/uzo6sbay6po7OpxayIUmWnIJMDnroJGWW0CmhfldeWcu+p3M7B4oRrF1kRy/2IrEGuNtpYyCwYoq2LMmdazgKAvMBdg5wJw8TtpcZ6nZCdFdzy9h0zZKLCYJ8XalrB7jH1iE6CW75bAi4mG8uP2awq9kUsB7ofNyvqx95uQtWUHRF4YKeSsyjC2mFlFekzFx8eKFcyiiiYwk5lJFXqnUxnR3bstT4GDZlbcID3PLZCEfjc1j73YtjutPw3kFiqenAhJGwgg0H2KJuhWm0EFVsaQ4UfZYPoy5yCivZGMSGI/BxzY7t3VhAyFpcTH1w8dkAUhveaw9Es36a5gQiRE6YhiIE6KANl9dDqGd6ujqSh7AYYpF6PvQBHfnuH1RYWs3qlaWC8ORDniQw9g5jDJXKq2luuPg4LQKRxjxBiBBjtVAXawoI0M355sBPWWU1mwWqKXAsRuL7ejiZdaJKS8DFZ6Wgp8quE+k0YUS4WGI5IESIsKSiWq9FNBZYT/S6geAgPFuFi89KQeQP9Txz1O9aC8QIIaIZoFrsKwrrWC5rqkDfUmkc4c7D5+ixe/oxd9XDtZ1V1+OMAuKzBZKSkup8fX3xImFLTExMXXZ2tvhpPYcOHdLus379erHUeqisrhXXbIcu9/1bXLMvbKapIT09nfLz6ydqjIuLoyVLlohbtgFSPcxZd1rc4lg7Nt3Ot2DBAsrJyRG3rBfUo+b+EMcSvdpimgd7xSbF9/zzz7P/S0tLbcL6bTuaxtq23pt0CwtCcGwDmxSfj48PhYaGsnVjrd+uXbto4MCBhPFgWJydnemZZ56hlJQUcQ8Nq1at0u6zYcMGsVTD4cOHtZ/Nnj1bLK0vxzn/+OMPmjlzpnZ7+/bt4l4a9u3bR6NHj2afPzGyK731cG/qG9OL5s2bR2VlulM+S9/Fw8OD/Vb8Bj8/P1aGZdKkSTcdw7E8Nik+V1dXmjVrFls31PrV1NTQtGnT2AN/4sQJsZSoqqqKPdy9e/c2qQv72muv0dy5c9k6rlFSUsLWAUQ5atQoJiI58fHxNH36dBo+fLheMVVXV9N9993HfoO8/rtmzRoKDAy0CRfclrDZOt+TTz5plPVbvXo1LVq0iK2/8847TLR1dXW0c+dOVoZtyZ1tLRCbXOByYB0lUcbExNDZs2fZ97hy5QqNHTuWlZ88eZLmz5/P1uVI55W+P44ZOXIk+wzbe/fuZescdWCz4nNxcaG1a9ey9easH6zeli1b2Lq7uzu9/vrr5OamSZUOCyQ99Hv27DGp9YB1hrBgsSZMmMC+hyQqJycnWrFiBfXqpQmwhISE0Keffkq+vpqZhxp7oeCc77//Pvv+OGbixIniJxrLyVEPNis+MGTIEK1wmrJ+eOhPn9aE8CFUuGhSfcnR0ZG2bdvGPjMl48aN09YH27XTDM+Rfw9cNzxct/dKcHAweXpq+m5CsMnJyWy9KaKiosQ10p6bow5sWnx4qN9++2223pT1y8zMpOLi1g/DaS3y79G9e3dmheXg9/Tt21fc4lg7Ni0+0ND6ZWdns/XG6N+/PxMq3MGGC4IiAQHmm0BEbtkSEhLY95DTnGXkWBc2Lz5YC6muhId54cKF4if1yB96BDiwGEPDutTmzZvFNeOQWzZ9bmVzlpFjXdi8+AAsxNNPP83W0b7WEARnHnnkEbaOiOGUKVPo3LlzbBtAXAjfy9vs5HUpWFTsD8uEZgIpamosEB/qgqDh90hLS2OBIKkJAdZcCgpxrBO7EB945ZVXtJFCfXzwwQfasDxC+WjXk4IuPXr0uKnNTe7OwqJif7iCaCaIjo5u8lpNgQZx6bzy74FmEynwM3nyZJ0XAcc6sUnxRUREiGv1wPrJQ/UI5Xft2pWtA1g/NCUsW7aMBgwYIJZqGDFiBHMl5Q88rNSmTZvo1VdfFUs050R7IdrqJDe2MaQmhIZI50X7YmPfY+XKlWKJcTR2TY5l4OP5OBanNUlzrRm7cTs5HLXBxcfhWAguPg7HQnDxcTgWgouPw7EQXHwcjoXg4uNwLAQXH4djIbj4OBwLwcXH4VgILj4Ox0Jw8XE4FoKLj8OxEFx8HI6F4OLjcCwEFx+HYyG4+DgcC8HFx+FYCC4+DsdC8BwuHEWorKqhYU8vopz8+tmYmsPZqR0d/noqBfh6iCW2Bbd8HEWAkKY8OlzcMoynxtxqs8IDXHwcxTBGTC0Rq7XBxcdRDGMEZetWD3DxcRTFEFHZg9UDXHwcRTFEWPZg9QAXH0dxmhKXvVg9wMXHUZymBGYvVg9w8XEsgj6R2ZPVA1x8HIugT2j2ZPUAFx/HYsjFZm9WD3DxcSyGXHD2ZvUAFx/HokB0nYN87M7qAd6xmmNxrmYVMAHaG1x8HI6F4G4nh2MhuPg4HAvBxcfhWAguPg7HQnDxcTgWgouPw7EIRP8fgdF/nYqoCUsAAAAASUVORK5CYII=)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "9m-KpngQSOyP",
      "metadata": {
        "id": "9m-KpngQSOyP"
      },
      "source": [
        "\n",
        "## This model has different parameters available compared to last time. The frequency of how often the tone and shock are free to change as well as when the shock starts. The orange lines on the plots show when the first shock occurs and the last one is just after the last one ends. Any spikes that occur outside the orange lines are caused by just tone.\n",
        "\n",
        "---\n",
        "## CHALLENGE - Adjust the 3 given parameters to ensure the cell spikes with only tone, i.e. spike after the second orange line. There must be no spikes before the first orange line.\n",
        "\n",
        "### Hints:\n",
        "*   #### The video on Pavlov's dog has some keen insights about the timing of the two stimuli.\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "id": "9e2211f2",
      "metadata": {
        "cellView": "form",
        "id": "9e2211f2"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/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": [
            "/usr/bin/xcrun\n",
            "/Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair\n",
            "Mod files: \"modfiles/modfiles/AMPA_NMDA_LTP.mod\" \"modfiles/modfiles/AMPA_NMDA_STP.mod\" \"modfiles/modfiles/Gfluct_new_exc.mod\" \"modfiles/modfiles/Gfluct_new_inh.mod\" \"modfiles/modfiles/cadyn.mod\" \"modfiles/modfiles/capool.mod\" \"modfiles/modfiles/currentclamp.mod\" \"modfiles/modfiles/h.mod\" \"modfiles/modfiles/im.mod\" \"modfiles/modfiles/kadist.mod\" \"modfiles/modfiles/kaprox.mod\" \"modfiles/modfiles/kdrca1.mod\" \"modfiles/modfiles/leak.mod\" \"modfiles/modfiles/na3.mod\" \"modfiles/modfiles/nap.mod\" \"modfiles/modfiles/pyr2pyr.mod\" \"modfiles/modfiles/sahp.mod\"\n",
            "\n",
            "Creating 'x86_64' directory for .o files.\n",
            "\n",
            " -> \u001b[32mCompiling\u001b[0m mod_func.cpp\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/AMPA_NMDA_LTP.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/AMPA_NMDA_STP.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/Gfluct_new_exc.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/Gfluct_new_inh.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/cadyn.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/capool.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/currentclamp.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/h.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/im.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/kadist.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/kaprox.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/kdrca1.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/leak.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/na3.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/nap.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/pyr2pyr.mod\n",
            " -> \u001b[32mNMODL\u001b[0m ../modfiles/sahp.mod\n",
            " -> \u001b[32mCompiling\u001b[0m AMPA_NMDA_LTP.c\n",
            "Warning: Default 120 of PARAMETER eca will be ignored and set by NEURON.\n",
            " -> \u001b[32mCompiling\u001b[0m AMPA_NMDA_STP.c\n",
            " -> \u001b[32mCompiling\u001b[0m Gfluct_new_exc.c\n",
            " -> \u001b[32mCompiling\u001b[0m Gfluct_new_inh.c\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Translating AMPA_NMDA_STP.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/AMPA_NMDA_STP.c\n",
            "Translating AMPA_NMDA_LTP.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/AMPA_NMDA_LTP.c\n",
            "Translating Gfluct_new_exc.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/Gfluct_new_exc.c\n",
            "Notice: This mechanism cannot be used with CVODE\n",
            "Thread Safe\n",
            "Thread Safe\n",
            "Thread Safe\n",
            "Translating cadyn.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/cadyn.c\n",
            "Translating Gfluct_new_inh.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/Gfluct_new_inh.c\n",
            "Thread Safe\n",
            "Notice: This mechanism cannot be used with CVODE\n",
            "Thread Safe\n",
            "Translating capool.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/capool.c\n",
            "WARNING: xx (a STATE) is assigned a value in a DERIVATIVE block.\n",
            " Multistep integrators (such as Runge) may not work correctly.\n",
            "Thread Safe\n",
            "Translating currentclamp.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/currentclamp.c\n",
            "Translating h.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/h.c\n",
            "Thread Safe\n",
            "Thread Safe\n",
            "Translating im.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/im.c\n",
            "Thread Safe\n",
            "Translating kadist.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/kadist.c\n",
            "Translating kaprox.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/kaprox.c\n",
            "Thread Safe\n",
            "Thread Safe\n",
            "Translating kdrca1.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/kdrca1.c\n",
            "Thread Safe\n",
            "Translating leak.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/leak.c\n",
            "Translating na3.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/na3.c\n",
            "Thread Safe\n",
            "Thread Safe\n",
            "Translating nap.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/nap.c\n",
            "Thread Safe\n",
            "Translating pyr2pyr.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/pyr2pyr.c\n",
            "Translating sahp.mod into /Users/gregglickert/Documents/GitHub/Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair/x86_64/sahp.c\n",
            "Warning: dt undefined. (declared within VERBATIM?)\n",
            "Thread Safe\n",
            "Thread Safe\n",
            "AMPA_NMDA_LTP.c:42:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "AMPA_NMDA_LTP.c:771:32: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "  if (_tsav > t){ extern char* hoc_object_name(); hoc_execerror(hoc_object_name(_pnt->ob), \":Event arrived out of order. Must call ParallelContext.set_maxstep AFTER assigning minimum NetCon.delay\");}\n",
            "                               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:46:14: note: conflicting prototype is here\n",
            "extern char* hoc_object_name(Object*);\n",
            "             ^\n",
            "Gfluct_new_exc.cAMPA_NMDA_STP.c:43:42::1818: :warning:  a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]warning: \n",
            "a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "         extern double *getarg();                        ^\n",
            "\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h::15:1517: note: :expanded from macro 'getarg'\n",
            "17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^#define getarg  hoc_getarg\n",
            "                ^\n",
            "\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h::4949::16: note: 16conflicting prototype is here:\n",
            " note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "extern double* getarg(int);\n",
            "               ^/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:\n",
            "17: note: /Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.hexpanded from macro 'getarg':\n",
            "15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "#define getarg  hoc_getarg\n",
            "                ^                ^\n",
            "\n",
            "AMPA_NMDA_STP.c:416:32: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "  if (_tsav > t){ extern char* hoc_object_name(); hoc_execerror(hoc_object_name(_pnt->ob), \":Event arrived out of order. Must call ParallelContext.set_maxstep AFTER assigning minimum NetCon.delay\");}\n",
            "                               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:46:14: note: conflicting prototype is here\n",
            "extern char* hoc_object_name(Object*);\n",
            "             ^\n",
            "Gfluct_new_inh.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "1 warning generated.\n",
            "2 warnings generated.\n",
            "1 warning generated.\n",
            "cadyn.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " -> \u001b[32mCompiling\u001b[0m cadyn.c\n",
            " -> \u001b[32mCompiling\u001b[0m capool.c\n",
            " -> \u001b[32mCompiling\u001b[0m currentclamp.c\n",
            " -> \u001b[32mCompiling\u001b[0m h.c\n",
            " -> \u001b[32mCompiling\u001b[0m im.c\n",
            " -> \u001b[32mCompiling\u001b[0m kadist.c\n",
            " -> \u001b[32mCompiling\u001b[0m kaprox.c\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "2 warnings generated.\n",
            "capool.c:42:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "currentclamp.c:41:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "1 warning generated.\n",
            "1 warning generated.\n",
            "1 warning generated.\n",
            "h.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "im.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "kadist.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "kaprox.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "1 warning generated.\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " -> \u001b[32mCompiling\u001b[0m kdrca1.c\n",
            " -> \u001b[32mCompiling\u001b[0m leak.c\n",
            " -> \u001b[32mCompiling\u001b[0m na3.c\n",
            " -> \u001b[32mCompiling\u001b[0m nap.c\n",
            " -> \u001b[32mCompiling\u001b[0m pyr2pyr.c\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "1 warning generated.\n",
            "1 warning generated.\n",
            "1 warning generated.\n",
            "kdrca1.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "leak.c:41:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "na3.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "nap.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "1 warning generated.\n",
            "1 warning generated.\n",
            "1 warning generated.\n",
            "1 warning generated.\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " -> \u001b[32mCompiling\u001b[0m sahp.c\n",
            " => \u001b[32mLINKING\u001b[0m shared library ./libnrnmech.dylib\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "pyr2pyr.c:42:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "pyr2pyr.c:611:32: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "  if (_tsav > t){ extern char* hoc_object_name(); hoc_execerror(hoc_object_name(_pnt->ob), \":Event arrived out of order. Must call ParallelContext.set_maxstep AFTER assigning minimum NetCon.delay\");}\n",
            "                               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:46:14: note: conflicting prototype is here\n",
            "extern char* hoc_object_name(Object*);\n",
            "             ^\n",
            "sahp.c:43:18: warning: a function declaration without a prototype is deprecated in all versions of C and is treated as a zero-parameter prototype in C2x, conflicting with a previous declaration [-Wdeprecated-non-prototype]\n",
            "         extern double *getarg();\n",
            "                        ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/oc_ansi.h:49:16: note: conflicting prototype is here\n",
            "extern double* getarg(int);\n",
            "               ^\n",
            "/Users/gregglickert/opt/anaconda3/envs/bmtk/lib/python3.8/site-packages/neuron/.data/include/hocdec.h:15:17: note: expanded from macro 'getarg'\n",
            "#define getarg  hoc_getarg\n",
            "                ^\n",
            "1 warning generated.\n",
            "2 warnings generated.\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " => \u001b[32mLINKING\u001b[0m executable ./special LDFLAGS are:    \n",
            "Successfully created x86_64/special\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "ld: warning: ignoring duplicate libraries: '-lnrnmech'\n"
          ]
        }
      ],
      "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",
        "\n",
        "    !git clone https://github.com/cyneuro/Fear-Lesson-Plans &> /dev/null\n",
        "    %cd Fear-Lesson-Plans/Lesson-2-How-do-Tone-Shock-pair\n",
        "\n",
        "if(os.path.exists('x86_64')==False):\n",
        "    os.system('nrnivmodl modfiles')"
      ]
    },
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        "outputId": "f171babb-eff7-4614-cf45-2101ed804701",
        "pycharm": {
          "name": "#%%\n"
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      },
      "outputs": [
        {
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              "VBox(children=(HBox(children=(Button(button_style='info', description='Reset', icon='refresh', style=ButtonSty…"
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              "Output()"
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      ],
      "source": [
        "#@title Run cell to activate model\n",
        "import numpy as np\n",
        "from os.path import normpath, sep, join\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import gridspec\n",
        "from neuron import h\n",
        "from neuron.units import ms, mV\n",
        "import ipywidgets as widgets\n",
        "from ipywidgets import interactive_output,HBox,VBox,Label,Layout\n",
        "from IPython.display import display\n",
        "%matplotlib inline\n",
        "h.load_file('stdrun.hoc')\n",
        "\n",
        "h.dt = 0.1 # time step (resolution) of the simulation in ms\n",
        "h.tstop = 1700 # how long to run the simulation in ms\n",
        "h.v_init= -65 # initial membrane potential in mV\n",
        "h.load_file('PN_cells.hoc') # reads in template\n",
        "cell = h.PN_C() #cell from template file\n",
        "\n",
        "\n",
        "tone2pyr0 = h.pyr2pyr((cell.soma[0](0.5))) # makes a syn connected to soma\n",
        "shock2pyr0 = h.pyr2pyr((cell.soma[0](0.5)))\n",
        "\n",
        "def generate_spike_times(firing_rate,start_time, end_time):\n",
        "    if firing_rate == 0:# in case shock is set to 0 fix divide by zero error\n",
        "        firing_rate = 1\n",
        "        start_time = 4000\n",
        "        end_time = 5000\n",
        "    interval = 1000.0 / firing_rate  # Interval between spikes in ms (1000 ms = 1 second)\n",
        "    spike_times = []\n",
        "    time = start_time\n",
        "    while time <= end_time:\n",
        "        spike_times.append(time)\n",
        "        time += interval\n",
        "    return spike_times\n",
        "\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)                # derefences and records data\n",
        "Soma_v.record(cell.soma[0](0.5)._ref_v)\n",
        "\n",
        "\n",
        "def plot_variables(tone_freq,shock_start,shock_spike_times): # plots stuff\n",
        "\n",
        "    fig = plt.figure(figsize=(15, 5),tight_layout=True)\n",
        "    gs = gridspec.GridSpec(2, 1, width_ratios=[1],height_ratios=[1,1])\n",
        "\n",
        "    ax0 = plt.subplot(gs[1,:])\n",
        "    ax1 = plt.subplot(gs[0,:])\n",
        "\n",
        "    ax0.plot(t, Soma_v)\n",
        "    ax0.legend(['Soma Vm'])\n",
        "    ax0.set_ylabel('Voltage (mV)')\n",
        "    ax0.set_xlabel('Time (ms)')\n",
        "    ax0.set_ylim(-80,50)\n",
        "    #print(shock_spike_times)\n",
        "    if(shock_spike_times[0] != 4000):\n",
        "      ax0.axvline(x = shock_start, color = 'orange', linestyle = 'dashdot')\n",
        "      ax0.axvline(x = shock_start+1000, color = 'orange', linestyle = 'dashdot')\n",
        "    ax0.set_xlim(0,1800)\n",
        "\n",
        "    ax1.set_ylabel('Inputs')\n",
        "    ax1.set_xlabel(\"Time (ms)\")\n",
        "\n",
        "    if tone_freq == 0:  # in case tone is set to 0 fix divide by zero error\n",
        "        tone = np.arange(3000,4000,1)\n",
        "    else:\n",
        "        tone = np.arange(100,1750,1000/tone_freq)\n",
        "    tone_index = []\n",
        "    for i in range(len(tone)):\n",
        "        tone_index.append(1)\n",
        "    shock_index = []\n",
        "    for i in range(len(shock_spike_times)):\n",
        "        shock_index.append(2)\n",
        "\n",
        "    ax1.scatter(shock_spike_times,shock_index,label='Shock')\n",
        "    ax1.scatter(tone,tone_index,label='Tone')\n",
        "    if tone_freq == 0:\n",
        "        major_ticks = np.arange(3000,4000,1)\n",
        "    else:\n",
        "        major_ticks = np.arange(100, 1750, 1000/tone_freq)\n",
        "    y_ticks = np.arange(1,3,1)\n",
        "    ax1.set_xticks(major_ticks)\n",
        "    ax1.set_yticks(y_ticks)\n",
        "    ax1.legend()\n",
        "    n = 4  # Keeps every 4th tick label\n",
        "    [l.set_visible(False) for (i,l) in enumerate(ax1.xaxis.get_ticklabels()) if i % n != 0]\n",
        "    ax1.grid()\n",
        "    ax1.set_xlim(0,1800)\n",
        "    ax1.set_ylim(0.8,2.2)\n",
        "\n",
        "    plt.show()\n",
        "\n",
        "def activemodel(initW_tone, initW_shock,tone,shock,shock_start,thres1=0.26, thres2=0.31):\n",
        "    weight_tone = initW_tone\n",
        "    if (weight_tone == 0):\n",
        "        weight_tone = 0.0000000001\n",
        "\n",
        "    weight_shock = initW_shock\n",
        "    if (weight_shock == 0):\n",
        "        weight_shock = 0.00000000001\n",
        "\n",
        "    tone_freq = tone\n",
        "    shock_freq = shock\n",
        "\n",
        "    tone2pyr0.initW = weight_tone\n",
        "    tone2pyr0.threshold1 = thres1\n",
        "    tone2pyr0.threshold2 = thres2\n",
        "    shock2pyr0.threshold1 = 5\n",
        "    shock2pyr0.threshold2 = 6\n",
        "    tone2pyr0.Beta_nmda = 0.026\n",
        "    #soma[i].diam = 30\n",
        "\n",
        "    nstim_tone = h.NetStim(0.9) # makes spike trains\n",
        "    if (tone_freq != 0):\n",
        "        nstim_tone.interval=(1000/tone_freq) # ms (mean) time between spikes\n",
        "        nstim_tone.start = 100               # ms (most likely) start time of first spike\n",
        "    else:\n",
        "        nstim_tone.interval=0\n",
        "        nstim_tone.start = 10000            # way to make the tone freq 0 during stim time\n",
        "    nstim_tone.number = 100                 # (average) number of spikes\n",
        "    nstim_tone.noise = 0                    # range 0 to 1. Fractional randomness.\n",
        "    nc_tone = h.NetCon(nstim_tone,tone2pyr0,0,0,1)    # connects tone to soma via tone2pyr syn\n",
        "\n",
        "    shock2pyr0.initW = weight_shock\n",
        "    firing_rate = shock_freq  # Firing rate in Hz\n",
        "    start_time = shock_start  # Start time in ms\n",
        "    end_time = shock_start+999  # End time in ms\n",
        "\n",
        "\n",
        "    shock_spike_times = generate_spike_times(firing_rate,start_time,end_time)\n",
        "    netcons = [h.NetCon(None, shock2pyr0) for _ in shock_spike_times]\n",
        "#    Create a NEURON event to deliver the spikes\n",
        "    h.cvode.active(1)  # Activate the CVODE solver\n",
        "\n",
        "    h.finitialize(h.v_init * mV)  # runs sims\n",
        "\n",
        "    for netcon, time in zip(netcons, shock_spike_times):\n",
        "        netcon.event(time)\n",
        "\n",
        "    h.continuerun(h.tstop * ms)\n",
        "    plt.close('all')\n",
        "    plot_variables(tone_freq,shock_start,shock_spike_times)\n",
        "\n",
        "#change these values\n",
        "initW_tone = 0.19\n",
        "initW_shock = 8.3\n",
        "thres1 = 0.26\n",
        "thres2 = 0.31\n",
        "#\n",
        "diam = 30\n",
        "tone_freq = 3\n",
        "shock_freq = 5\n",
        "shock_start = 250\n",
        "\n",
        "w_reset = widgets.Button(description=\"Reset\", disabled=False, button_style='info', tooltip='Reset parameters', icon='refresh')\n",
        "w_solution = widgets.Button(description='Show Solution',icon='history',button_style='primary')\n",
        "w_initW_tone = widgets.FloatSlider(value=initW_tone, min=0, max=20, step=0.1,layout=Layout(width='20%', height='15px'))\n",
        "w_initW_shock = widgets.FloatSlider(value=initW_shock, min=0, max=20, step=0.1,layout=w_initW_tone.layout)\n",
        "w_shock_start = widgets.FloatSlider(value=shock_start,min=100,max=500,step=1,layout=w_initW_tone.layout)\n",
        "w_tone_f = widgets.IntSlider(value=tone_freq, min=0, max=15, step=1,layout=w_initW_tone.layout)\n",
        "w_shock_f = widgets.IntSlider(value=shock_freq, min=0, max=15, step=1,layout=w_initW_tone.layout)\n",
        "w_thres1 = widgets.FloatSlider(value=thres1, min=0.01, max=1, step=0.05,layout=w_initW_tone.layout)\n",
        "w_thres2 = widgets.FloatSlider(value=thres2, min=0.01, max=1, step=0.05,layout=w_initW_tone.layout)\n",
        "\n",
        "def reset_default(*args):\n",
        "    #w_initW_tone.value = initW_tone\n",
        "    #w_initW_shock.value = initW_shock\n",
        "    #w_thres1.value = thres1\n",
        "    #w_thres2.value = thres2\n",
        "    w_tone_f.value = tone_freq\n",
        "    w_shock_f.value = shock_freq\n",
        "    w_shock_start.value = shock_start\n",
        "\n",
        "w_reset.on_click(reset_default)\n",
        "\n",
        "def show_solution(*args):\n",
        "    w_tone_f.value = 15\n",
        "    w_shock_f.value = 15\n",
        "    w_shock_start.value = 100\n",
        "\n",
        "w_solution.on_click(show_solution)\n",
        "\n",
        "\n",
        "labels = ['Tone Freq','Shock Freq','Shock Start Time','Tone Weight','Shock Weight','Threshold1','Threshold2']\n",
        "Labels = [Label(L) for L in labels]\n",
        "\n",
        "ui = VBox([HBox([w_reset,w_solution]), HBox([Labels[0],w_tone_f,Labels[1], w_shock_f,Labels[2],w_shock_start])])\n",
        "out = interactive_output(activemodel, {'initW_tone':w_initW_tone,'initW_shock':w_initW_shock,\n",
        "                                       'tone':w_tone_f,'shock':w_shock_f,'shock_start':w_shock_start})\n",
        "\n",
        "display(ui,out)\n",
        "\n",
        "\n"
      ]
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