tutorials/W3D2_DynamicNetworks/W3D2_Tutorial1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/NeuromatchAcademy/course-content/blob/master/tutorials/W3D2_DynamicNetworks/W3D2_Tutorial1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Oh1wn4afauo0"
   },
   "source": [
    "# Neuromatch Academy: Week 3, Day 2, Tutorial 1\n",
    "# Neuronal Network Dynamics: Neural Rate Models\n",
    "\n",
    "__Content creators:__ Qinglong Gu, Songtin Li, Arvind Kumar, John Murray, Julijana Gjorgjieva \n",
    "\n",
    "__Content reviewers:__ Spiros Chavlis, Lorenzo Fontolan, Richard Gao, Maryam Vaziri-Pashkam,Michael Waskom\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "A9pNslIYayZt"
   },
   "source": [
    "---\n",
    "# Tutorial Objectives\n",
    "\n",
    "The brain is a complex system, not because it is composed of a large number of diverse types of neurons, but mainly because of how neurons are connected to each other. The brain is indeed a network of highly specialized neuronal networks. \n",
    "\n",
    "The activity of a neural network constantly evolves in time. For this reason, neurons can be modeled as dynamical systems. The dynamical system approach is only one of the many modeling approaches that computational neuroscientists have developed (other points of view include information processing,  statistical models, etc.). \n",
    "\n",
    "How the dynamics of neuronal networks affect the representation and processing of information in the brain is an open question. However, signatures of altered brain dynamics present in many brain diseases (e.g., in epilepsy or Parkinson's disease) tell us that it is crucial to study network activity dynamics if we want to understand the brain.\n",
    "\n",
    "In this tutorial, we will simulate and study one of the simplest models of biological neuronal networks. Instead of modeling and simulating individual excitatory neurons (e.g., LIF models that you implemented yesterday), we will treat them as a single homogeneous population and approximate their dynamics using a single one-dimensional equation describing the evolution of their average spiking rate in time.\n",
    "\n",
    "In this tutorial, we will learn how to build a firing rate model of a single population of excitatory neurons. \n",
    "\n",
    "**Steps:**\n",
    "- Write the equation for the firing rate dynamics of a 1D excitatory population.\n",
    "- Visualize the response of the population as a function of parameters such as threshold level and gain, using the frequency-current (F-I) curve.\n",
    "- Numerically simulate the dynamics of the excitatory population and find the fixed points of the system. \n",
    "- Investigate the stability of the fixed points by linearizing the dynamics around them.\n",
    " \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "BptrqpMma6c3"
   },
   "source": [
    "---\n",
    "# Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "cellView": "both",
    "colab": {},
    "colab_type": "code",
    "id": "QG7r5GjEadue"
   },
   "outputs": [],
   "source": [
    "# Imports\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy.optimize as opt       # root-finding algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "cellView": "form",
    "colab": {},
    "colab_type": "code",
    "id": "QCwXDPapf7D-"
   },
   "outputs": [],
   "source": [
    "# @title Figure Settings\n",
    "import ipywidgets as widgets       # interactive display\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "plt.style.use(\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content/master/nma.mplstyle\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "cellView": "form",
    "colab": {},
    "colab_type": "code",
    "id": "C7rvBOvji_hj"
   },
   "outputs": [],
   "source": [
    "# @title Helper functions\n",
    "\n",
    "\n",
    "def plot_fI(x, f):\n",
    "  plt.figure(figsize=(6, 4))  # plot the figure\n",
    "  plt.plot(x, f, 'k')\n",
    "  plt.xlabel('x (a.u.)', fontsize=14)\n",
    "  plt.ylabel('F(x)', fontsize=14)\n",
    "  plt.show()\n",
    "\n",
    "\n",
    "def plot_dr_r(r, drdt):\n",
    "  plt.figure()\n",
    "  plt.plot(r, drdt, 'k')\n",
    "  plt.plot(r, 0. * r, 'k--')\n",
    "  plt.xlabel(r'$r$')\n",
    "  plt.ylabel(r'$\\frac{dr}{dt}$', fontsize=20)\n",
    "  plt.ylim(-0.1, 0.1)\n",
    "\n",
    "\n",
    "def plot_dFdt(x, dFdt):\n",
    "  plt.figure()\n",
    "  plt.plot(x, dFdt, 'r')\n",
    "  plt.xlabel('x (a.u.)', fontsize=14)\n",
    "  plt.ylabel('dF(x)', fontsize=14)\n",
    "  plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "iTfHsVLEg2Su"
   },
   "source": [
    "# Section 1: Neuronal network dynamics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 519
    },
    "colab_type": "code",
    "id": "uOLOhRbOg95q",
    "outputId": "ce679df6-afb7-49fa-c97c-305853602b71"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Video available at https://youtube.com/watch?v=p848349hPyw\n"
     ]
    },
    {
     "data": {
      "image/jpeg": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEABALDBgYFhsaGRoeHRsfIi0lIyIgIzgqLSgvOS43MDAwLjg1PVBFQDpLOTAtRWFFS1NWW1xbNkVlbWRYbFBZW1cBERISGRYZMBsbMFdCNT1XV1hXV11jV1dXWFdXXVdXWFdXV1dkY19XV1daWFdXXV1jV2NXWVdXV1dXXWNXWmBXV//AABEIAWgB4AMBIgACEQEDEQH/xAAbAAEAAgMBAQAAAAAAAAAAAAAABQYBAwQCB//EAE4QAAEDAgIGBwQHAwgIBwEAAAEAAgMEERIhBRMxQVFSFyJTYXGS0gYygZEUI0JiobHBFmOiFTNDcnOT0fAkNFSCo7LT8SVEdIOz4eIH/8QAGAEBAQEBAQAAAAAAAAAAAAAAAAECAwT/xAAgEQEBAAICAgMBAQAAAAAAAAAAAQIRITEDEkFR8DIi/9oADAMBAAIRAxEAPwD5+iIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgit/RxXdrT+Z3oTo4ru1p/M70IKgis1N7DVcr3tbJACzI3c7jbLq9y6T/8AzquH9LT+Z3oQVBFY6j2Kqo5GxufCXOBIs51ttuVe/wBhqvtIPM70oKyis37DVfaQeZ3pT9hqvtIPM70qbgrKKz/sNV9pB5nelP2Gq+0g8zvSm4aVhFZv2Gq+0g8zvSsfsPV9pB5nelNxdK0isv7EVfaQeZ3pT9iKrtIPM70p7Q0+tIiKoIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiCI0IPrak/ft+JUo9R2hRnUH96VIPUhUFpI3rmDhEPxcf8F0hcdcb6QPdEz/AJnLrUqx4lBtkVyyucBcusO82XnS2kW00eI5kmzR3qrSUNTWO1l3Oad590eCzWpLVibO5/uSX8HAr3gl5neZViXQr6frhxv3KT0Npl8kZa6xezJ1943H81OL0txs7SboZeY+Za3U8nE/NZfpEYchZ3Ei4/MLQa2U7HN+LP8A9IyPp38fxUJpZ72PDL5HM596mDVSnaY/gD/iuSppGSuxPdna2WSQ7fRURF1ZEWFxwaUhkqJKdrjrI/eFst2w77XF/FB2osLloNIMqAXRtfg+y9zbNeOLeIQdaIiAiLgdpaLUslGJwkdhY0N6znZ5AfAn4IO9F4ifiaHWIuL2cLEeIXtARFhBlEWEGUWmrqWwxPlffAxpc6wvkBcraDdBlEWEGUWuWdjC0OcAXnC2+82JsPgCtiAiwsoCItFJVMmZjZe2JzcxbNri0/iCg3osLKAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgjdDizZTxmf8AnZdzlx6MFmO75JD/ABldRKRKgKo3r5O5jB+Z/Vdd1wOdeuqO4tH8IXas1pBaWpdfXU7Hi8TGOkcNxzAsfjZSQ0mxzxExoFhkAdy9wytM0rSASGtyPA3/AFWjUU8OseyOzjcFzW93cuGd509Xjx42jq2qEpIA2KsVD3RSvwOLbtvkbKWhomPu8lwz3GyzTxM+lMBa1xLSOsMQyz3q48VPJLYiKCul18WKRxaXZ3dkVd4GNc2+Sji2C5AZCSDbKIZFZl0gImk4gB3MXS8uESboQvJjC5tbKQDcWIv7q0yNeduE+LQsqvSIi7Obm0hVtggkmdsY0utx4D4nJVNlYyCKmmLJ9dHIXzudA9oIkP1t3FtrDIj+qFbqqljmbgkbibiDrXIzBuNneBkvc8LZGOY8YmuBa4HeDkQgxURCSNzSTZw2tcWn4EZhVWixR0Oj42a0ioALw2SzjaO+Fhc4YQbbARkDbarZFE1jGsaOq0AAXvkMtpXOdGwGBsBjGqaAGtucrbLG9wRxvdBEl9RTMqZGRStjbA57WyyCS0g2Yes42I2jZl3rxBDOBFJFHUmS7S58k7XMe0kYrtxkbL2sMslNUmj4ocWAOJdtL3ueT3XcSbdy1Q6Gp43hzWOGE3a3G4saeLWE4R8Ag46Wn+kz1L5JJQYpdWxrJHMDAGg3s02JN7533KLipGyU+jMTn5zObdr3Nywym/VIzuNo7xsKsVRomCSTWOYcZABLXubiA2BwaQHfG69s0dC1sTWss2F2KMAnqmxHHg4/NBGw0oqpanWySjVyatjY5XMwANBDuqRcm97lckM0tQyha+WQYpJmOex2EyNaHgHLiADceIspmr0RBM/G9hxEWJa9zMQ4OwkYh43W76HFeKzANV/N2yDcsOQHcghqqV8Ek9O17/rmx6glxcQT9W61zfq2a74lZpJ3vkp6cvfenMhmN83BnUZi44sQd8FMy0cT5I5XMBfFfA7luLGyR0cTZZJWsAkkAD3cbbPzQVp8j9XFVxiZofNHhe6cuxNfIG9aO+EAg5AbMtikqaMvrKtznyERPZgYHkNvqmnYNvhs+K6hoSm5HWDg8N1j8LSDiBa29hmNwXXHTsa972izpCC48SBYfgAgq09NrdEy1T5ZTNJA57jrHYcwbswXw2GzZf4q1t90eH6KPk0BSOx4ojaS+JuNwaSdpwg2B7wLqStuQVOKNzdHU1XrpjP9T1jK4ghz2tILb2IsTuuuqR756qpa6Od7YnBjBFMIw0FjXXPXaSSSc+Gzepn+TodS2DB9U3Dhbc5YSC3O98iAvFXouGZ+N7XB9rFzHujJHAlhFx4oIaqpHyChFTrBJr3MylIJbheWk4DbFYC5HfxWyplkD56MSPD5pGGN1ziax4OPCfu4H+FwpafRkEkTYnMsxhBaGuLS0jeC0gjfvWw0URlZLh+sY0sa65uAbXH4IIWmrpZXx5kupoHulaCRiluWAEbx1ZDn3LTJEWUDa5s8rqjA2XFrHYXk2ODBfDY3wgW/FWGCkjjfI9jQ10rsTyPtG1rrmboSlD8YjzDsQbidgDr3xBl8IN8722oOaOIy182KSQNjbC5rGvLW4utmbbdmzYd91GaOqXPw05xwwunmvIOrrHaxx1bSMxlv32IG9WdlOxsjpAOu8AOPEC9vzK0v0bA6Iwln1ZcXWudpdiuDe4N87jYg6gsrAWUBERAREQEREBERAREQEREBERAREQEREBERBxUYsz/ecf4itpXiEWb8/wA16VRXI86upP7wfg0Bd6jad4E1Q5xAGtdmTbuXqo0zAzLHiPBuf47FjtpHwVdtKvaftjAPEDF+hXbXyVLfdwavgdvxVebUB1bHPa15AbcL5FWbSD7t90OHFcM+3r8V4QUEpLXXFs/8lROjpDNXtsTY3AztlZdmknuEb7ZEiyidDSMiqY3yEtY03JG75LeE+XPyX4WGfRMkYa1nXvclwaG27slz1EcwY5jY3kEWJDTc93cFbKeSORmOMte07CM1rMsfFq17au3Pd1pz0rfqYwcjgbcHwWXNC2OfHxZ+C1Ex/d/BYFvREXdzEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERBoAsvDnAAk5AZlbdUeK5dJUD5oXRskDC7Iki+W8bd6qPnWkqjFI4gktL3H5kn9VzYs/871aZPYaRwI+kt23/AJs+pYb7CyXualhyt/Nn1K7gr1JAHyAFwabgi++25WrUOfhBIAt1iuc+w0hv/pLc/wB2fUuyD2YqmNLRW7ur9Xs+ZuuOeG7uO2Hk1NVB6bpmxtxEjbZrd5VUwnFdXyT2Ime4vfVhzjvMZ9S1D2Bk/wBpZ/dn1LWOOmc8/ZUqaeSI3je5h7jZdFTXyyOa4Owu2HgrKPYGT/aW/wB2fUjfYKQX/wBKbn+6OXD7S1YzLpVBWTXw6zPYurRdS4vcHOJuN+5WD9gZbG9W2/HVH1L3B7CyscHfSmmx7M5/xLHq37RdkRFtzEREBERAREQEREBERBhZXFpXHgbqxdweD7t+Oai5J6iN0bZJZ8Lg0lzYw5xOB2IANYcgQDkMr8EFgRVyaorHxapzZBK4dbCzIA0xyDrWvre+/wAFP0x+rZtPVHvCx2bwd6DYoet9oY43ljGmQjIm9m34X3/JSNe9zYJSz3gxxb42yVFaBYW2bkFv0dpqOd2CxY/cDv8AA/5KklQoXESRlvvB7beNwr6gysOcACSbAZklZUX7RuIpHW2EtB8MQug5pvaZgdaONz28xOG/htPzspDR2k46gHBcOG1rto7+8KmLt0G4isitvxA+GEn8wEFzREQa55mxsL3nC1uZJUI72nbiyhcW8S4A/L/7Wfatx1cQ+yX5+OE2/X5KuoLvQ1sc7McZ7iDtB4FdKq3sw4/SHgbDHn8CLfm5WhAWisrI4GY5DYbABmSeAXQqx7UuOuiG4MJHjcX/AE+aDoHtO2+cL8Pc4X+Wz8VNU9QyVgew3adhVEVg9lHG0w+yHNPxtn+AagsCwsrCDj0jpOOnAxXLjsa3ae/uCj4faZhdaSNzG8wOK3jsPyuorTjiayW+7CB4YQfzJXCgv7XAgEG4OYIXkytxBuIYjmBfP5KN9nHE0jL7i4DwDjZR1dC3+VqZrjha1slQ5zjbE7JgF+DRu4ILIHC5FxcbRwXpVn2VmbJPWTHN80zsP9SOzW34bVZUGUREBERAWFlEGEWUQFhZRAWFlEBERBhZREBERAREQEREBERAREQEREBERBhYLQSCQLjYeC9IgwiyiDBCq2ldBOibJJEQWNaXYDusL2B4K1Lm0g28Eo4xu/5Sgq2imsiljfVgxtcA6F+2M3Fxd252ew27lcVHaHY2Sgpg9oc10EdwRcG7BtXOaCekzozrIhtppDs/snfZ8DceCCaWqogbIxzHC7XCxC5tH6UiqMQbdsjPfieLPZ4j9RktOlK5+IU1NY1DxfEcxEzYXu/QbygqGmD9Fm1bbzNDg1zgCdWSC4B1tpwgmw3BWrQWi2xgTYxI57eq5vu4Tn1fFaK2gZTNoI2XIFW0uc7NziWPu5x3kkrZGfoEwZ/5OV3VPYvP2T9xx2cCbb0E2srCip9MF7zFRsE0gNnPJ+qjP3nDafujPwQbdOGn+ju+kPDGbjvvuwjaT3BUSGaol60MBfG7GY3HJzwy2Ihvx2XVgGjvpVQ5hkdKWZT1ByDeMMIHu/eIzAyvcqUq42x1lA1gDWgSsAAsAMFwB5UGn2UkpXwl0Eokeffvk4dxbuH+c1OqraX0THBP9IGKOJ7rvfH1XQPP9IOLD9ppuN/FSDdJzU1hWgOj3VMY6h/tG54PHMeCCZUZp+nhdAXyyCIMzDybWPDvvwWKjTIL9VStFRNvwnqMvsL3bB4C5UTNRST1GqMplqALyygWZTtP2Ym7MZGwm5tn3IK3FXl8uEMcIQTeYtIAAIDnYTnYFwvwuvomjaNkEQaw3BzLuYneo19HHFW0cTGgRiGZmHbl1Cb8brNI76DK2neT9GkdaB5+w7sieHL8uCCcWEJUQ/SslQSyhaHgGzp3/wA03jh5z3DLvQc/tNTwgNldJgk91oAxGTg0NGZPgojQ+jJqkyCRup1b8Lhe7s2h3gMnDirNo/RLIXGVznTTkWdNJ73g22TW9wWrRX+t6QH71h+cLEEjTwNjY1jRZrRYBepImutiaHWzFxey9og8NjaCSAATtIG3xXtEQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQcekNIMp24nhxGFzuqL3tbqjvN8vArRLp2BrgLk5nMWsADhvmbkXvsuciu2opmSYMbb4HB7e4jYfxXNHoiBrWNa1zQxoaA17hcA3s7PPPjxPEoNcel2m3Vecw0uAGFrjsBzvst81pg07ibDeF4dIGlwyya5jnYhnmLtItty2cdjtDjWtc12GMEOLQXXJF9vWsdu0i+Xhbo/kuHq9U9VrWizjsaHADbwc75oPdBWtnZjYCBe2djuv8AZJG9baht43ji0j8F4paRkWLDiJcbuLnFxOVhme4Le4XBQR3s4b6PpP7CP/lCklE+yxvo6l/smhdWkq9tPHiILnOOFjG+89x2NH+ckEf7SMicI2hmKrcSICw4XtO92IbGjfu3b1z0Ws0djNU3WtkdifVMFzf963aANgIuAOCktFaPdGXzzkPqZfeI2MbujZ90fiblSJIAz2IIjTUrHx0sjHBzfpMRa5puDc2yPxXTpeqp44i2o6zZBhEYGJz77mtGZKqemw12F+jQ4ME8eN2ynL8YDcI3nFa5bla97qa0IYWTYZw9te4dZ09i54/dO2Ye5trbwg4qOOokeykrHyRQuaTEy/XlaCepI8HaG2u0bRv2qUqpTiFDRARuDRrHtGULDw++c7D4rHtGRKGUrG4qh5D4yMtVY/zpO6347OKezZEbZKd4w1LHYpSc9bfZKDvB/C1kEpRUkcETYom4WNFgPzJ4k8VH6V/1zR5/eyD/AIL1LKsaZ0prqilZSWe9k5GscDqg4xvGG42m1zYcM7IJ7SNZDDGTO4BjurYi+K/2QN5PBVimZOHR00zpaeilJEINtYRuie4HqjbYbbZXU/Q6IbG/XSuM9Qf6R/2e5g2NHh8brX7QyxmHUFmtlm6scd7EkfavuDcji3IIytpXUsrYdGOwSyAudC7rRNba2sPKb2GW07l3ez88Mbfo2F8VQLueyX33uPvPvsdc7x+C1ezzDBJLBUZ1TuuZTnr27AR/V2Yd23epTSVJBNH9eG4W9YOJwlh5g7aD3hBy6RNq6h79cP4L/ovWnamm1RgmaZDKLNiYLvd3tG6x+1kAqrWV9TraYxvkkp2yOEdSYrvN43B1m/bsLkOtn377XoSmphHrYHa0v96YnE95+8f0ytwQQ9BBPPKKbSL3dVocyIGzZW7zI4HrEZAtyG/O6tLGBoDWgAAWAAsAO5cmlNHiojADsErDiikG1jtx8NxG8LxorSBma5kjcFREcMrOB3ObxadoKCQUVo/KtrR3xH+C36KVUTRn/wARrB+6gP8A8g/RBKlQej/aB8tYaWSFrOq8te2TEHFjsLgAWjfi+SmKmdsUb5He6xpcfAC6qekIzSO0TUSZOa4slsL3dI27tm3rYkFh0zpMUsDpMONwBIbe17Zm53Dv7wN69aIrJKiBkskbY8bQ5rQ8uNiLi92ixVf9rWvdTMjcCJayZkYbyMve34C/eeACtcTA1oaMg0ADwGSD2iIgIiwg4f5Qd9JfAI74GCRzsWQBJAFre91Tl+K1UekpZ2MeyLKSPWMLiQBsIa423g7Re1itegjrJKuo7SbA0/djGAfxY/mpD6DDYjVtsQQRuscyO6+/igjpNKyvpJpo2tYWM3uuQ61yCLbBuN89uzbLROJbna++2xazRxEuJjbd7cLsvebwPELZHGGgNaLAIPaKPqjJjNnVAH3GsLdm64usUpkxi7qgj77WBvxsLoJBRGj9O62qfTOiLHNaXB2LE12F2F1stxuPgpOonbHG57jZrQSb9wuqrOx1NPoyfCS5weyRrBcudIC+3nJQTenNMto4w4sdI4kANbtzNh+KkIXPLQXtDXcAcX42CrGlotZW0MDiC90pnlschgHVb4XuPmdpK6/a/GIG4Hua6R7YmWJAa5zh1zY7QBl4oJ9ZUA2qcdKWMjtTHCGAXNnyON9g22a0+CnkNaZREQEREBERAREQEREBERAREQEREBFhEGUWFxaXwGBzXTagn3X4sJDhmLccxs3oOHQtWyDRkckpwtYCO82eQABvJ2WW7RtHJJJ9LqRaQi0UZ2QsO7+ud5+Cp3spBKJX1FTZ0URdJZ0tms2kvbHtvmbXttKntFaen0g3BAY4jmXvJBc1uI2DGE3Jta7j1b7LoJvSGlIoCGm75Xe5EwYnu+G4d5sFxjRs1V1q04Y9opoz1f8A3HD3z3e74rt0fouKnuWAukd78jzie8/eP6bF2IIj2kaG0YwgAMlhsALAWlZsXr2hkh1IjfEJpJThhj3l3EEZtA2l24KP9uGP+jh0UobIP6Mu/nBiByHEFoIPjxXH7I00kEb6iokhc1kbruxl7mNviwjc0bSRmTlwQd1DR1Oj7yOBqw8N1r23MrbC1hc9Zo3Dbt23WdMV9PJFHUU8w+kNJ1IaCXPP2o3MGdjvBGW3JKDTlRXRN+ixtjJvilfm1mZsGjIuda19wO8rcPZpjDrYpZGVWZM56xeTa4e3YW5DIWQaqMSaRDnTu1UTXFrqZhIdcbRK7I/AWB7106WgZH9BaxoYxlS0BrRYDqPFvxULpTS0lDM2eaLBKbMlwZxzs4t3te3aA7dcXK5NK18tTTUtTDUMEptrI75AgkCRrbmxBv437kFz0lXsp48brkk4WMHvPcdjWjiVz6LoHtc6oqCHVMgs62yNu6NncN53nNVTRFRPTUwrKtjXCJhbCXS3Nydwz6zic3E5AWtkrDFVVNaBqf8AR4LZy2+sfx1bT7o+87PuQPaKWN+GKPE6saccIizcw8ztwYdhvtC06MhNa55rXYpIX2NNa0bD9lxH27jME5dymaDR8VO0tiba+biTdzjxcTmT4qM9onagx1cbXmVnVOBhcHs2lr7bBwO4+KDfpjKeg/8AUEf8KReqvQ4LzNTPNPOdpaLsf3SN2HxyPeqhPWy1kdLOypDHukLZGuNtXYva2QDY04HG/HJX+na1sbAw4mhoAN73Ftt96CNp9MFrxFWMEEpNmuveKQ/cdx+6bHxXvStE8ubUU9vpEYsAchI3aY3fodxXdUQMlYWSND2OyLXC4KifotRRi9OTPANsMjuuwfu3naPuu+aCR0fXMqImysvY5FpFnNIyLXDcQVx0+Wk6gcaeI/xSBVmX2oiiqJ5orsN7SROaesLANktue12RG8DwWNDvdLWxSvqQIXRMkzfY4sRcIib7A9xNuFggu1VRxTNwysa9vBwuEFHEGsbq24Y3YmC3unPMd+Z+a3Ig5KjRVNK/HJCx7+ZwuV1NaAABkBkFlZQEREBeXsDgQ4Ag7QRcFekQaoaeOO+BjWX24WgX+S2oiAiIgwiyiDXNAyQASMa8A3AcARfjmjIGNDQ1jWhubQAAB4cNp+a2Ig5zQwF2Iwx4r3vgF78b22rbLE17S17Q5p2hwuF7RBx0ujYonOcxoxON7/4cF1rKItyuV3REREEREBERAREQEREBERAREQaaqobDE+V98LGlxtmbAXyXINKgOcx8bmva1ziLg5NDTtB34vwK7pY2va5jwHNcCCDmCDtBXI7RMBbhLSdtyXuJNxYgm9yLACxyyCDmbps3eDC44cbhhI9xmG5Nzt64yXuo0wBGHRxlziXgAkD3JAw/ncL3LoeF0geQbYXAtBIBxYb3z2WYARsN81sOi4CXHBm6/wBo5XIJtnlcgHLeg7FR66pdNM97jvIb3NByCvCqOltFyRSuc1pdG4lwLcy2+ZBCCNI35XGYuLq7aPbGYmSMjYzGwHqtA2i9slUqTR8s7g1rXNB2ucLWHdferrDGGMa0bGgAfBB7WuaTAxzj9kE/ILYvL2hwIOwiyChPldI4vebvdmT+g7gsMIBBc0Obliacw5t7kEb/APGy6azRssDi0tc5g91zRfLde2d1t0ZouSaRpc0tjBBJcLXtnYBBZ6PRtPASYYY4yRYljQCR8F1IsoIX2ioqcwyTPgifJYNDnsBIubDbwuqtHG1jQ1osBsAV60hSiaF8ZyxDI8DtB+aps9JLG4tfG6/FoJB8Lfqg96NijfPHHLG2SN7s2vFxexs6x37r8CrhSUUMDS2GNkbSbkMaGgnjkoDQOjHmUTSNLWt90HaTsv8AJWZBlRHtJVOjgDWkgyOw3G0CxJt8rfFSy4NNUBqIcLcntOJt+P8A2JCCnNAGwW8FNezFSWyuh+w5pcBwIIvbxv8Agol8EjThdG8HhhJ/EZKf9ntGvjJmkGEkWa3eBtN+85fJBPLxLE17Sx7Q5rhYgi4I4Fe0QVLT9DTwOYyGCOPGCXFjQCRl1TbdfP4BRTWADCAAOA2K1e0GjnTNa+MXey+XEHaPyVZEMl8OqkxcMP67PxQWL2YqXOjfG431ZGHuab2HwIKxpj2hNNmIsbRK2LNxBc4i5DBbOw38cl06C0e6CIl/vvNzbdwC4/aKhlkqqGZrDJFC9xkY217m2FwB22I8UHW7Ssg0g2lMBDHxlzZb5EjaLd2xSqj6aN8k5nkYWBrSyNrttiQXONtl7Cw4DvsJBAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREGEIWUQYARZRAWFlEGCEAWUQEREGEIHBZRBhZREBYWUQYsOCLKICIiDCYRwWUQYRZRBhZREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERARc9ZWMgYZJLhoyuGl35Bb0GUREBERAREQEREBERAREQEREBFhck+lKaM4XzRtI3Fwv8AJN6WY3LiR2IuWn0jBKbRyseeAcL/ACXSmyyy6rKIiIIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiwiDK01dQ2GJ8rzZjGlzvAC5W1aa2lbPDJE++GRpabbbEWyQQ9Y+ab6Gx9mieVr3MAza1n1lid+YaD4r3HpOoOkG09m4TG+R4tmxt8LMwcydpHeut+jC+VkrpSXMYWWAAGElpNuBOEZ96xLor/SX1Ecro3vYGPsAcgciL7Dn3juQNBVM8sBNQGawSPYcHunC4tuL7slJLVTwtjY1jBZrRYZ3+ZO0962oCLCygIsIgyixiGYvmNqA32IMotVRMI2F7r2FtnjZbUBF5kvhNiAbZEi4HiojRNbVVNO2bFCzGXYQWONwCQD7+8C6CZXl7w0FzjYAXJO4Lg+ly6mEODRPKcPVBwjaS7PcACfGy5faOV2rbEHAXDpHlwvdjBcggEbThHxUt01hj7XTYyN9Z13lzKc+6wHC6QcXnaAeHzUhT0cUQtHGxg+60BRvs5pSWobM2djI5YZMBay9rWBBz+K06Z03LFUU8FO1jnSyasufcgbCbAEXsCCfG3GyRcs7eJxPpK1Oj4JRaSNru+2Y8CMwuPHJSOAke6SncbB7s3Rk7MR3t79ykoy4NbrHNLthIFgT3Ak/mk0TXtcxwBa4EEHeEs+lxz+MuZ+6e1lQ+gqt95KaU3fCbB29zAbAnv2X8QphJds5Y+t0IiKsiIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiDxLHiaW3IuLXabH4Hcoag0XSSPncIIy1smBvV5QMR8cWIfBTa8hgAIaA3adm87/mghxWPdUztMswY2RkbAxjSMRaC7rFhFhcbTuKkGRziHCJGmW5s97bi2I2uGlueGwytmtEGjZI2Pa2a2N7nl2AYruJJtnbK+WW5d8UYY0NbsAsEHFqq3tqf+4d/wBVZ1Vb21P/AHDv+qvVVpCNmsaQ54jbikwi4aLXz77Z2Fz81DQ1EsFHRxta8Szva4kWNrkyvaLnlBCCepWzC+ufG7hgYWW8buddea5pLRZsrs/6JwafjcjJdLTcA2t3HcsoIfVu7Ks/vh61J0wtG3Jwy2PN3fE3K2og45mVRcdXLC1m4Oic4/Eh4/JZgZUh31kkLm8GROafmXn8l1ogqVHDEK+u1jiI4YGwm5s6QPBe5zrWJcSTYjjkp7QVGYKSGI3GFuwm5Fze3wvb4LrdAwuDixpcNjiBceBXtBD6Wjq9S/62DDcZal1/eFs9Z+i7qdlSHfWyRObbYyJzTfxLz+S3zRNe0tcLg/8AdbEEZ7R1epop3A2eWFrOOJ3Vbb4kJQaKbDqMMji2KMtDS64vYAEeADh8V3yQMfbExrrbLgFemMDRZoAA3AWCCPqr/TqXl1cw/wB76u34ByjdPvaayCIuA1rMGZ3axrn/ADa0j4qbrKcvDS2wfG7GwnZexBB7iCR8VxaZgaNXUljXGI3eLAksIs75ZH4KV08fevtGR6yLS9XHGDeoijkBtky3VLj+J7zYLxCI5NNRsY5pjpYDbO5L3nM95INyrSzC4BwsQRt4heGUsTSC2NgI2ENAVc1e9sYA/UNuQZ5o4cR2Ri5cS3LJxsM+4JHWMk0y84rtgibC0A3u95ufkGm/h3KySRteC1zQ4HaCLhaKgwwMMrmtaGN2houBwH+CLJu6iIoLfyrUf1XflDdWFROg6F7A+ab+dmOIjkBJIb45/wCbKWUx6b8t/wBcftcCIirmIiICIiAiIgIiICIiAiIgIiICIiAij9c7mKa5/MUEgij9c/mKa5/MUEgij9c/mKa5/MUEgij9c/mKa5/MUEgij9c/mKa5/MUEgij9c/mKa5/MUEgij9c/mKa5/MUEgij9c/mKa5/MUEgij9c/mKa5/MUEgij9c/mKa5/MUEfLo6f6PVwhhc6eV7i/EACx1hYZ3vg6tjYZbV1TQzGeCTV3axkgDQQMLnFobiz3NBzF963a5/MU1zuYoO9t7C+1ZUfrn8xTXP5igkEUfrn8xTXP5igkEUfrn8xTXP5igkEUfrn8xXPV6QMQF3ZnmNgNgue7MfMIJhFWtJaRqo2AtxSXyOAYLA54gSTcgA5Z7b5KSiqJCLuIBufdNxa+Wdhusgk0Ufrn8xTXP5igkFgi64Nc/mKa5/MUGkRS0hOraZafbgHvx/1eLe7aFvi0zTOy1rWu3tf1SPEFY1zuYrw84vesfEArOrOnX3xy/qcvcumqcGzX6x/LEMZ/D9V4ippZ3tkqGhjGm7Ir3z3Oedl+A3LLHlvu5eAsvWudzFNb7T3mP8xIIo/XP5imufzFac0gij9c/mKa5/MUEgij9c/mKa5/MUEgij9c/iU1z+YoJBFH65/EprncxQSCKP1z+Yprn8xQSCKP1z+YprncxQSCKP1z+Yprn8xQSCKP1z+YrzJVFou59hsuTxyCCSRRkdZiJDX3I2/5+a965/MUHhRdZHUmbWRsIDGhvvN+sBkY51hfLqtcM7bVOatvBNW3ggrE8FSLPkBJcQDazjc5DIfmtupr3FwLywF1wWllx1X5DI5X1e6/grFqxwTVt4IIWjbV652tP1Zabe6bOyta2fMo6GlqYi0FgBOrBdm8veHAl5zOVsRuQCNiterbwTVt4IK4yOvwEmRwIa49bA67sGV8LfdxXIAz/JclOaqZ4H1hwvBBlaB1A6EnMNAOyXZwVu1beCatvBBXYItIYG439Yuwv93qggXe2172INgbe9sXRRNrC2YSuDXEfVk2cGnO+zaB1dtvgprVt4Jq28EEFWUdQ8U5bINbGHEvGTXOwgZjlOY+K4hR1+pMeMtAhAGEt24BliJvixXz2WVq1beCatvBBXjFpDGcL24LkAuw3tYuaTYbyQwjg2+9an0tc+NzXPcAY5AA4sxFxDQ0OLRa19YcrbrqzatvBNW3ggg5GVeoYLnWaw6wsLQS3rWwYhYC+HI52vvXJTR1uUQe5ojEQLgBfPAJGguFjhAeb5+8OCs+rbwTVt4IK3LHpG1mOzEbhclmbrOsT33wbrL2aWsxW1he3HcY8GQEgLTkB9nFfwVh1beCatvBBX6dlaDDiLyAfrQ4x57MwW7tthbfuUwujVt4Jq28EHMi6dW3gmrbwQcyLp1beCatvBBzIunVt4Jq28EHMi6dW3gmrbwQc6itK1ereyzHuBcGOIZcNFw65Lha1gbnd8FO6tvBeXU7CQS25F7fHaggrYXgMIkfneNzw8xmxw2tsHXNydxtwClImYWtbygD5Cy6xE0bBZNW3gg5kXTq28E1beCDmRdOrbwTVt4IOZF06tvBNW3gg5kXTq28E1beCDmRdOrbwTVt4IOZcelYZXxXhtrWODmXNgSMiD8CVK6tvBNW3ggqzKCtia7VvJIcGNNwSYmtdhPWNr4nC/cFsqKevfjAe3J7HMuAG5Pab5G+wG4O1WXVt4Jq28EFf0lSTSwRNDHOlAzcXgFpyvci23i3MbhmpEsl1+LG3U4LYMOeK+2/C25d+rbwTVt4IKvDRVTBeNhjcGkOOMHGS8HEBe2TcW2xzsurR7qrXBkrjhawOebDNxGHBcCxGWLLefgp7Vt4Jq28EEHoynkbLO50ZiDrBgxhwNiescycRvnsyACzVUMslK1kpbLMHNJcOqD1he3+7dTerbwTVt4IK9WQVbtZHHibGA7AWuaDbqYWi+Y2P28VmKKtLzie5rceZuz3cRIw5clgb79isGrbwTVt4IKxNS1xYYx7hjc2wLQLkOsb7Qb4f8VJyUzvpccoJwCN7XDFkDdpbYebNSmrbwTVt4IOZeJ48bS3ZddmrbwTVt4IOCCJwc9z3BxdvAtYC9htPH81vXRq28E1beCD2iIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiDCyvmfSBXckHkPqWOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SD6ai+ZdIFdyQeQ+pOkCu5IPIfUg+movmXSBXckHkPqTpAruSDyH1IPpqL5l0gV3JB5D6k6QK7kg8h9SCqoiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIg/9k=\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"854\"\n",
       "            height=\"480\"\n",
       "            src=\"https://www.youtube.com/embed/p848349hPyw?fs=1\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x7f4e68c80c10>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# @title Video 1: Dynamic networks\n",
    "from IPython.display import YouTubeVideo\n",
    "video = YouTubeVideo(id=\"p848349hPyw\", width=854, height=480, fs=1)\n",
    "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n",
    "video"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "eL6hmfObfQAq"
   },
   "source": [
    "## Section 1.1: Dynamics of a single excitatory population\n",
    "\n",
    "Individual neurons respond by spiking. When we average the spikes of neurons in a population, we can define the average firing activity of the population. In this model, we are interested in how the population-averaged firing varies as a function of time and network parameters. Mathematically, we can describe the firing rate dynamic as:\n",
    "\n",
    "\\begin{align}\n",
    "\\tau \\frac{dr}{dt} &= -r + F(w\\cdot r + I_{\\text{ext}})  \\quad\\qquad (1)\n",
    "\\end{align}\n",
    "\n",
    "$r(t)$ represents the average firing rate of the excitatory population at time $t$, $\\tau$ controls the timescale of the evolution of the average firing rate, $w$ denotes the strength (synaptic weight) of the recurrent input to the population, $I_{\\text{ext}}$ represents the external input, and the transfer function $F(\\cdot)$ (which can be related to f-I curve of individual neurons described in the next sections) represents the population activation function in response to all received inputs.\n",
    "\n",
    "To start building the model, please execute the cell below to initialize the simulation parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "cellView": "form",
    "colab": {},
    "colab_type": "code",
    "id": "bigVVyUhgUTk"
   },
   "outputs": [],
   "source": [
    "# @title Default parameters for a single excitatory population model\n",
    "\n",
    "\n",
    "def default_pars_single(**kwargs):\n",
    "  pars = {}\n",
    "\n",
    "  # Excitatory parameters\n",
    "  pars['tau'] = 1.     # Timescale of the E population [ms]\n",
    "  pars['a'] = 1.2      # Gain of the E population\n",
    "  pars['theta'] = 2.8  # Threshold of the E population\n",
    "\n",
    "  # Connection strength\n",
    "  pars['w'] = 0.  # E to E, we first set it to 0\n",
    "\n",
    "  # External input\n",
    "  pars['I_ext'] = 0.\n",
    "\n",
    "  # simulation parameters\n",
    "  pars['T'] = 20.       # Total duration of simulation [ms]\n",
    "  pars['dt'] = .1       # Simulation time step [ms]\n",
    "  pars['r_init'] = 0.2  # Initial value of E\n",
    "\n",
    "  # External parameters if any\n",
    "  for k in kwargs:\n",
    "    pars[k] = kwargs[k]\n",
    "\n",
    "  # Vector of discretized time points [ms]\n",
    "  pars['range_t'] = np.arange(0, pars['T'], pars['dt'])\n",
    "\n",
    "  return pars\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "UsD-neCVeTGZ"
   },
   "source": [
    "You can use:\n",
    "- `pars = default_pars_single()` to get all the parameters, and then you can execute `print(pars)` to check these parameters. \n",
    "- `pars = default_pars_single(T=T_sim, dt=time_step)` to set new simulation time and time step\n",
    "- After `pars = default_pars_single()`, use `pars['New_para'] = value` to add an new parameter with its value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "6CwsfbhNbND5"
   },
   "source": [
    "## Section 1.2: F-I curves\n",
    "In electrophysiology, a neuron is often characterized by its spike rate output in response to input currents. This is often called the **F-I** curve, denoting the output spike frequency (**F**) in response to different injected currents (**I**). We estimated this for an LIF neuron in yesterday's tutorial.\n",
    "\n",
    "The transfer function $F(\\cdot)$ in Equation $1$ represents the gain of the population as a function of the total input. The gain is often modeled as a sigmoidal function, i.e., more input drive leads to a nonlinear increase in the population firing rate. The output firing rate will eventually saturate for high input values. \n",
    "\n",
    "A sigmoidal $F(\\cdot)$ is parameterized by its gain $a$ and threshold $\\theta$.\n",
    "\n",
    "$$ F(x;a,\\theta) = \\frac{1}{1+\\text{e}^{-a(x-\\theta)}} - \\frac{1}{1+\\text{e}^{a\\theta}}  \\quad(2)$$\n",
    "\n",
    "The argument $x$ represents the input to the population. Note that the second term is chosen so that $F(0;a,\\theta)=0$.\n",
    "\n",
    "Many other transfer functions (generally monotonic) can be also used. Examples are the rectified linear function $ReLU(x)$ or the hyperbolic tangent $tanh(x)$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "poBY4hdb0cuB"
   },
   "source": [
    "### Exercise 1: Implement F-I curve \n",
    "\n",
    "Let's first investigate the activation functions before simulating the dynamics of the entire population. \n",
    "\n",
    "In this exercise, you will implement a sigmoidal **F-I** curve or transfer function $F(x)$, with gain $a$ and threshold level $\\theta$ as parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "QjFIB5n_j5CG"
   },
   "outputs": [],
   "source": [
    "def F(x, a, theta):\n",
    "  \"\"\"\n",
    "  Population activation function.\n",
    "\n",
    "  Args:\n",
    "    x (float): the population input\n",
    "    a (float): the gain of the function\n",
    "    theta (float): the threshold of the function\n",
    "\n",
    "  Returns:\n",
    "    float: the population activation response F(x) for input x\n",
    "  \"\"\"\n",
    "  #################################################\n",
    "  ## TODO for students: compute f = F(x) ##\n",
    "  # Fill out function and remove\n",
    "  raise NotImplementedError(\"Student excercise: implement the f-I function\")\n",
    "  #################################################\n",
    "  # add the expression of f = F(x)\n",
    "  f = ...\n",
    "\n",
    "  return f\n",
    "\n",
    "\n",
    "pars = default_pars_single()  # get default parameters\n",
    "x = np.arange(0, 10, .1)      # set the range of input\n",
    "\n",
    "# Uncomment below to test your function\n",
    "# f = F(x, pars['a'], pars['theta'])\n",
    "\n",
    "# plot_fI(x, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "cellView": "both",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 289
    },
    "colab_type": "code",
    "id": "mEVbZ3kUg4gV",
    "outputId": "40e7f01c-9830-45ed-e948-d699457fc0f6"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 272,
       "width": 416
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# to_remove solution\n",
    "\n",
    "\n",
    "def F(x, a, theta):\n",
    "  \"\"\"\n",
    "  Population activation function.\n",
    "\n",
    "  Args:\n",
    "    x (float): the population input\n",
    "    a (float): the gain of the function\n",
    "    theta (float): the threshold of the function\n",
    "\n",
    "  Returns:\n",
    "    float: the population activation response F(x) for input x\n",
    "  \"\"\"\n",
    "\n",
    "  # add the expression of f = F(x)\n",
    "  f = (1 + np.exp(-a * (x - theta)))**-1 - (1 + np.exp(a * theta))**-1\n",
    "\n",
    "  return f\n",
    "\n",
    "\n",
    "pars = default_pars_single()  # get default parameters\n",
    "x = np.arange(0, 10, .1)      # set the range of input\n",
    "\n",
    "# Uncomment below to test your function\n",
    "f = F(x, pars['a'], pars['theta'])\n",
    "\n",
    "with plt.xkcd():\n",
    "  plot_fI(x, f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "AWn7abgf004N"
   },
   "source": [
    "### Interactive Demo: Parameter exploration of F-I curve\n",
    "Here's an interactive demo that shows how the F-I curve is changing for different values of the gain and threshold parameters.\n",
    "\n",
    "\n",
    "**Remember to enable the demo by running the cell.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 494,
     "referenced_widgets": [
      "3d965eef36fd4909a735ff028bcc0e1d",
      "faf01f26b0674c6386d54c14ef8220ce",
      "1e2b55a8d65a44bcb14c3afda18d28cd",
      "8d0816867ffe407487d90b16fac13b07",
      "2f002382d18a4a1694262a94a7c14fd3",
      "1fa0489a5d684def8fa2a297ea5f753e",
      "265d2564bc7b487d9fb562e66efa3056",
      "8df4e721bda545518bc561f8c7f7044c",
      "a8605133a4794285bf7edd3d896797a5",
      "bf5ce7d822604b80a673cc1d3214ae8f"
     ]
    },
    "colab_type": "code",
    "id": "Ii4dmW7PnX1S",
    "outputId": "6bff419b-eabd-4162-f732-ba5c7e4e0178"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 413,
       "width": 558
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# @title\n",
    "\n",
    "# @markdown Make sure you execute this cell to enable the widget!\n",
    "\n",
    "\n",
    "def interactive_plot_FI(a, theta):\n",
    "  \"\"\"\n",
    "  Population activation function.\n",
    "\n",
    "  Expecxts:\n",
    "    a     : the gain of the function\n",
    "    theta : the threshold of the function\n",
    "\n",
    "  Returns:\n",
    "    plot the F-I curve with give parameters\n",
    "  \"\"\"\n",
    "\n",
    "  # set the range of input\n",
    "  x = np.arange(0, 10, .1)\n",
    "  plt.figure()\n",
    "  plt.plot(x, F(x, a, theta), 'k')\n",
    "  plt.xlabel('x (a.u.)', fontsize=14)\n",
    "  plt.ylabel('F(x)', fontsize=14)\n",
    "  plt.show()\n",
    "\n",
    "\n",
    "_ = widgets.interact(interactive_plot_FI, a=(0.3, 3, 0.3), theta=(2, 4, 0.2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "iqhKlUPYiZMD"
   },
   "source": [
    "## Section 1.3: Simulation scheme of E dynamics\n",
    "\n",
    "Because $F(\\cdot)$ is a nonlinear function, the exact solution of Equation $1$ can not be determined via analytical methods. Therefore, numerical methods must be used to find the solution. In practice, the derivative on the left-hand side of Equation $1$ can be approximated using the Euler method on a time-grid of stepsize $\\Delta t$:\n",
    "\n",
    "\\begin{align}\n",
    "&\\frac{dr}{dt} \\approx \\frac{r[k+1]-r[k]}{\\Delta t} \n",
    "\\end{align}\n",
    "where $r[k] = r(k\\Delta t)$. \n",
    "\n",
    "Thus,\n",
    "\n",
    "$$\\Delta r[k] = \\frac{\\Delta t}{\\tau}[-r[k] + F(w\\cdot r[k] + I_{\\text{ext}}(k;a,\\theta))]$$\n",
    "\n",
    "\n",
    "Hence, Equation (1) is updated at each time step by:\n",
    "\n",
    "$$r[k+1] = r[k] + \\Delta r[k]$$\n",
    "\n",
    "**_Please execute the following cell to enable the WC simulator_**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 294
    },
    "colab_type": "code",
    "id": "W8aIJkkUp-MK",
    "outputId": "9a81e32e-01a4-4426-ca49-bafc09189906"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function simulate_single in module __main__:\n",
      "\n",
      "simulate_single(pars)\n",
      "    Simulate an excitatory population of neurons\n",
      "    \n",
      "    Args:\n",
      "      pars   : Parameter dictionary\n",
      "    \n",
      "    Returns:\n",
      "      rE     : Activity of excitatory population (array)\n",
      "    \n",
      "    Example:\n",
      "      pars = default_pars_single()\n",
      "      r = simulate_single(pars)\n",
      "\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# @title Single population rate model simulator: `simulate_single`\n",
    "\n",
    "\n",
    "def simulate_single(pars):\n",
    "  \"\"\"\n",
    "  Simulate an excitatory population of neurons\n",
    "\n",
    "  Args:\n",
    "    pars   : Parameter dictionary\n",
    "\n",
    "  Returns:\n",
    "    rE     : Activity of excitatory population (array)\n",
    "\n",
    "  Example:\n",
    "    pars = default_pars_single()\n",
    "    r = simulate_single(pars)\n",
    "  \"\"\"\n",
    "\n",
    "  # Set parameters\n",
    "  tau, a, theta = pars['tau'], pars['a'], pars['theta']\n",
    "  w = pars['w']\n",
    "  I_ext = pars['I_ext']\n",
    "  r_init = pars['r_init']\n",
    "  dt, range_t = pars['dt'], pars['range_t']\n",
    "  Lt = range_t.size\n",
    "\n",
    "  # Initialize activity\n",
    "  r = np.zeros(Lt)\n",
    "  r[0] = r_init\n",
    "  I_ext = I_ext * np.ones(Lt)\n",
    "\n",
    "  # Update the E activity\n",
    "  for k in range(Lt - 1):\n",
    "      dr = dt / tau * (-r[k] + F(w * r[k] + I_ext[k], a, theta))\n",
    "      r[k+1] = r[k] + dr\n",
    "\n",
    "  return r\n",
    "\n",
    "\n",
    "print(help(simulate_single))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "gFjFCTCylCBB"
   },
   "source": [
    "### Interactive Demo: Parameter Exploration of single population dynamics\n",
    "\n",
    "Note that $w=0$, as in the default setting, means no recurrent input to the neuron population in Equation (1). Hence, the dynamics is entirely determined by the external input $I_{\\text{ext}}$. Try to explore how $r_{\\text{sim}}(t)$ changes with different $I_{\\text{ext}}$ and $\\tau$ parameter values, and investigate the relationship between $F(I_{\\text{ext}}; a, \\theta)$ and the steady value of $r(t)$. Note that, $r_{\\rm ana}(t)$ denotes the analytical solution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 494,
     "referenced_widgets": [
      "e8f1a7df46e04c01b4cc276d7663e507",
      "27973076c5d2475f8d111ff2ee216eb5",
      "b196d837ae7145d6b0a39894394f317d",
      "362b0f4e1c8648b4b845dc6d177ee2b6",
      "5876e151df074128b5a4bd26d848480a",
      "4c4cf9c06ace43608a51f5cb0aacaa07",
      "43bd841b0d4740efaaee3abcd872c55f",
      "ad0859e74dbc4d0a908de41d0c8ba1ae",
      "079eefba30c4497fa44328dc61d1bbeb",
      "ce205884defa455388f721cbb448463c"
     ]
    },
    "colab_type": "code",
    "id": "-Q-oHxJ-lCTo",
    "outputId": "2835de44-4764-46b4-e76d-1786365f6471"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 413,
       "width": 558
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# @title\n",
    "\n",
    "# @markdown Make sure you execute this cell to enable the widget!\n",
    "\n",
    "# get default parameters\n",
    "pars = default_pars_single(T=20.)\n",
    "\n",
    "\n",
    "def Myplot_E_diffI_difftau(I_ext, tau):\n",
    "  # set external input and time constant\n",
    "  pars['I_ext'] = I_ext\n",
    "  pars['tau'] = tau\n",
    "\n",
    "  # simulation\n",
    "  r = simulate_single(pars)\n",
    "\n",
    "  # Analytical Solution\n",
    "  r_ana = (pars['r_init']\n",
    "           + (F(I_ext, pars['a'], pars['theta'])\n",
    "           - pars['r_init']) * (1. - np.exp(-pars['range_t'] / pars['tau'])))\n",
    "\n",
    "  # plot\n",
    "  plt.figure()\n",
    "  plt.plot(pars['range_t'], r, 'b', label=r'$r_{\\mathrm{sim}}$(t)', alpha=0.5,\n",
    "           zorder=1)\n",
    "  plt.plot(pars['range_t'], r_ana, 'b--', lw=5, dashes=(2, 2),\n",
    "           label=r'$r_{\\mathrm{ana}}$(t)', zorder=2)\n",
    "  plt.plot(pars['range_t'],\n",
    "           F(I_ext, pars['a'], pars['theta']) * np.ones(pars['range_t'].size),\n",
    "           'k--', label=r'$F(I_{\\mathrm{ext}})$')\n",
    "  plt.xlabel('t (ms)', fontsize=16.)\n",
    "  plt.ylabel('Activity r(t)', fontsize=16.)\n",
    "  plt.legend(loc='best', fontsize=14.)\n",
    "  plt.show()\n",
    "\n",
    "\n",
    "_ = widgets.interact(Myplot_E_diffI_difftau, I_ext=(0.0, 10., 1.),\n",
    "                     tau=(1., 5., 0.2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SazqY37rPjG_"
   },
   "source": [
    "## Think!\n",
    "Above, we have numerically solved a system driven by a positive input and that, if $w_{EE} \\neq 0$, receives an excitatory recurrent input (**try changing the value of $w_{EE}$ to a positive number**). Yet, $r_E(t)$ either decays to zero or reaches a fixed non-zero value.\n",
    "- Why doesn't the solution of the system \"explode\" in a finite time? In other words, what guarantees that $r_E$(t) stays finite? \n",
    "- Which parameter would you change in order to increase the maximum value of the response? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kPz152Jr1Ouu"
   },
   "source": [
    "# Section 2: Fixed points of the single population system\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 519
    },
    "colab_type": "code",
    "id": "e28m-dir01ft",
    "outputId": "bbc1fc72-f8bd-4d0c-988f-abefac46063e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Video available at https://youtube.com/watch?v=Ox3ELd1UFyo\n"
     ]
    },
    {
     "data": {
      "image/jpeg": "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\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"854\"\n",
       "            height=\"480\"\n",
       "            src=\"https://www.youtube.com/embed/Ox3ELd1UFyo?fs=1\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x7f4e685a3ed0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# @title Video 2: Fixed point\n",
    "from IPython.display import YouTubeVideo\n",
    "video = YouTubeVideo(id=\"Ox3ELd1UFyo\", width=854, height=480, fs=1)\n",
    "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n",
    "video"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "oLRs3MptqvPQ"
   },
   "source": [
    "As you varied the two parameters in the last Interactive Demo, you noticed that, while at first the system output quickly changes, with time, it reaches its maximum/minimum value and does not change anymore. The value eventually reached by the system is called the **steady state** of the system, or the **fixed point**. Essentially, in the steady states the derivative with respect to time of the activity ($r$) is zero, i.e. $\\displaystyle \\frac{dr}{dt}=0$. \n",
    "\n",
    "We can find that the steady state of the Equation. (1) by setting $\\displaystyle{\\frac{dr}{dt}=0}$ and solve for $r$:\n",
    "\n",
    "$$-r_{\\text{steady}} + F(w\\cdot r_{\\text{steady}} + I_{\\text{ext}};a,\\theta) = 0, \\qquad (3)$$\n",
    "\n",
    "When it exists, the solution of Equation. (3) defines a **fixed point** of the dynamical system Equation. (1). Note that if $F(x)$ is nonlinear, it is not always possible to find an analytical solution, but the solution can be found via numerical simulations, as we will do later.\n",
    "\n",
    "From the Interactive Demo, one could also notice that the value of $\\tau$ influences how quickly the activity will converge to the steady state from its initial value. \n",
    "\n",
    "In the specific case of $w=0$, we can also analytically compute  the solution of Equation (1) (i.e., the thick blue dashed line) and deduce the role of $\\tau$ in determining the convergence to the fixed point: \n",
    "\n",
    "$$\\displaystyle{r(t) = \\big{[}F(I_{\\text{ext}};a,\\theta) -r(t=0)\\big{]} (1-\\text{e}^{-\\frac{t}{\\tau}})} + r(t=0)$$ \\\\\n",
    "\n",
    "We can now numerically calculate the fixed point with the `scipy.optimize.root` function.\n",
    "\n",
    "<font size=3><font color='gray'>_(Recall that at the very beginning, we `import scipy.optimize as opt` )_</font></font>.\n",
    "\n",
    "\\\\\n",
    "\n",
    "Please execute the cell below to define the functions `my_fp_single` and `check_fp_single`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 484
    },
    "colab_type": "code",
    "id": "bF2xtQZt9Qi4",
    "outputId": "4cd44022-4d75-4f70-8e0e-55495fc61074"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function my_fp_single in module __main__:\n",
      "\n",
      "my_fp_single(pars, r_init)\n",
      "    Calculate the fixed point through drE/dt=0\n",
      "    \n",
      "    Args:\n",
      "      pars    : Parameter dictionary\n",
      "      r_init  : Initial value used for scipy.optimize function\n",
      "    \n",
      "    Returns:\n",
      "      x_fp    : value of fixed point\n",
      "\n",
      "None\n",
      "Help on function check_fp_single in module __main__:\n",
      "\n",
      "check_fp_single(pars, x_fp, mytol=0.0001)\n",
      "     Verify |dr/dt| < mytol\n",
      "    \n",
      "    Args:\n",
      "      pars    : Parameter dictionary\n",
      "      fp      : value of fixed point\n",
      "      mytol   : tolerance, default as 10^{-4}\n",
      "    \n",
      "    Returns :\n",
      "      Whether it is a correct fixed point: True/False\n",
      "\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# @title Function of calculating the fixed point\n",
    "\n",
    "# @markdown Make sure you execute this cell to enable the function!\n",
    "\n",
    "\n",
    "def my_fp_single(pars, r_init):\n",
    "  \"\"\"\n",
    "  Calculate the fixed point through drE/dt=0\n",
    "\n",
    "  Args:\n",
    "    pars    : Parameter dictionary\n",
    "    r_init  : Initial value used for scipy.optimize function\n",
    "\n",
    "  Returns:\n",
    "    x_fp    : value of fixed point\n",
    "  \"\"\"\n",
    "\n",
    "  # get the parameters\n",
    "  a, theta = pars['a'], pars['theta']\n",
    "  w = pars['w']\n",
    "  I_ext = pars['I_ext']\n",
    "\n",
    "  # define the right hand of E dynamics\n",
    "  def my_WCr(x):\n",
    "    r = x\n",
    "    drdt = (-r + F(w * r + I_ext, a, theta))\n",
    "    y = np.array(drdt)\n",
    "\n",
    "    return y\n",
    "\n",
    "  x0 = np.array(r_init)\n",
    "  x_fp = opt.root(my_WCr, x0).x\n",
    "\n",
    "  return x_fp\n",
    "\n",
    "\n",
    "print(help(my_fp_single))\n",
    "\n",
    "\n",
    "def check_fp_single(pars, x_fp, mytol=1e-4):\n",
    "  \"\"\"\n",
    "   Verify |dr/dt| < mytol\n",
    "\n",
    "  Args:\n",
    "    pars    : Parameter dictionary\n",
    "    fp      : value of fixed point\n",
    "    mytol   : tolerance, default as 10^{-4}\n",
    "\n",
    "  Returns :\n",
    "    Whether it is a correct fixed point: True/False\n",
    "  \"\"\"\n",
    "\n",
    "  a, theta = pars['a'], pars['theta']\n",
    "  w = pars['w']\n",
    "  I_ext = pars['I_ext']\n",
    "\n",
    "  # calculate Equation(3)\n",
    "  y = x_fp - F(w * x_fp + I_ext, a, theta)\n",
    "\n",
    "  # Here we set tolerance as 10^{-4}\n",
    "  return np.abs(y) < mytol\n",
    "\n",
    "\n",
    "print(help(check_fp_single))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "mDWEXMZKttU7"
   },
   "source": [
    "## Exercise 2: Visualization of the fixed point\n",
    "\n",
    "When it is not possible to find the solution for Equation (3) analytically, a graphical approach can be taken. To that end, it is useful to plot $\\displaystyle{\\frac{dr}{dt}=0}$ as a function of $r$. The values of $r$ for which the plotted function crosses zero on the y axis correspond to fixed points. \n",
    "\n",
    "Here, let us, for example, set $w=5.0$ and $I^{\\text{ext}}=0.5$. From Equation (1), you can obtain\n",
    "\n",
    "$$\\frac{dr}{dt} = [-r + F(w\\cdot r + I^{\\text{ext}})]/\\tau $$\n",
    "\n",
    "Then, plot the $dr/dt$ as a function of $r$, and check for the presence of fixed points. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "ayPQegJprkWu"
   },
   "source": [
    "Finally, try to find the fixed points using the previously defined function `my_fp_single(pars, r_init)` with proper initial values ($r_{\\text{init}}$). You can use the previously defined function `check_fp_single(pars, x_fp)` to verify that the values of $r{\\rm fp}$ for which $\\displaystyle{\\frac{dr}{dt}} = 0$ are the true fixed points. From the line $\\displaystyle{\\frac{dr}{dt}}$ plotted above, the proper initial values can be chosen as the values close to where the line crosses zero on the y axis (real fixed point)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "2H4UHFa3qkjZ"
   },
   "outputs": [],
   "source": [
    "pars = default_pars_single()  # get default parameters\n",
    "\n",
    "# set your external input and wEE\n",
    "pars['I_ext'] = 0.5\n",
    "pars['w'] = 5.0\n",
    "\n",
    "r = np.linspace(0, 1, 1000)  # give the values of r\n",
    "\n",
    "# Calculate drEdt\n",
    "# drdt = ...\n",
    "\n",
    "# Uncomment this to plot the drdt across r\n",
    "# plot_dr_r(r, drdt)\n",
    "\n",
    "################################################################\n",
    "# TODO for students:\n",
    "# Find the values close to the intersections of drdt and y=0\n",
    "# as your initial values\n",
    "# Calculate the fixed point with your initial value, verify them,\n",
    "# and plot the corret ones\n",
    "# check if x_fp is the intersection of the lines with the given function\n",
    "# check_fpE(pars, x_fp)\n",
    "# vary different initial values to find the correct fixed point (Should be 3)\n",
    "# Use blue, red and yellow colors, respectively ('b', 'r', 'y' codenames)\n",
    "################################################################\n",
    "\n",
    "# Calculate the first fixed point with your initial value\n",
    "# x_fp_1 = my_fp_single(pars, ...)\n",
    "# if check_fp_single(pars, x_fp_1):\n",
    "#   plt.plot(x_fp_1, 0, 'bo', ms=8)\n",
    "\n",
    "# Calculate the second fixed point with your initial value\n",
    "# x_fp_2 = my_fp_single(pars, ...)\n",
    "# if check_fp_single(pars, x_fp_2):\n",
    "#   plt.plot(x_fp_2, 0, 'ro', ms=8)\n",
    "\n",
    "# Calculate the third fixed point with your initial value\n",
    "# x_fp_3 = my_fp_single(pars, ...)\n",
    "# if check_fp_single(pars, x_fp_3):\n",
    "#   plt.plot(x_fp_3, 0, 'yo', ms=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 433
    },
    "colab_type": "code",
    "id": "BanscjCer4p8",
    "outputId": "c1cd6110-5f8a-4a8f-d982-d5a39e9c7ac8"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 416,
       "width": 560
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# to_remove solution\n",
    "pars = default_pars_single()  # get default parameters\n",
    "\n",
    "# set your external input and wEE\n",
    "pars['I_ext'] = 0.5\n",
    "pars['w'] = 5.0\n",
    "\n",
    "r = np.linspace(0, 1, 1000)  # give the values of r\n",
    "\n",
    "# Calculate drEdt\n",
    "drdt = (-r + F(pars['w'] * r + pars['I_ext'],\n",
    "               pars['a'], pars['theta'])) / pars['tau']\n",
    "\n",
    "with plt.xkcd():\n",
    "  plot_dr_r(r, drdt)\n",
    "\n",
    "  # Calculate the first fixed point with your initial value\n",
    "  x_fp_1 = my_fp_single(pars, 0.)\n",
    "  if check_fp_single(pars, x_fp_1):\n",
    "    plt.plot(x_fp_1, 0, 'bo', ms=8)\n",
    "\n",
    "  # Calculate the second fixed point with your initial value\n",
    "  x_fp_2 = my_fp_single(pars, 0.4)\n",
    "  if check_fp_single(pars, x_fp_2):\n",
    "    plt.plot(x_fp_2, 0, 'ro', ms=8)\n",
    "\n",
    "  # Calculate the third fixed point with your initial value\n",
    "  x_fp_3 = my_fp_single(pars, 0.9)\n",
    "  if check_fp_single(pars, x_fp_3):\n",
    "    plt.plot(x_fp_3, 0, 'yo', ms=8)\n",
    "\n",
    "  plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "wwNMGXYGBa5l"
   },
   "source": [
    "## Interactive Demo: fixed points as a function of recurrent and external inputs.\n",
    "\n",
    "You can now explore how the previous plot changes when the recurrent coupling $w$ and the external input $I_{\\text{ext}}$ take different values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 494,
     "referenced_widgets": [
      "cbf436d58b84451cb353857b976f6619",
      "8b53efaff39c45f6b269e3fb06814c43",
      "c196f29849bf4937a1b0202c45eebb15",
      "dbc2d44a07c24cba986a1e847a345ff2",
      "97b1221f0fc547f8a2fc28f1df79ee25",
      "8ee452c24b904b198454786a68e1f24d",
      "ddd50ec26da046eeba02b043cafbdc5b",
      "47405460b3724432b451e422667817ee",
      "a9374e2fa5f744ebb47a4cf2706a5888",
      "15b3247ae83243fdb32a564e625f9101"
     ]
    },
    "colab_type": "code",
    "id": "8sg7vgP-lCZG",
    "outputId": "f9704c35-f757-4b43-f7f2-c9a43bcee7ed"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 413,
       "width": 558
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# @title\n",
    "\n",
    "# @markdown Make sure you execute this cell to enable the widget!\n",
    "\n",
    "\n",
    "def plot_intersection_single(w, I_ext):\n",
    "  # set your parameters\n",
    "  pars['w'] = w\n",
    "  pars['I_ext'] = I_ext\n",
    "\n",
    "  # note that wEE!=0\n",
    "  if w > 0:\n",
    "    # find fixed point\n",
    "    x_fp_1 = my_fp_single(pars, 0.)\n",
    "    x_fp_2 = my_fp_single(pars, 0.4)\n",
    "    x_fp_3 = my_fp_single(pars, 0.9)\n",
    "\n",
    "    plt.figure()\n",
    "    r = np.linspace(0, 1., 1000)\n",
    "    drdt = (-r + F(w * r + I_ext, pars['a'], pars['theta'])) / pars['tau']\n",
    "\n",
    "    plt.plot(r, drdt, 'k')\n",
    "    plt.plot(r, 0. * r, 'k--')\n",
    "\n",
    "    if check_fp_single(pars, x_fp_1):\n",
    "        plt.plot(x_fp_1, 0, 'bo', ms=8)\n",
    "    if check_fp_single(pars, x_fp_2):\n",
    "        plt.plot(x_fp_2, 0, 'ro', ms=8)\n",
    "    if check_fp_single(pars, x_fp_3):\n",
    "        plt.plot(x_fp_3, 0, 'yo', ms=8)\n",
    "\n",
    "    plt.xlabel(r'$r$', fontsize=14.)\n",
    "    plt.ylabel(r'$\\frac{dr}{dt}$', fontsize=20.)\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "_ = widgets.interact(plot_intersection_single, w=(1, 7, 0.2),\n",
    "                     I_ext=(0, 3, 0.1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "fyrPM1Jbyo_g"
   },
   "source": [
    "---\n",
    "# Summary\n",
    "\n",
    "In this tutorial, we have investigated the dynamics of a rate-based single population of neurons.\n",
    "\n",
    "We learned about:\n",
    "- The effect of the input parameters and the time constant of the network on the dynamics of the population.\n",
    "- How to find the fixed point(s) of the system.\n",
    "\n",
    "Next, we have two Bonus, but important concepts in dynamical system analysis and simulation. If you have time left, watch the next video and proceed to solve the exercises. You will learn:\n",
    "\n",
    "- How to determine the stability of a fixed point by linearizing the system.\n",
    "- How to add realistic inputs to our model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "aVOG-mq54Rdn"
   },
   "source": [
    "---\n",
    "# Bonus 1: Stability of a fixed point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 519
    },
    "colab_type": "code",
    "id": "ANa4mTHU1bAY",
    "outputId": "7763aa11-d701-4b9a-b155-7c67b8c835fb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Video available at https://youtube.com/watch?v=KKMlWWU83Jg\n"
     ]
    },
    {
     "data": {
      "image/jpeg": "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\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"854\"\n",
       "            height=\"480\"\n",
       "            src=\"https://www.youtube.com/embed/KKMlWWU83Jg?fs=1\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x7f4e68499d90>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# @title Video 3: Stability of fixed points\n",
    "from IPython.display import YouTubeVideo\n",
    "video = YouTubeVideo(id=\"KKMlWWU83Jg\", width=854, height=480, fs=1)\n",
    "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n",
    "video"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "ZBMGFCjICfyn"
   },
   "source": [
    "#### Initial values and trajectories\n",
    "\n",
    "Here, let us first set $w=5.0$ and $I_{\\text{ext}}=0.5$, and investigate the dynamics of $r(t)$ starting with different initial values $r(0) \\equiv r_{\\text{init}}$. We will plot the trajectories of $r(t)$ with $r_{\\text{init}} = 0.0, 0.1, 0.2,..., 0.9$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 358
    },
    "colab_type": "code",
    "id": "-Yxw8Ba0lCOk",
    "outputId": "9de21ea2-45df-4354-d0c0-39fab53f96c1"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 341,
       "width": 557
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# @title Initial values\n",
    "\n",
    "# @markdown Make sure you execute this cell to see the trajectories!\n",
    "\n",
    "pars = default_pars_single()\n",
    "pars['w'] = 5.0\n",
    "pars['I_ext'] = 0.5\n",
    "\n",
    "plt.figure(figsize=(8, 5))\n",
    "for ie in range(10):\n",
    "  pars['r_init'] = 0.1 * ie  # set the initial value\n",
    "  r = simulate_single(pars)  # run the simulation\n",
    "\n",
    "  # plot the activity with given initial\n",
    "  plt.plot(pars['range_t'], r, 'b', alpha=0.1 + 0.1 * ie,\n",
    "           label=r'r$_{\\mathrm{init}}$=%.1f' % (0.1 * ie))\n",
    "\n",
    "plt.xlabel('t (ms)')\n",
    "plt.title('Two steady states?')\n",
    "plt.ylabel(r'$r$(t)')\n",
    "plt.legend(loc=[1.01, -0.06], fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "jpfoNrK-2NXO"
   },
   "source": [
    "## Interactive Demo: dynamics as a function of the initial value\n",
    "\n",
    "Let's now set $r_{\\rm init}$ to a value of your choice in this demo. How does the solution change? What do you observe?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 462,
     "referenced_widgets": [
      "2e985dec15f547b595ae3feafd50ce88",
      "bed72d4b831149209b58e053ec842cff",
      "d9b0e8a78ac04bd4900d4d220f97fa84",
      "f136d3b11ff944ecb7f2ddf68273b237",
      "8dc6502870d64333848a77c523426cdf",
      "72ceefef687443f8a0cf8f00532f0caf",
      "8dc1c02e9b04485f9671bf9111ee306c"
     ]
    },
    "colab_type": "code",
    "id": "-Wxb8d72EUJ1",
    "outputId": "d9e73260-dd63-45af-b038-5cbd48f8bb46"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 413,
       "width": 558
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# @title\n",
    "\n",
    "# @markdown Make sure you execute this cell to enable the widget!\n",
    "\n",
    "pars = default_pars_single()\n",
    "pars['w'] = 5.0\n",
    "pars['I_ext'] = 0.5\n",
    "\n",
    "\n",
    "def plot_single_diffEinit(r_init):\n",
    "  pars['r_init'] = r_init\n",
    "  r = simulate_single(pars)\n",
    "\n",
    "  plt.figure()\n",
    "  plt.plot(pars['range_t'], r, 'b', zorder=1)\n",
    "  plt.plot(0, r[0], 'bo', alpha=0.7, zorder=2)\n",
    "  plt.xlabel('t (ms)', fontsize=16)\n",
    "  plt.ylabel(r'$r(t)$', fontsize=16)\n",
    "  plt.ylim(0, 1.0)\n",
    "  plt.show()\n",
    "\n",
    "\n",
    "_ = widgets.interact(plot_single_diffEinit, r_init=(0, 1, 0.02))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "7GfCUmfPD8AJ"
   },
   "source": [
    "### Stability analysis via linearization of the dynamics\n",
    "\n",
    "Just like Equation $1$ in the case ($w=0$) discussed above, a generic linear system \n",
    "$$\\frac{dx}{dt} = \\lambda (x - b),$$ \n",
    "has a fixed point for $x=b$. The analytical solution of such a system can be found to be:\n",
    "$$x(t) = b + \\big{(} x(0) - b \\big{)} \\text{e}^{\\lambda t}.$$ \n",
    "Now consider a small perturbation of the activity around the fixed point: $x(0) = b+ \\epsilon$, where $|\\epsilon| \\ll 1$. Will the perturbation $\\epsilon(t)$ grow with time or will it decay to the fixed point? The evolution of the perturbation with time can be written, using the analytical solution for $x(t)$, as:\n",
    " $$\\epsilon (t) = x(t) - b = \\epsilon \\text{e}^{\\lambda t}$$\n",
    "\n",
    "- if $\\lambda < 0$, $\\epsilon(t)$ decays to zero, $x(t)$ will still converge to $b$ and the fixed point is \"**stable**\".\n",
    "\n",
    "- if $\\lambda > 0$, $\\epsilon(t)$ grows with time, $x(t)$ will leave the fixed point $b$ exponentially, and the fixed point is, therefore, \"**unstable**\" ."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "We_283Jsww-l"
   },
   "source": [
    "### Compute the stability of Equation $1$\n",
    "\n",
    "Similar to what we did in the linear system above, in order to determine the stability of a fixed point $r^{*}$ of the excitatory population dynamics, we perturb Equation (1) around $r^{*}$ by $\\epsilon$, i.e. $r = r^{*} + \\epsilon$. We can plug in Equation (1) and obtain the equation determining the time evolution of the perturbation $\\epsilon(t)$:\n",
    "\n",
    "\\begin{align}\n",
    "\\tau \\frac{d\\epsilon}{dt} \\approx -\\epsilon + w F'(w\\cdot r^{*} + I_{\\text{ext}};a,\\theta) \\epsilon \n",
    "\\end{align}\n",
    "\n",
    "where $F'(\\cdot)$ is the derivative of the transfer function $F(\\cdot)$. We can rewrite the above equation as:\n",
    "\n",
    "\\begin{align}\n",
    "\\frac{d\\epsilon}{dt} \\approx \\frac{\\epsilon}{\\tau }[-1 + w F'(w\\cdot r^* + I_{\\text{ext}};a,\\theta)] \n",
    "\\end{align}\n",
    "\n",
    "That is, as in the linear system above, the value of\n",
    "\n",
    "$$\\lambda = [-1+ wF'(w\\cdot r^* + I_{\\text{ext}};a,\\theta)]/\\tau \\qquad (4)$$\n",
    "\n",
    "determines whether the perturbation will grow or decay to zero, i.e., $\\lambda$ defines the stability of the fixed point. This value is called the **eigenvalue** of the dynamical system."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "sYvzeee7xXv-"
   },
   "source": [
    "## Exercise 3: Compute $dF$ and Eigenvalue\n",
    "\n",
    "The derivative of the sigmoid transfer function is:\n",
    "\\begin{align} \n",
    "\\frac{dF}{dx} & = \\frac{d}{dx} (1+\\exp\\{-a(x-\\theta)\\})^{-1}  \\\\\n",
    "& = a\\exp\\{-a(x-\\theta)\\} (1+\\exp\\{-a(x-\\theta)\\})^{-2}. \\qquad (5)\n",
    "\\end{align}\n",
    "\n",
    "Let's now find the expression for the derivative $\\displaystyle{\\frac{dF}{dx}}$ in the following cell and plot it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ltwFK_Kr4OMJ"
   },
   "outputs": [],
   "source": [
    "def dF(x, a, theta):\n",
    "  \"\"\"\n",
    "  Population activation function.\n",
    "\n",
    "  Args:\n",
    "    x     : the population input\n",
    "    a     : the gain of the function\n",
    "    theta : the threshold of the function\n",
    "\n",
    "  Returns:\n",
    "    dFdx  : the population activation response F(x) for input x\n",
    "  \"\"\"\n",
    "\n",
    "  #################################################\n",
    "  # TODO for students: compute dFdx ##\n",
    "  raise NotImplementedError(\"Student excercise: compute the deravitive of F\")\n",
    "  #################################################\n",
    "  # Calculate the population activation\n",
    "  dFdx = ...\n",
    "\n",
    "  return dFdx\n",
    "\n",
    "\n",
    "pars = default_pars_single()  # get default parameters\n",
    "x = np.arange(0, 10, .1)      # set the range of input\n",
    "\n",
    "# Uncomment below to test your function\n",
    "# df = dF(x, pars['a'], pars['theta'])\n",
    "\n",
    "# plot_dFdt(x, df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 433
    },
    "colab_type": "code",
    "id": "XnWExh9PHjXx",
    "outputId": "75450f0d-4911-42bd-8a6c-9c75370b3b42"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 416,
       "width": 560
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# to_remove solution\n",
    "def dF(x, a, theta):\n",
    "  \"\"\"\n",
    "  Population activation function.\n",
    "\n",
    "  Args:\n",
    "    x     : the population input\n",
    "    a     : the gain of the function\n",
    "    theta : the threshold of the function\n",
    "\n",
    "  Returns:\n",
    "    dFdx  : the population activation response F(x) for input x\n",
    "  \"\"\"\n",
    "\n",
    "  # Calculate the population activation\n",
    "  dFdx = a * np.exp(-a * (x - theta)) * (1 + np.exp(-a * (x - theta)))**-2\n",
    "\n",
    "  return dFdx\n",
    "\n",
    "\n",
    "pars = default_pars_single()  # get default parameters\n",
    "x = np.arange(0, 10, .1)      # set the range of input\n",
    "\n",
    "df = dF(x, pars['a'], pars['theta'])\n",
    "\n",
    "with plt.xkcd():\n",
    "  plot_dFdt(x, df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "dBj1ptgvI-Wi"
   },
   "source": [
    "## Exercise 4: Compute eigenvalues\n",
    "\n",
    "As discussed above, for the case with $w=5.0$ and $I_{\\text{ext}}=0.5$, the system displays **three** fixed points. However, when we simulated the dynamics and varied the initial conditions $r_{\\rm init}$, we could only obtain **two** steady states. In this exercise, we will now check the stability of each of the three fixed points by calculating the corresponding eigenvalues with the function `eig_single`. Check the sign of each eigenvalue (i.e., stability of each fixed point). How many of the fixed points are stable?\n",
    "\n",
    "Note that the expression of the eigenvalue at fixed point $r^*$\n",
    "$$\\lambda = [-1+ wF'(w\\cdot r^* + I_{\\text{ext}};a,\\theta)]/\\tau$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "aWijQ8UoKToC"
   },
   "outputs": [],
   "source": [
    "def eig_single(pars, fp):\n",
    "  \"\"\"\n",
    "  Args:\n",
    "    pars : Parameter dictionary\n",
    "    fp   : fixed point r_fp\n",
    "\n",
    "  Returns:\n",
    "    eig : eigevalue of the linearized system\n",
    "  \"\"\"\n",
    "\n",
    "  # get the parameters\n",
    "  tau, a, theta = pars['tau'], pars['a'], pars['theta']\n",
    "  w, I_ext = pars['w'], pars['I_ext']\n",
    "  print(tau, a, theta, w, I_ext)\n",
    "\n",
    "  #################################################\n",
    "  ## TODO for students: compute eigenvalue ##\n",
    "  raise NotImplementedError(\"Student excercise: compute the eigenvalue\")\n",
    "  #################################################\n",
    "  # Compute the eigenvalue\n",
    "  eig = ...\n",
    "\n",
    "  return eig\n",
    "\n",
    "\n",
    "pars = default_pars_single()\n",
    "pars['w'] = 5.0\n",
    "pars['I_ext'] = 0.5\n",
    "\n",
    "# Uncomment below lines after completing the eig_single function.\n",
    "# Find the eigenvalues for all fixed points of Exercise 2\n",
    "\n",
    "# x_fp_1 = my_fp_single(pars, 0.).item()\n",
    "# eig_fp_1 = eig_single(pars, x_fp_1).item()\n",
    "# print(f'Fixed point1 at {x_fp_1:.3f} with Eigenvalue={eig_fp_1:.3f}')\n",
    "\n",
    "# x_fp_2 = my_fp_single(pars, 0.4).item()\n",
    "# eig_fp_2 = eig_single(pars, x_fp_2).item()\n",
    "# print(f'Fixed point2 at {x_fp_2:.3f} with Eigenvalue={eig_fp_2:.3f}')\n",
    "\n",
    "# x_fp_3 = my_fp_single(pars, 0.9).item()\n",
    "# eig_fp_3 = eig_single(pars, x_fp_3).item()\n",
    "# print(f'Fixed point3 at {x_fp_3:.3f} with Eigenvalue={eig_fp_3:.3f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "nkqkqk8bZBhx"
   },
   "source": [
    "**SAMPLE OUTPUT**\n",
    "\n",
    "```\n",
    "Fixed point1 at 0.042 with Eigenvalue=-0.583\n",
    "Fixed point2 at 0.447 with Eigenvalue=0.498\n",
    "Fixed point3 at 0.900 with Eigenvalue=-0.626\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 69
    },
    "colab_type": "code",
    "id": "JS--teci4OJP",
    "outputId": "b41d59e4-ac7f-4814-9947-3bad16ebee7e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0 1.2 2.8 5.0 0.5\n",
      "Fixed point1 at 0.042 with Eigenvalue=-0.583\n",
      "1.0 1.2 2.8 5.0 0.5\n",
      "Fixed point2 at 0.447 with Eigenvalue=0.498\n",
      "1.0 1.2 2.8 5.0 0.5\n",
      "Fixed point3 at 0.900 with Eigenvalue=-0.626\n"
     ]
    }
   ],
   "source": [
    "# to_remove solution\n",
    "def eig_single(pars, fp):\n",
    "  \"\"\"\n",
    "  Args:\n",
    "    pars : Parameter dictionary\n",
    "    fp   : fixed point r_fp\n",
    "\n",
    "  Returns:\n",
    "    eig : eigevalue of the linearized system\n",
    "  \"\"\"\n",
    "\n",
    "  # get the parameters\n",
    "  tau, a, theta = pars['tau'], pars['a'], pars['theta']\n",
    "  w, I_ext = pars['w'], pars['I_ext']\n",
    "  print(tau, a, theta, w, I_ext)\n",
    "\n",
    "  # Compute the eigenvalue\n",
    "  eig = (-1. + w * dF(w * fp + I_ext, a, theta)) / tau\n",
    "\n",
    "  return eig\n",
    "\n",
    "\n",
    "pars = default_pars_single()\n",
    "pars['w'] = 5.0\n",
    "pars['I_ext'] = 0.5\n",
    "\n",
    "# Find the eigenvalues for all fixed points of Exercise 2\n",
    "\n",
    "x_fp_1 = my_fp_single(pars, 0.).item()\n",
    "eig_fp_1 = eig_single(pars, x_fp_1).item()\n",
    "print(f'Fixed point1 at {x_fp_1:.3f} with Eigenvalue={eig_fp_1:.3f}')\n",
    "\n",
    "x_fp_2 = my_fp_single(pars, 0.4).item()\n",
    "eig_fp_2 = eig_single(pars, x_fp_2).item()\n",
    "print(f'Fixed point2 at {x_fp_2:.3f} with Eigenvalue={eig_fp_2:.3f}')\n",
    "\n",
    "x_fp_3 = my_fp_single(pars, 0.9).item()\n",
    "eig_fp_3 = eig_single(pars, x_fp_3).item()\n",
    "print(f'Fixed point3 at {x_fp_3:.3f} with Eigenvalue={eig_fp_3:.3f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "CMMC70D0UnOR"
   },
   "source": [
    "## Think! \n",
    "Throughout the tutorial, we have assumed $w> 0 $, i.e., we considered a single population of **excitatory** neurons. What do you think will be the behavior of a population of inhibitory neurons, i.e., where $w> 0$ is replaced by $w< 0$? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "6Yrw1jeTe7Kt"
   },
   "source": [
    "---\n",
    "# Bonus 2: Noisy input drives the transition between two stable states\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "EEeJHvHZfL3d"
   },
   "source": [
    "## Ornstein-Uhlenbeck (OU) process\n",
    "\n",
    "As discussed in several previous tutorials, the OU process is usually used to generate a noisy input into the neuron. The OU input $\\eta(t)$ follows: \n",
    "\n",
    "$$\\tau_\\eta \\frac{d}{dt}\\eta(t) = -\\eta (t) + \\sigma_\\eta\\sqrt{2\\tau_\\eta}\\xi(t)$$\n",
    "\n",
    "Execute the following function `my_OU(pars, sig, myseed=False)` to generate an OU process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 287
    },
    "colab_type": "code",
    "id": "vcr7Og51fIu3",
    "outputId": "238eacae-cdf9-4c42-f1a1-bee11b91a138"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 270,
       "width": 702
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# @title OU process `my_OU(pars, sig, myseed=False)`\n",
    "\n",
    "# @markdown Make sure you execute this cell to visualize the noise!\n",
    "\n",
    "\n",
    "def my_OU(pars, sig, myseed=False):\n",
    "  \"\"\"\n",
    "  A functions that generates Ornstein-Uhlenback process\n",
    "\n",
    "  Args:\n",
    "    pars       : parameter dictionary\n",
    "    sig        : noise amplitute\n",
    "    myseed     : random seed. int or boolean\n",
    "\n",
    "  Returns:\n",
    "    I          : Ornstein-Uhlenbeck input current\n",
    "  \"\"\"\n",
    "\n",
    "  # Retrieve simulation parameters\n",
    "  dt, range_t = pars['dt'], pars['range_t']\n",
    "  Lt = range_t.size\n",
    "  tau_ou = pars['tau_ou']  # [ms]\n",
    "\n",
    "  # set random seed\n",
    "  if myseed:\n",
    "      np.random.seed(seed=myseed)\n",
    "  else:\n",
    "      np.random.seed()\n",
    "\n",
    "  # Initialize\n",
    "  noise = np.random.randn(Lt)\n",
    "  I_ou = np.zeros(Lt)\n",
    "  I_ou[0] = noise[0] * sig\n",
    "\n",
    "  # generate OU\n",
    "  for it in range(Lt - 1):\n",
    "    I_ou[it + 1] = (I_ou[it]\n",
    "                    + dt / tau_ou * (0. - I_ou[it])\n",
    "                    + np.sqrt(2 * dt / tau_ou) * sig * noise[it + 1])\n",
    "\n",
    "  return I_ou\n",
    "\n",
    "\n",
    "pars = default_pars_single(T=100)\n",
    "pars['tau_ou'] = 1.  # [ms]\n",
    "sig_ou = 0.1\n",
    "I_ou = my_OU(pars, sig=sig_ou, myseed=2020)\n",
    "plt.figure(figsize=(10, 4))\n",
    "plt.plot(pars['range_t'], I_ou, 'r')\n",
    "plt.xlabel('t (ms)')\n",
    "plt.ylabel(r'$I_{\\mathrm{OU}}$')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "zJV8UIlZgrh0"
   },
   "source": [
    "## Example: Up-Down transition\n",
    "\n",
    "In the presence of two or more fixed points, noisy inputs can drive a transition between the fixed points! Here, we stimulate an E population for 1,000 ms applying OU inputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "cellView": "form",
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 287
    },
    "colab_type": "code",
    "id": "2ctSJ2E7fRQi",
    "outputId": "3e3cd7cf-b1d5-41e0-9852-499fe31fc913"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 270,
       "width": 702
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# @title Simulation of an E population with OU inputs\n",
    "\n",
    "# @markdown Make sure you execute this cell to spot the Up-Down states!\n",
    "\n",
    "pars = default_pars_single(T=1000)\n",
    "pars['w'] = 5.0\n",
    "sig_ou = 0.7\n",
    "pars['tau_ou'] = 1.  # [ms]\n",
    "pars['I_ext'] = 0.56 + my_OU(pars, sig=sig_ou, myseed=2020)\n",
    "\n",
    "r = simulate_single(pars)\n",
    "\n",
    "plt.figure(figsize=(10, 4))\n",
    "plt.plot(pars['range_t'], r, 'b', alpha=0.8)\n",
    "plt.xlabel('t (ms)')\n",
    "plt.ylabel(r'$r(t)$')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "include_colab_link": true,
   "name": "NeuromatchAcademy_W3D2_Tutorial1",
   "provenance": [],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.8"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "0047b45abad94414ab23f4fa3dce9297": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "SliderStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": "",
       "handle_color": null
      }
     },
     "08012ee4e4a74402be172889e0535e89": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "_dom_classes": [
        "widget-interact"
       ],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "VBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "VBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_18b0e2d8f4024a5d98ef5a8b8af0dabc",
        "IPY_MODEL_5fa7c4ee9d5a41639ae90fc35a3ca3b5",
        "IPY_MODEL_398bff75e20f4fff89b74413816ea949"
       ],
       "layout": "IPY_MODEL_c236b240328b42d2b0eb43da4ddee369"
      }
     },
     "0b05ffeb571f46e1b7b8b2ecb576ee0a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "0b3c487b850346f09783bc6ddafba340": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_a319d6c080744ce09437c243c1b1dbec",
       "msg_id": "",
       "outputs": []
      }
     },
     "0b659107f0b14dc39adb837351a1885b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatSliderModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "FloatSliderView",
       "continuous_update": true,
       "description": "a",
       "description_tooltip": null,
       "disabled": false,
       "layout": "IPY_MODEL_f4d0dfeac14b44de8d334904cefb9953",
       "max": 3.0,
       "min": 0.3,
       "orientation": "horizontal",
       "readout": true,
       "readout_format": ".2f",
       "step": 0.3,
       "style": "IPY_MODEL_2245917ead984717bb0b875515c1da7c",
       "value": 1.5
      }
     },
     "0d54f4e275814865b7d406c0ede3a4ad": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_6dabac8d752445e5ac91897ae7d5bebd",
       "msg_id": "",
       "outputs": []
      }
     },
     "121af53b11254dccb4cd131ddab99058": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "18b0e2d8f4024a5d98ef5a8b8af0dabc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatSliderModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "FloatSliderView",
       "continuous_update": true,
       "description": "I_ext",
       "description_tooltip": null,
       "disabled": false,
       "layout": "IPY_MODEL_9821f318006342c5a00523847af168cc",
       "max": 10.0,
       "min": 0.0,
       "orientation": "horizontal",
       "readout": true,
       "readout_format": ".2f",
       "step": 1.0,
       "style": "IPY_MODEL_59604aced8624bc59cf9445321d42cdd",
       "value": 5.0
      }
     },
     "2245917ead984717bb0b875515c1da7c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "SliderStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": "",
       "handle_color": null
      }
     },
     "31f5f1a7e3194f89a439f26291197744": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "398bff75e20f4fff89b74413816ea949": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_0b05ffeb571f46e1b7b8b2ecb576ee0a",
       "msg_id": "",
       "outputs": []
      }
     },
     "3b8ec557c1ee43ff86ae646b44c73b19": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatSliderModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "FloatSliderView",
       "continuous_update": true,
       "description": "w",
       "description_tooltip": null,
       "disabled": false,
       "layout": "IPY_MODEL_82a0a91649e848949cb3e6970b1b2891",
       "max": 7.0,
       "min": 1.0,
       "orientation": "horizontal",
       "readout": true,
       "readout_format": ".2f",
       "step": 0.2,
       "style": "IPY_MODEL_db551c5ad0714a03bee9730c7d8c8ecc",
       "value": 4.0
      }
     },
     "44b8de00aefd4699b5692904058cd9c3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "SliderStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": "",
       "handle_color": null
      }
     },
     "45fc9bc67d8f49bb9dae917b85e94888": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "SliderStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": "",
       "handle_color": null
      }
     },
     "5408d89d731a4eea9fcbb15e9c492ced": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "SliderStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": "",
       "handle_color": null
      }
     },
     "55c0a9b820154597998a72454065a19a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "59604aced8624bc59cf9445321d42cdd": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "SliderStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": "",
       "handle_color": null
      }
     },
     "5fa7c4ee9d5a41639ae90fc35a3ca3b5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatSliderModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "FloatSliderView",
       "continuous_update": true,
       "description": "tau",
       "description_tooltip": null,
       "disabled": false,
       "layout": "IPY_MODEL_f2f857f0240645fc8e839e50f1883dad",
       "max": 5.0,
       "min": 1.0,
       "orientation": "horizontal",
       "readout": true,
       "readout_format": ".2f",
       "step": 0.2,
       "style": "IPY_MODEL_44b8de00aefd4699b5692904058cd9c3",
       "value": 3.0
      }
     },
     "6dabac8d752445e5ac91897ae7d5bebd": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "82a0a91649e848949cb3e6970b1b2891": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "864ed1229cec4e9697da690bd063f4a1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "9250b3225383401a8a1dd19c94d5fb82": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "_dom_classes": [
        "widget-interact"
       ],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "VBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "VBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_3b8ec557c1ee43ff86ae646b44c73b19",
        "IPY_MODEL_fbc0e00bb3724284b0084a54dc05b892",
        "IPY_MODEL_0d54f4e275814865b7d406c0ede3a4ad"
       ],
       "layout": "IPY_MODEL_31f5f1a7e3194f89a439f26291197744"
      }
     },
     "9821f318006342c5a00523847af168cc": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "a319d6c080744ce09437c243c1b1dbec": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "ab0c6d93562e47168f9392ee4b30d1d9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatSliderModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "FloatSliderView",
       "continuous_update": true,
       "description": "theta",
       "description_tooltip": null,
       "disabled": false,
       "layout": "IPY_MODEL_d656476748d14a5a94390e8158271c42",
       "max": 4.0,
       "min": 2.0,
       "orientation": "horizontal",
       "readout": true,
       "readout_format": ".2f",
       "step": 0.2,
       "style": "IPY_MODEL_5408d89d731a4eea9fcbb15e9c492ced",
       "value": 3.0
      }
     },
     "ac5fa2802dfa433a9f1344992395313d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "_dom_classes": [
        "widget-interact"
       ],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "VBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "VBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_cb4d33ac132c40d4940442e289f76e2c",
        "IPY_MODEL_0b3c487b850346f09783bc6ddafba340"
       ],
       "layout": "IPY_MODEL_d65dbea3300845ae9167831177f5905b"
      }
     },
     "c236b240328b42d2b0eb43da4ddee369": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "c5fb31edfb0a4292b9a63dd6e191f77a": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_864ed1229cec4e9697da690bd063f4a1",
       "msg_id": "",
       "outputs": []
      }
     },
     "cb4d33ac132c40d4940442e289f76e2c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatSliderModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "FloatSliderView",
       "continuous_update": true,
       "description": "r_init",
       "description_tooltip": null,
       "disabled": false,
       "layout": "IPY_MODEL_d2bdbe38ba5f44d4ba75a6463e344ab7",
       "max": 1.0,
       "min": 0.0,
       "orientation": "horizontal",
       "readout": true,
       "readout_format": ".2f",
       "step": 0.02,
       "style": "IPY_MODEL_45fc9bc67d8f49bb9dae917b85e94888",
       "value": 0.0
      }
     },
     "d2bdbe38ba5f44d4ba75a6463e344ab7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "d656476748d14a5a94390e8158271c42": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "d65dbea3300845ae9167831177f5905b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "db551c5ad0714a03bee9730c7d8c8ecc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "SliderStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "SliderStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": "",
       "handle_color": null
      }
     },
     "f2f857f0240645fc8e839e50f1883dad": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "f4d0dfeac14b44de8d334904cefb9953": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "f69fc6cf52484a64969e745ed5fb7762": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "_dom_classes": [
        "widget-interact"
       ],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "VBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "VBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_0b659107f0b14dc39adb837351a1885b",
        "IPY_MODEL_ab0c6d93562e47168f9392ee4b30d1d9",
        "IPY_MODEL_c5fb31edfb0a4292b9a63dd6e191f77a"
       ],
       "layout": "IPY_MODEL_121af53b11254dccb4cd131ddab99058"
      }
     },
     "fbc0e00bb3724284b0084a54dc05b892": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatSliderModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatSliderModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "FloatSliderView",
       "continuous_update": true,
       "description": "I_ext",
       "description_tooltip": null,
       "disabled": false,
       "layout": "IPY_MODEL_55c0a9b820154597998a72454065a19a",
       "max": 3.0,
       "min": 0.0,
       "orientation": "horizontal",
       "readout": true,
       "readout_format": ".2f",
       "step": 0.1,
       "style": "IPY_MODEL_0047b45abad94414ab23f4fa3dce9297",
       "value": 1.0
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}