docs/first-order/classify_waveforms.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classifying Fast-Spiking and Regular-Spiking Neurons\n",
    "\n",
    "In this notebook, we will classify **fast-spiking (FS)** neurons from **regular-spiking (RS)** neurons in visual cortical areas of the mouse brian. We will also visualize the differences between these two types of cells by comparing their peak waveforms and optotagged unit responses. This notebook utilizes open source data from the Allen Institute, but is designed to be customizable with alternative datasets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Environment Setup\n",
    "**⚠️Note: If running on a new environment, run this cell once and then restart the kernel⚠️**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    from databook_utils.dandi_utils import dandi_download_open\n",
    "except:\n",
    "    !git clone https://github.com/AllenInstitute/openscope_databook.git\n",
    "    %cd openscope_databook\n",
    "    %pip install -e ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from databook_utils.dandi_utils import dandi_stream_open\n",
    "from hdmf.common import DynamicTable\n",
    "from pynwb import NWBHDF5IO\n",
    "from pynwb.misc import Units\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Streaming Ecephys Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dandiset_id = \"000021\"\n",
    "dandi_filepath = \"sub-707296975/sub-707296975_ses-721123822.nwb\"\n",
    "dandi_api_key = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\katrina.ager\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\hdmf\\spec\\namespace.py:531: UserWarning: Ignoring cached namespace 'hdmf-common' version 1.1.3 because version 1.6.0 is already loaded.\n",
      "  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n",
      "c:\\Users\\katrina.ager\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\hdmf\\spec\\namespace.py:531: UserWarning: Ignoring cached namespace 'core' version 2.2.2 because version 2.5.0 is already loaded.\n",
      "  warn(\"Ignoring cached namespace '%s' version %s because version %s is already loaded.\"\n"
     ]
    }
   ],
   "source": [
    "# This can sometimes take a while depending on the size of the file\n",
    "io = dandi_stream_open(dandiset_id, dandi_filepath, dandi_api_key=dandi_api_key)\n",
    "nwb = io.read()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Accessing Data Tables\n",
    "Here, we want to access data from the `Units` table of the NWB file. This table contains information about each unit from a given experiment. A unit typically refers to an individual neuron that is recorded during an extracellular electrophysiology experiment. We will also be accessing data from the `Electrodes` table of the NWB file. This table contains information about each electrode (neuropixel probe) that was used during this experiment. This is a useful place to get information about specific channels, or recording sites, that are positioned along the probe. While we will not use every column of data from both of these tables, the relevant data we extract will be explained below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "           amplitude_cutoff  firing_rate  presence_ratio       snr  \\\n",
       "id                                                                   \n",
       "950907203          0.376577     2.533384            0.99  2.830406   \n",
       "950907522          0.022585     0.055246            0.65  0.622514   \n",
       "950907205          0.012123    14.739577            0.99  2.838052   \n",
       "950907520          0.007576     1.098404            0.99  2.423808   \n",
       "950907518          0.075400     0.062280            0.87  2.263385   \n",
       "950907524          0.002313     1.448536            0.99  4.285082   \n",
       "950907209          0.084063     0.040263            0.96  3.343694   \n",
       "950907207          0.500000     0.007849            0.04  1.429174   \n",
       "950907528          0.500000     0.003160            0.29  2.618464   \n",
       "950907526          0.024568     0.376838            0.99  2.697075   \n",
       "\n",
       "           velocity_below  isolation_distance  silhouette_score  \\\n",
       "id                                                                \n",
       "950907203             NaN        6.340840e+01               NaN   \n",
       "950907522             NaN        1.211930e+01               NaN   \n",
       "950907205             NaN        1.291725e+02          0.193312   \n",
       "950907520             NaN        6.282138e+01          0.137635   \n",
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       "950907524        0.686767        5.045019e+01          0.143138   \n",
       "950907209        0.000000        1.992695e+01               NaN   \n",
       "950907207       -1.373534        1.143549e+02               NaN   \n",
       "950907528        0.343384        1.376060e+13               NaN   \n",
       "950907526        0.000000        6.677386e+01          0.092951   \n",
       "\n",
       "           velocity_above  nn_miss_rate  PT_ratio  ...  cluster_id  \\\n",
       "id                                                 ...               \n",
       "950907203        0.073582      0.000781  0.545221  ...           0   \n",
       "950907522       -0.171692      0.001937  0.354055  ...         153   \n",
       "950907205       -0.892797      0.004831  1.054721  ...           1   \n",
       "950907520        0.824121      0.001901  0.456900  ...         152   \n",
       "950907518        0.206030      0.000000  0.434353  ...         151   \n",
       "950907524        0.068677      0.001834  0.558508  ...         154   \n",
       "950907209        0.156975      0.000467  0.637890  ...           3   \n",
       "950907207        1.178950      0.000067  1.086981  ...           2   \n",
       "950907528        0.629537      0.000000  0.551650  ...         156   \n",
       "950907526        0.595198      0.000235  0.576049  ...         155   \n",
       "\n",
       "           waveform_halfwidth  waveform_duration  recovery_slope   amplitude  \\\n",
       "id                                                                             \n",
       "950907203            0.151089           0.274707       -0.044249   45.540300   \n",
       "950907522            0.219765           0.480737       -0.007213   49.501937   \n",
       "950907205            0.109883           0.151089       -0.244173  101.262915   \n",
       "950907520            0.206030           0.329648       -0.053915   85.989735   \n",
       "950907518            0.178559           0.343384       -0.053040   84.470426   \n",
       "950907524            0.164824           0.357119       -0.123923  136.843200   \n",
       "950907209            0.178559           0.343384       -0.115789  114.131278   \n",
       "950907207            0.137353           0.467002       -0.087455   58.044156   \n",
       "950907528            0.164824           0.315913       -0.106002   82.516452   \n",
       "950907526            0.123618           0.219765       -0.086945   85.886190   \n",
       "\n",
       "           spread  isi_violations  \\\n",
       "id                                  \n",
       "950907203    70.0         0.06548   \n",
       "950907522    70.0         0.00000   \n",
       "950907205    40.0         0.00510   \n",
       "950907520    50.0         0.00000   \n",
       "950907518    50.0         0.00000   \n",
       "950907524    60.0         0.00000   \n",
       "950907209    70.0         0.00000   \n",
       "950907207   100.0         0.00000   \n",
       "950907528   110.0         0.00000   \n",
       "950907526   110.0         0.00000   \n",
       "\n",
       "                                                 spike_times  \\\n",
       "id                                                             \n",
       "950907203  [1.8463237565528026, 1.9619905358580827, 2.311...   \n",
       "950907522  [75.19259518261279, 186.3849701306289, 191.589...   \n",
       "950907205  [0.6211892301590656, 0.9079561760850958, 1.081...   \n",
       "950907520  [2.1005573374638606, 3.85505904603257, 4.01682...   \n",
       "950907518  [1.9085904838560483, 5.879527684167119, 31.678...   \n",
       "950907524  [2.348824245897788, 2.5458577711062924, 2.6720...   \n",
       "950907209  [10.606598954149941, 21.535109596551273, 52.97...   \n",
       "950907207  [9220.822768046102, 9221.122635004784, 9221.42...   \n",
       "950907528  [380.3052589740686, 1307.7695954906458, 1546.2...   \n",
       "950907526  [2.2609241602989334, 32.71425381635791, 55.055...   \n",
       "\n",
       "                                            spike_amplitudes  \\\n",
       "id                                                             \n",
       "950907203  [8.327628219252525e-05, 8.367903428567035e-05,...   \n",
       "950907522  [7.996977585316541e-05, 6.97690878117426e-05, ...   \n",
       "950907205  [5.270051606545425e-05, 5.0142859160195626e-05...   \n",
       "950907520  [7.694648306411865e-05, 7.492886255594172e-05,...   \n",
       "950907518  [7.178091557968419e-05, 6.456652055153236e-05,...   \n",
       "950907524  [0.00011948493821011336, 0.0001511098249575643...   \n",
       "950907209  [9.775257470604628e-05, 9.453428297313494e-05,...   \n",
       "950907207  [6.54109900575074e-05, 7.75283889854388e-05, 6...   \n",
       "950907528  [7.262832980570496e-05, 8.690587004932377e-05,...   \n",
       "950907526  [5.304596375917082e-05, 0.00010119436098758314...   \n",
       "\n",
       "                                               waveform_mean  \n",
       "id                                                            \n",
       "950907203  [[0.0, 1.4724449999999971, -0.393510000000004,...  \n",
       "950907522  [[0.0, -1.6420295202952053, 2.3475553505535047...  \n",
       "950907205  [[0.0, -0.9787049999999999, -4.640805000000003...  \n",
       "950907520  [[0.0, -1.4923350000000075, -1.402439999999998...  \n",
       "950907518  [[0.0, -3.4937234042553165, 3.7997872340425505...  \n",
       "950907524  [[0.0, 2.527005000000001, 1.158495000000003, 0...  \n",
       "950907209  [[0.0, 3.588493670886069, 2.7976329113924, 1.2...  \n",
       "950907207  [[0.0, 0.48370129870129897, 2.144999999999998,...  \n",
       "950907528  [[0.0, -13.234838709677422, -15.53080645161290...  \n",
       "950907526  [[0.0, -1.1261249999999983, -2.767439999999997...  \n",
       "\n",
       "[10 rows x 29 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "units = nwb.units\n",
    "units[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "      <th>imp</th>\n",
       "      <th>location</th>\n",
       "      <th>filtering</th>\n",
       "      <th>group</th>\n",
       "      <th>group_name</th>\n",
       "      <th>probe_vertical_position</th>\n",
       "      <th>probe_horizontal_position</th>\n",
       "      <th>probe_id</th>\n",
       "      <th>local_index</th>\n",
       "      <th>valid_data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>850243981</td>\n",
       "      <td>8470.0</td>\n",
       "      <td>3169.0</td>\n",
       "      <td>3169.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>20</td>\n",
       "      <td>43</td>\n",
       "      <td>760213137</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>850243983</td>\n",
       "      <td>8466.0</td>\n",
       "      <td>3160.0</td>\n",
       "      <td>3160.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>20</td>\n",
       "      <td>11</td>\n",
       "      <td>760213137</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
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       "      <td>850243985</td>\n",
       "      <td>8461.0</td>\n",
       "      <td>3152.0</td>\n",
       "      <td>3152.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>40</td>\n",
       "      <td>59</td>\n",
       "      <td>760213137</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>850243987</td>\n",
       "      <td>8456.0</td>\n",
       "      <td>3144.0</td>\n",
       "      <td>3144.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>40</td>\n",
       "      <td>27</td>\n",
       "      <td>760213137</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>850243989</td>\n",
       "      <td>8452.0</td>\n",
       "      <td>3135.0</td>\n",
       "      <td>3135.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>60</td>\n",
       "      <td>43</td>\n",
       "      <td>760213137</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>850243991</td>\n",
       "      <td>8447.0</td>\n",
       "      <td>3127.0</td>\n",
       "      <td>3127.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>60</td>\n",
       "      <td>11</td>\n",
       "      <td>760213137</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>850243993</td>\n",
       "      <td>8442.0</td>\n",
       "      <td>3119.0</td>\n",
       "      <td>3119.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>80</td>\n",
       "      <td>59</td>\n",
       "      <td>760213137</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>850243995</td>\n",
       "      <td>8438.0</td>\n",
       "      <td>3110.0</td>\n",
       "      <td>3110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>80</td>\n",
       "      <td>27</td>\n",
       "      <td>760213137</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>850243997</td>\n",
       "      <td>8433.0</td>\n",
       "      <td>3102.0</td>\n",
       "      <td>3102.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>100</td>\n",
       "      <td>43</td>\n",
       "      <td>760213137</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>850243999</td>\n",
       "      <td>8429.0</td>\n",
       "      <td>3093.0</td>\n",
       "      <td>3093.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MB</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeA abc.EcephysElectrodeGroup at 0x30737366...</td>\n",
       "      <td>probeA</td>\n",
       "      <td>100</td>\n",
       "      <td>11</td>\n",
       "      <td>760213137</td>\n",
       "      <td>9</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id       x       y       z  imp location  \\\n",
       "0  850243981  8470.0  3169.0  3169.0  NaN       MB   \n",
       "1  850243983  8466.0  3160.0  3160.0  NaN       MB   \n",
       "2  850243985  8461.0  3152.0  3152.0  NaN       MB   \n",
       "3  850243987  8456.0  3144.0  3144.0  NaN       MB   \n",
       "4  850243989  8452.0  3135.0  3135.0  NaN       MB   \n",
       "5  850243991  8447.0  3127.0  3127.0  NaN       MB   \n",
       "6  850243993  8442.0  3119.0  3119.0  NaN       MB   \n",
       "7  850243995  8438.0  3110.0  3110.0  NaN       MB   \n",
       "8  850243997  8433.0  3102.0  3102.0  NaN       MB   \n",
       "9  850243999  8429.0  3093.0  3093.0  NaN       MB   \n",
       "\n",
       "                                           filtering  \\\n",
       "0  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "1  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "2  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "3  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "4  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "5  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "6  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "7  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "8  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "9  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "\n",
       "                                               group group_name  \\\n",
       "0  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "1  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "2  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "3  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "4  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "5  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "6  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "7  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "8  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "9  probeA abc.EcephysElectrodeGroup at 0x30737366...     probeA   \n",
       "\n",
       "   probe_vertical_position  probe_horizontal_position   probe_id  local_index  \\\n",
       "0                       20                         43  760213137            0   \n",
       "1                       20                         11  760213137            1   \n",
       "2                       40                         59  760213137            2   \n",
       "3                       40                         27  760213137            3   \n",
       "4                       60                         43  760213137            4   \n",
       "5                       60                         11  760213137            5   \n",
       "6                       80                         59  760213137            6   \n",
       "7                       80                         27  760213137            7   \n",
       "8                      100                         43  760213137            8   \n",
       "9                      100                         11  760213137            9   \n",
       "\n",
       "   valid_data  \n",
       "0        True  \n",
       "1        True  \n",
       "2        True  \n",
       "3        True  \n",
       "4        True  \n",
       "5        True  \n",
       "6        True  \n",
       "7        True  \n",
       "8        True  \n",
       "9        True  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert the electrodes table into a pandas df for easier analysis\n",
    "electrodes = nwb.electrodes\n",
    "electrodes_df = electrodes.to_dataframe()\n",
    "\n",
    "# Reset the index to include it as a regular column\n",
    "electrodes_df.reset_index(inplace=True)\n",
    "\n",
    "electrodes_df[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extracting and Aligning Particular Data From the Tables\n",
    "Now we want to extract and align particular data from the `Units` and `Electrodes` tables from above. There are several criteria that need to be met in order for us to select only select neurons that will be valuable to our analysis: \n",
    "1) **Location**: The tables above contain information from every area of the brain that the probes were inserted into. However, we only want to analyze data that was collected from areas on the probe that were inserted into the visual cortical areas of the mouse brain. For this reason, we create a dictionary called `channel_to_probes_dict` to map each channel of each probe to its position within the brain so we can exclude units that are not from these desired areas. Since the channel location information is stored in the `Electrodes` table, we wrote a function called `get_unit_location` where we can input a `peak_channel_id` from the stimulus table and receive the location of the channel. This function allows us to align data from the `Electrodes` table with data from the `Units` table. We use the `cortex` list to identify which units we want to select for particular coritcal locations in the example below, and exclude any units that are not from these particular locations in the list.\n",
    "2) **Electrode Validity**: The last column of the `Electrodes` table is labeled `valid_data` and tells us if data from a specific channel was valid or not. We only want to include data from channels that are 'True' (valid) for this column. We write a function called `is_electrode_valid` that will create a list of the `id` of each channel that provides valid data, so we can exclude any channel from our analysis that does not meet this criteria.\n",
    "3) **Unit Quality**: One of the columns in the `Units` table called `quality` contains information about the quality of the data of each unit. We only want to include units in our analysis that have 'good' quality and are not 'noise'. To exclude the noisy units, we create a function that will return 'True' only when the unit's quality is 'good'. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a dictionary that maps the id of a channel to its location \n",
    "channel_to_probes_dict = {}\n",
    "\n",
    "for i in range(len(electrodes_df)):\n",
    "    channel_id = electrodes_df['id'][i]\n",
    "    location = electrodes_df['location'][i]\n",
    "    channel_to_probes_dict[channel_id] = location\n",
    "\n",
    "# function aligns location information from electrodes table with channel id from the units table\n",
    "def get_unit_location(peak_id):\n",
    "    return channel_to_probes_dict[peak_id]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# returns a list of channels ids that are valid within electrodes table\n",
    "valid_electrode_ids = []\n",
    "\n",
    "for i, valid in enumerate(electrodes_df['valid_data']): \n",
    "    if valid == True:\n",
    "        valid_electrode_ids.append(electrodes_df['id'][i])\n",
    "\n",
    "valid_electrode_id = set(valid_electrode_ids)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have defined some of the criteria for selecting data, we can combine what we have with some additional filtering criteria into one unified function called `select_unit` that will be used in a for loop below. When data from a specific unit is passed into this function, the function will return 'True' if that unit meets all the defined criteria. This will help us exclude units that do not meet the criteria in the loop below. You can modify this function to fit whatever criteria is most reasonable for your dataset. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "cortex = ['VISrl', 'VISal', 'VISam', 'VISpm', 'VISp', 'VISI']\n",
    "\n",
    "def select_unit(quality_value, units_channel_id, valid_electrode_ids, units_violations, units_amplitude, units_presence):\n",
    "    if (quality_value == 'good' and\n",
    "    get_unit_location(units_channel_id) in cortex and\n",
    "    units_channel_id in valid_electrode_ids and\n",
    "    units_violations < 0.5 and\n",
    "    units_amplitude < 0.1 and\n",
    "    units_presence > 0.95):\n",
    "        return True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the Distribution of Waveform Durations\n",
    "Now that we have all of our unit selection criteria defined and in one function, we need to generate a list of properties from the `Units` table to plot. For this first plot, we want to plot a distribution of `waveform_duration`s for our selected units. Ideally, this will form a bimodal distribution with one peak containing the waveform durations of fast-spiking (FS) neurons and the other containing the durations of regular-spiking (RS) neurons. Characteristically, FS neurons will have shorter spike durations than RS neurons, so they will be represented by the first peak in the distribution. In order to select the `waveform_duration`s for the desired units, we first created a for-loop that loops through the `Units` table and appends the index of a unit when that unit meets the criteria. This list, `selected_unit_indices`, can be used to index specific data from the units table that meets the criteria for all the superseding plots. Next, we create a for-loop that appends a specific unit's `waveform_duration` using the `selected_unit_indices` list. This list of durations called `selected_waveform_durations` is then plotted below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[86, 87, 89, 92, 94, 95, 98, 99, 109, 111, 112, 113, 114, 115, 116, 118, 119, 121, 122, 123, 125, 126, 130, 132, 133, 134, 135, 137, 138, 139, 141, 143, 149, 153, 154, 158, 171, 176, 462, 464, 466, 467, 469, 470, 471, 472, 474, 476, 477, 480, 484, 640, 641, 643, 644, 645, 647, 648, 649, 650, 652, 654, 657, 658, 661, 665, 667, 668, 669, 670, 671, 672, 673, 679, 682, 683, 686, 710, 711, 1097, 1102, 1106, 1110, 1114, 1121, 1129, 1132, 1135, 1136, 1137, 1138, 1141, 1143, 1144, 1145, 1151, 1155, 1156, 1161, 1166, 1172, 1253, 1272, 1274, 1278, 1280, 1286, 1290, 1292, 1293, 1295, 1296, 1305, 1306, 1309, 1379, 1386, 1388, 1389, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1526, 1527, 1528, 1530, 1531, 1533, 1534, 1536, 1537, 1538, 1539, 1540, 1547, 1550, 1552, 1553, 1554, 1556, 1557, 1560, 1561, 1563, 1565, 1567, 1569, 1571, 1572, 1573, 1575, 1580, 1582, 1584, 1589, 1598]\n"
     ]
    }
   ],
   "source": [
    "selected_unit_indices = []\n",
    "\n",
    "# loop that creates a list of units' waveform durations if the unit meets the filtering criteria\n",
    "for i in range(len(units)):\n",
    "    units_channel_id = units['peak_channel_id'][i]\n",
    "    quality_value = units['quality'][i]\n",
    "    units_violations = units['isi_violations'][i]\n",
    "    units_amplitude = units['amplitude_cutoff'][i]\n",
    "    units_presence = units['presence_ratio'][i]\n",
    "\n",
    "    if select_unit(quality_value, units_channel_id, valid_electrode_ids, units_violations, units_amplitude, units_presence) == True: \n",
    "        selected_unit_indices.append(i)\n",
    "\n",
    "print(selected_unit_indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of durations that will be plotted:  161\n"
     ]
    }
   ],
   "source": [
    "selected_waveform_duration = []\n",
    "\n",
    "for i in range(len(units)):\n",
    "    waveform_duration = units['waveform_duration'][i]\n",
    "    if i in selected_unit_indices: \n",
    "        selected_waveform_duration.append(waveform_duration)\n",
    "        \n",
    "print('Number of durations that will be plotted: ', len(selected_waveform_duration))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = selected_waveform_duration\n",
    "bins = np.linspace(0,1.4,1000)\n",
    "hist, bin_edges = np.histogram(data, bins=bins)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(bin_edges[:-1], hist)\n",
    "\n",
    "plt.xlabel(\"Waveform Duration (ms)\")\n",
    "plt.ylabel(\"# units\")\n",
    "plt.title(\"Distribution of Waveform Durations from Visual Coritcal Neurons\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, there are two defined peaks in this bimodal distribution. We want to separate the FS neurons from the RS neurons, and to do so we must select a threshold point. This means that everything to the left of the point has shorter waveform durations and can be classified as FS neuron, and everything to the right of the point has longer waveform duration and can be classified as RS neurons. For the plot above, this threshold point falls around 0.4 ms. The threshold point usually falls in the middle between the two peaks, and, for this plot, can be identified as the space between the 2 distributions that has the fewest number of units (0) for that time in the duration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define the threshold based on the plot above\n",
    "threshold = 0.4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot The Waveform Profile of RS vs FS Neurons\n",
    "Now that we have defined a threshold point that can classify FS neurons from RS neurons, we can plot the unit peak waveforms for each of these two categories and compare them. There are several steps that must be taken in order to do so. The waveform information in the units table is a 2D array that contains many waveforms for an individual unit. In order to select the peak waveform we want to plot from this 2D array, we need to index the array using the `local_index`. However, the local idex data is stored in the electrodes table and not the units table. First, we need to create a dictionary that maps the `id` of each channel in the `electrodes` table to its associated `local_index`. This dictionary is necessary because by mapping the index to the channel ID, we can cross reference the data between the units table and the electodes table based on a specific identifier. Next, we use a for-loop to append the `selected_peak_waveform` to `selected_peak_waveform_rs` if the unit's duration is above the threshold value or `selected_peak_waveform_fs` if the unit's duration is less than the threshold value. We then plot the peak waveforms on top of each other for each type of neuron independently. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a dictionary that maps the channel id to the local index\n",
    "channel_id_to_local_index = {}\n",
    "\n",
    "for i in range(len(nwb.electrodes)):\n",
    "    channel_id_to_local_index[nwb.electrodes['id'][i]] = nwb.electrodes['local_index'][i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[86, 87, 89, 92, 94, 95, 98, 99, 109, 111, 112, 113, 114, 115, 116, 118, 119, 121, 122, 123, 125, 126, 130, 132, 133, 134, 135, 137, 138, 139, 141, 143, 149, 153, 154, 158, 171, 176, 462, 464, 466, 467, 469, 470, 471, 472, 474, 476, 477, 480, 484, 640, 641, 643, 644, 645, 647, 648, 649, 650, 652, 654, 657, 658, 661, 665, 667, 668, 669, 670, 671, 672, 673, 679, 682, 683, 686, 710, 711, 1097, 1102, 1106, 1110, 1114, 1121, 1129, 1132, 1135, 1136, 1137, 1138, 1141, 1143, 1144, 1145, 1151, 1155, 1156, 1161, 1166, 1172, 1253, 1272, 1274, 1278, 1280, 1286, 1290, 1292, 1293, 1295, 1296, 1305, 1306, 1309, 1379, 1386, 1388, 1389, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1526, 1527, 1528, 1530, 1531, 1533, 1534, 1536, 1537, 1538, 1539, 1540, 1547, 1550, 1552, 1553, 1554, 1556, 1557, 1560, 1561, 1563, 1565, 1567, 1569, 1571, 1572, 1573, 1575, 1580, 1582, 1584, 1589, 1598]\n"
     ]
    }
   ],
   "source": [
    "print(selected_unit_indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of RS waveforms to be plotted:  134\n",
      "number of FS waveforms to be plotted:  27\n"
     ]
    }
   ],
   "source": [
    "selected_peak_waveform_rs = []\n",
    "selected_peak_waveform_fs = []\n",
    "\n",
    "for index in selected_unit_indices:\n",
    "    waveform_duration = units['waveform_duration'][index]\n",
    "    unit_mean_waveform = units['waveform_mean'][index]\n",
    "    units_channel_id = units['peak_channel_id'][index]\n",
    "    local_index = channel_id_to_local_index[units_channel_id]\n",
    "    peak_waveform = unit_mean_waveform[local_index]\n",
    "\n",
    "    if waveform_duration > threshold:\n",
    "        selected_peak_waveform_rs.append(peak_waveform)\n",
    "    else: \n",
    "        selected_peak_waveform_fs.append(peak_waveform)\n",
    "        \n",
    "print('number of RS waveforms to be plotted: ', len(selected_peak_waveform_rs))\n",
    "print('number of FS waveforms to be plotted: ', len(selected_peak_waveform_fs))   \n",
    "\n",
    "# convert lists into arrays and transpose for the plots\n",
    "selected_peak_waveform_fs = np.array(selected_peak_waveform_fs).transpose()\n",
    "selected_peak_waveform_rs = np.array(selected_peak_waveform_rs).transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# these will be the same for each unit in this experiment, so we can index the first unit to define these values\n",
    "Hz = list(nwb.devices.values())[0].sampling_rate\n",
    "n_secs = peak_waveform.shape[0] / Hz\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10,6))\n",
    "\n",
    "n_secs = len(selected_peak_waveform_fs[:,0]) / Hz \n",
    "time_axis = np.linspace(0, n_secs * 1000, len(selected_peak_waveform_fs[:,0]))\n",
    "\n",
    "ax.plot(time_axis, selected_peak_waveform_fs)\n",
    "\n",
    "ax.set_xlabel(\"time (ms)\")\n",
    "ax.set_ylabel(\"membrane potential (uV)\")\n",
    "ax.set_title(\"Unit Peak Waveform FS\", fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,6))\n",
    "\n",
    "# can do this because they are all the same length for this dataset \n",
    "n_secs = len(selected_peak_waveform_rs[:,0]) / Hz \n",
    "time_axis = np.linspace(0, n_secs * 1000, len(selected_peak_waveform_rs[:,0]))\n",
    "\n",
    "ax.plot(time_axis, selected_peak_waveform_rs)\n",
    "\n",
    "ax.set_xlabel(\"time (ms)\")\n",
    "ax.set_ylabel(\"membrane potential (uV)\")\n",
    "ax.set_title(\"Unit Peak Waveform RS\", fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}