Figure4_plot_synapses.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fe0e8e02",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "from caveclient import CAVEclient\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0fa76aa4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initialize CAVE client to access dataset \n",
    "\n",
    "client = CAVEclient()\n",
    "\n",
    "if not os.path.isfile(os.path.expanduser(\"~/.cloudvolume/secrets/cave-secret.json\")):\n",
    "    client.auth.get_new_token(open=True)\n",
    "\n",
    "datastack_name = 'fanc_production_mar2021'\n",
    "\n",
    "client = CAVEclient(datastack_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f6195f02",
   "metadata": {},
   "outputs": [],
   "source": [
    "# segids of club neurons grouped by cosine similarity, refer to Figure4_tonotopy python notebook \n",
    "\n",
    "dorsal_club_t1l = [648518346488912397,\n",
    "648518346503137403,\n",
    "648518346499541854,\n",
    "648518346509233018,\n",
    "648518346492002415,\n",
    "648518346494263154,\n",
    "648518346511235381,\n",
    "648518346500706739,\n",
    "648518346531374106,\n",
    "648518346481703327]\n",
    "\n",
    "medial_club_t1l = [648518346517527332,\n",
    "648518346531363354,\n",
    "648518346499840723,\n",
    "648518346488978410,\n",
    "648518346484528131,\n",
    "648518346486545841,\n",
    "648518346490136273,\n",
    "648518346488054046,\n",
    "648518346524142085]\n",
    "\n",
    "ventral_club_t1l = [648518346495414351,\n",
    "648518346481068634,\n",
    "648518346522179866,\n",
    "648518346495765904,\n",
    "648518346511819888,\n",
    "648518346514007065,\n",
    "648518346514428359,\n",
    "648518346494038560,\n",
    "648518346498554608,\n",
    "648518346497858151,\n",
    "648518346482976742,\n",
    "648518346477963245,\n",
    "648518346524144133,\n",
    "648518346472537865,\n",
    "648518346487705300,\n",
    "648518346499385438,\n",
    "648518346503767201,\n",
    "648518346499893315]\n",
    "\n",
    "# T2R \n",
    "dorsal_club_t2r = [648518346483806357,\n",
    "648518346478167277,\n",
    "648518346492356223,\n",
    "648518346475974370,\n",
    "648518346488045079,\n",
    "648518346499960531,\n",
    "648518346518565462]\n",
    "\n",
    "medial_club_t2r = [648518346493225392,\n",
    "648518346474234477,\n",
    "648518346502655814]\n",
    "\n",
    "ventral_club_t2r = [648518346495993163,\n",
    "648518346492913070,\n",
    "648518346477811470,\n",
    "648518346494998706]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8f08e788",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/ds/x7td6nf906g264l63pfg2zz40000gn/T/ipykernel_88509/825192305.py:28: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  t1l_club_df['cos_group'] = t1l_cos_group\n",
      "/var/folders/ds/x7td6nf906g264l63pfg2zz40000gn/T/ipykernel_88509/825192305.py:45: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  t2r_club_df['cos_group'] = t2r_cos_group\n"
     ]
    }
   ],
   "source": [
    "# import and organize data for each club group (T1L/T2R, dorsal/medial/ventral) from the feco_axons_v0 annotation table \n",
    "\n",
    "# import entire feco_axons_vo table \n",
    "feco_df_all = client.materialize.query_table('feco_axons_v0') \n",
    "\n",
    "# separate out T1L and T2R club neurons \n",
    "t1l_club_df = feco_df_all[(feco_df_all.cell_type.str.contains('club')) & (feco_df_all.classification_system == 'T1L')]\n",
    "t2r_club_df = feco_df_all[(feco_df_all.cell_type.str.contains('club')) & (feco_df_all.classification_system == 'T2R')]\n",
    "\n",
    "# create a new column in the dataframes to identify whether the club neuron is dorsal/medial/ventral \n",
    "t1l_cos_group = [] \n",
    "t2r_cos_group = []\n",
    "\n",
    "for id in t1l_club_df.pt_root_id: \n",
    "    \n",
    "    if id in dorsal_club_t1l: \n",
    "        t1l_cos_group.append('dorsal')\n",
    "        \n",
    "    elif id in medial_club_t1l: \n",
    "        t1l_cos_group.append('medial')\n",
    "        \n",
    "    elif id in ventral_club_t1l: \n",
    "        t1l_cos_group.append('ventral')\n",
    "    \n",
    "    else: \n",
    "        t1l_cos_group.append('other')\n",
    "        \n",
    "t1l_club_df['cos_group'] = t1l_cos_group \n",
    "        \n",
    "\n",
    "for id in t2r_club_df.pt_root_id: \n",
    "    \n",
    "    if id in dorsal_club_t2r: \n",
    "        t2r_cos_group.append('dorsal')\n",
    "        \n",
    "    elif id in medial_club_t2r: \n",
    "        t2r_cos_group.append('medial')\n",
    "        \n",
    "    elif id in ventral_club_t2r: \n",
    "        t2r_cos_group.append('ventral')\n",
    "    \n",
    "    else: \n",
    "        t2r_cos_group.append('other')\n",
    "        \n",
    "t2r_club_df['cos_group'] = t2r_cos_group \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "54a369b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# functions to generate postsynaptic synapse positions of each club cosine group \n",
    "\n",
    "def get_synapses(threshold, inputs):\n",
    "\n",
    "    upstream = False\n",
    "    syn_thresh = threshold \n",
    "    if upstream == True:\n",
    "        syn_df = client.materialize.synapse_query(post_ids = inputs)\n",
    "    else:\n",
    "        syn_df = client.materialize.synapse_query(pre_ids = inputs)\n",
    "\n",
    "    synapse_df = filt_syn_df(syn_df, syn_thresh)\n",
    "\n",
    "    x_synapses = [] \n",
    "    y_synapses = [] \n",
    "    z_synapses = [] \n",
    "    neuron_idx = [] \n",
    "\n",
    "    counter = 0\n",
    "\n",
    "    for idx in inputs:      \n",
    "        if upstream == True:\n",
    "            syn_df = client.materialize.synapse_query(post_ids = idx) # create synapse df for each segid \n",
    "        else:\n",
    "            syn_df = client.materialize.synapse_query(pre_ids = idx)\n",
    "\n",
    "        synapse_df = filt_syn_df(syn_df, syn_thresh)\n",
    "        synapse_df = synapse_df.reset_index()\n",
    "        neuron_idx.extend(np.ones(len(synapse_df)) * counter) # create neuron index to reference later \n",
    "        counter = counter + 1 \n",
    "\n",
    "        for synapse in range(0, len(synapse_df)): \n",
    "            if upstream == True: \n",
    "                x_synapses.append(synapse_df.pre_pt_position[synapse][0]) # fill x,y,z synapse positions \n",
    "                y_synapses.append(synapse_df.pre_pt_position[synapse][1]) \n",
    "                z_synapses.append(synapse_df.pre_pt_position[synapse][2]) \n",
    "\n",
    "            else: \n",
    "                x_synapses.append(synapse_df.post_pt_position[synapse][0]) \n",
    "                y_synapses.append(synapse_df.post_pt_position[synapse][1]) \n",
    "                z_synapses.append(synapse_df.post_pt_position[synapse][2]) \n",
    "\n",
    "\n",
    "    # Create dataframe for plotting \n",
    "    synapse_hist = {'x_synapses': x_synapses,\n",
    "                    'y_synapses': y_synapses, \n",
    "                    'z_synapses': z_synapses, \n",
    "                    'neuron' : neuron_idx}\n",
    "\n",
    "    # Create DataFrame\n",
    "    synapse_hist_df = pd.DataFrame(synapse_hist)\n",
    "    \n",
    "    return synapse_hist_df\n",
    "\n",
    "# filter function to constrain to partners that make threshold number of synapses \n",
    "\n",
    "def filt_syn_df(syn_df, syn_thresh):\n",
    "    \n",
    "    indices_to_include = []\n",
    "\n",
    "    # Find unique presynaptic neurons\n",
    "    unique_pre_ids = syn_df.pre_pt_root_id.unique().tolist()\n",
    "\n",
    "    # Loop through presynaptic neurons\n",
    "    for i in unique_pre_ids:       \n",
    "        pre_df = syn_df[syn_df.pre_pt_root_id == i]\n",
    "        # Find unique postsynaptic neurons targeted by i-th presynaptic neuron\n",
    "        unique_post_ids = pre_df.post_pt_root_id.unique().tolist() \n",
    "        # Loop through postsynaptic neurons\n",
    "        for j in unique_post_ids:    \n",
    "            # Is number of synapses onto j-th postsynaptic neuron larger than or equal to syn_thresh? \n",
    "            if sum(pre_df.post_pt_root_id == j) >= syn_thresh: \n",
    "                # Get indices (rows)\n",
    "                indices = pre_df.index.values[pre_df.post_pt_root_id == j]       \n",
    "                # Loop through indices \n",
    "                for k in indices:\n",
    "                    # Append each index separately to avoid lists within list\n",
    "                    indices_to_include.append(k)\n",
    "\n",
    "    # Sort indices in ascending order\n",
    "    indices_to_include.sort()\n",
    "    \n",
    "    # Create new syn_df with only connections above syn_thresh\n",
    "    syn_df_filt = syn_df.loc[indices_to_include]\n",
    "    \n",
    "    return syn_df_filt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "eac56769",
   "metadata": {},
   "outputs": [],
   "source": [
    "# get postsynaptic synapse positions for each club group \n",
    "\n",
    "dorsal_t1l_hist_df = get_synapses(3, t1l_club_df[t1l_club_df.cos_group == 'dorsal'].pt_root_id.tolist())\n",
    "medial_t1l_hist_df = get_synapses(3, t1l_club_df[t1l_club_df.cos_group == 'medial'].pt_root_id.tolist())\n",
    "ventral_t1l_hist_df = get_synapses(3, t1l_club_df[t1l_club_df.cos_group == 'ventral'].pt_root_id.tolist())\n",
    "\n",
    "dorsal_t2r_hist_df = get_synapses(3, t2r_club_df[t2r_club_df.cos_group == 'dorsal'].pt_root_id.tolist())\n",
    "medial_t2r_hist_df = get_synapses(3, t2r_club_df[t2r_club_df.cos_group == 'medial'].pt_root_id.tolist())\n",
    "ventral_t2r_hist_df = get_synapses(3, t2r_club_df[t2r_club_df.cos_group == 'ventral'].pt_root_id.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "4d5b215b",
   "metadata": {},
   "outputs": [
    {
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       "<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x1599677c0>"
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     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
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     "data": {
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\n",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot synapses \n",
    "\n",
    "# T1L \n",
    "fig = plt.figure(figsize = (8,8)) \n",
    "ax = plt.axes(projection =\"3d\")\n",
    "ax.set_axis_off()\n",
    "\n",
    "ax.scatter3D(dorsal_t1l_hist_df.x_synapses, dorsal_t1l_hist_df.y_synapses, dorsal_t1l_hist_df.z_synapses, color='#36c6f4',alpha = 0.2)\n",
    "ax.scatter3D(medial_t1l_hist_df.x_synapses, medial_t1l_hist_df.y_synapses, medial_t1l_hist_df.z_synapses, color = '#83c54d',alpha = 0.3)\n",
    "ax.scatter3D(ventral_t1l_hist_df.x_synapses, ventral_t1l_hist_df.y_synapses, ventral_t1l_hist_df.z_synapses, color = '#CC6699',alpha = 0.2)\n",
    "\n",
    "\n",
    "#T2R \n",
    "fig = plt.figure(figsize = (8,8)) \n",
    "ax = plt.axes(projection =\"3d\")\n",
    "ax.set_axis_off()\n",
    "\n",
    "# Creating plot\n",
    "ax.scatter3D(dorsal_t2r_hist_df.x_synapses, dorsal_t2r_hist_df.y_synapses, dorsal_t2r_hist_df.z_synapses, color='#6AA4BC',alpha = 0.2)\n",
    "ax.scatter3D(medial_t2r_hist_df.x_synapses, medial_t2r_hist_df.y_synapses, medial_t2r_hist_df.z_synapses, color = '#708D51',alpha = 0.3)\n",
    "ax.scatter3D(ventral_t2r_hist_df.x_synapses, ventral_t2r_hist_df.y_synapses, ventral_t2r_hist_df.z_synapses, color = '#854E6B',alpha = 0.2)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}