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spike lfp analysis
2019-10-17 17:44:01 +00:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
new selection of grid cells color changes and histogram overview of change
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"16:00:32 [I] klustakwik KlustaKwik2 version 0.2.6\n"
spike lfp analysis
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]
}
],
"source": [
"import os\n",
"import expipe\n",
"import pathlib\n",
"import numpy as np\n",
"import spatial_maps.stats as stats\n",
"import septum_mec\n",
"import septum_mec.analysis.data_processing as dp\n",
"import septum_mec.analysis.registration\n",
"import head_direction.head as head\n",
"import spatial_maps as sp\n",
"import speed_cells.speed as spd\n",
"import re\n",
"import joblib\n",
"import multiprocessing\n",
"import shutil\n",
"import psutil\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib\n",
"import seaborn as sns\n",
"from distutils.dir_util import copy_tree\n",
"from neo import SpikeTrain\n",
"import scipy\n",
"\n",
"from tqdm import tqdm_notebook as tqdm\n",
"from tqdm._tqdm_notebook import tqdm_notebook\n",
"tqdm_notebook.pandas()\n",
"\n",
"from spike_statistics.core import permutation_resampling\n",
"\n",
"from spikewaveform.core import calculate_waveform_features_from_template, cluster_waveform_features\n",
"\n",
new selection of grid cells color changes and histogram overview of change
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"from septum_mec.analysis.plotting import violinplot, despine"
spike lfp analysis
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]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"plt.rc('axes', titlesize=12)\n",
"plt.rcParams.update({\n",
" 'font.size': 12, \n",
" 'figure.figsize': (6, 4), \n",
" 'figure.dpi': 150\n",
"})\n",
"\n",
"output_path = pathlib.Path(\"output\") / \"stimulus-spike-lfp-response\"\n",
"(output_path / \"statistics\").mkdir(exist_ok=True, parents=True)\n",
"(output_path / \"figures\").mkdir(exist_ok=True, parents=True)\n",
"output_path.mkdir(exist_ok=True)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"data_loader = dp.Data()\n",
"actions = data_loader.actions\n",
"project = data_loader.project"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"identification_action = actions['identify-neurons']\n",
"sessions = pd.read_csv(identification_action.data_path('sessions'))\n",
"units = pd.read_csv(identification_action.data_path('units'))\n",
"session_units = pd.merge(sessions, units, on='action')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"lfp_action = actions['stimulus-spike-lfp-response']\n",
"lfp_results = pd.read_csv(lfp_action.data_path('results'))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# lfp_results has old unit id's but correct on (action, unit_name, channel_group)\n",
"lfp_results = lfp_results.drop('unit_id', axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
new selection of grid cells color changes and histogram overview of change
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"source": [
"stim_action = actions['stimulus-response']\n",
"stim_results = pd.read_csv(stim_action.data_path('results'))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# lfp_results has old unit id's but correct on (action, unit_name, channel_group)\n",
"stim_results = stim_results.drop('unit_id', axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
spike lfp analysis
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"source": [
"statistics_action = actions['calculate-statistics']\n",
"shuffling = actions['shuffling']\n",
"\n",
"statistics_results = pd.read_csv(statistics_action.data_path('results'))\n",
"statistics_results = session_units.merge(statistics_results, how='left')\n",
"quantiles_95 = pd.read_csv(shuffling.data_path('quantiles_95'))\n",
"action_columns = ['action', 'channel_group', 'unit_name']\n",
"data = pd.merge(statistics_results, quantiles_95, on=action_columns, suffixes=(\"\", \"_threshold\"))"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 11,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"data['unit_day'] = data.apply(lambda x: str(x.unit_idnum) + '_' + x.action.split('-')[1], axis=1)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 12,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"data = data.merge(lfp_results, how='left')"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"data = data.merge(stim_results, how='left')"
]
},
{
"cell_type": "code",
"execution_count": 14,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"waveform_action = actions['waveform-analysis']\n",
"waveform_results = pd.read_csv(waveform_action.data_path('results')).drop('template', axis=1)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 15,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"data = data.merge(waveform_results, how='left')"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 16,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"colors = ['#1b9e77','#d95f02','#7570b3','#e7298a']\n",
"labels = ['Baseline I', '11 Hz', 'Baseline II', '30 Hz']\n",
"queries = ['baseline and Hz11', 'frequency==11', 'baseline and Hz30', 'frequency==30']"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 17,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"data.bs = data.bs.astype(bool)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"data.loc[data.eval('not t_i_peak.isnull() and not bs'), 'ns_inhibited'] = True\n",
"data.ns_inhibited.fillna(False, inplace=True)\n",
"\n",
"data.loc[data.eval('t_i_peak.isnull() and not bs'), 'ns_not_inhibited'] = True\n",
"data.ns_not_inhibited.fillna(False, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"# make baseline for inhibited vs not inhibited\n",
"data.loc[data.unit_id.isin(data.query('ns_inhibited').unit_id.values), 'ns_inhibited'] = True\n",
"data.loc[data.unit_id.isin(data.query('ns_not_inhibited').unit_id.values), 'ns_not_inhibited'] = True"
]
},
{
"cell_type": "code",
"execution_count": 20,
spike lfp analysis
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of gridcells 225\n"
]
}
],
"source": [
new selection of grid cells color changes and histogram overview of change
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"query = (\n",
" 'gridness > gridness_threshold and '\n",
" 'information_rate > information_rate_threshold and '\n",
" 'gridness > .2 and '\n",
" 'average_rate < 25'\n",
")\n",
"sessions_above_threshold = data.query(query)\n",
"print(\"Number of sessions above threshold\", len(sessions_above_threshold))\n",
"print(\"Number of animals\", len(sessions_above_threshold.groupby(['entity'])))"
spike lfp analysis
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]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 21,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"gridcell_sessions = data[data.unit_day.isin(sessions_above_threshold.unit_day.values)]"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 22,
spike lfp analysis
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"metadata": {},
"outputs": [
{
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" <th></th>\n",
" <th>action</th>\n",
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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" <th>ns_not_inhibited</th>\n",
spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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" <td>0.0008</td>\n",
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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" <td>NaN</td>\n",
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new selection of grid cells color changes and histogram overview of change
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spike lfp analysis
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" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
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" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>True</td>\n",
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" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.259920</td>\n",
" <td>0.581698</td>\n",
" <td>5.891739</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.263630</td>\n",
" <td>0.596746</td>\n",
" <td>13.436847</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.281399</td>\n",
" <td>0.607354</td>\n",
" <td>17.446704</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.285816</td>\n",
" <td>0.603160</td>\n",
" <td>7.914246</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.279177</td>\n",
" <td>0.585152</td>\n",
" <td>10.840470</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>49</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.282336</td>\n",
" <td>0.711705</td>\n",
" <td>5.890705</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>54</th>\n",
" <td>1839-060619-3</td>\n",
" <td>False</td>\n",
" <td>1839</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>3</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>0.270286</td>\n",
" <td>0.573804</td>\n",
" <td>14.025342</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td>1834-150319-3</td>\n",
" <td>True</td>\n",
" <td>1834</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.277867</td>\n",
" <td>0.588852</td>\n",
" <td>17.162446</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>76</th>\n",
" <td>1834-120319-4</td>\n",
" <td>False</td>\n",
" <td>1834</td>\n",
" <td>30.0</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>4</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim ii</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>0.0044</td>\n",
" <td>0.018315</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>0.285028</td>\n",
" <td>0.578245</td>\n",
" <td>34.841257</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>87</th>\n",
" <td>1849-280219-4</td>\n",
" <td>False</td>\n",
" <td>1849</td>\n",
" <td>30.0</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>4</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim ii</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>0.272793</td>\n",
" <td>0.570844</td>\n",
" <td>10.825754</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>106</th>\n",
" <td>1849-110319-2</td>\n",
" <td>False</td>\n",
" <td>1849</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>0.0026</td>\n",
" <td>0.002400</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>0.230947</td>\n",
" <td>0.561223</td>\n",
" <td>2.339767</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.271262</td>\n",
" <td>0.615002</td>\n",
" <td>2.868000</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>125</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.307694</td>\n",
" <td>0.659653</td>\n",
" <td>6.912052</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>126</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.267708</td>\n",
" <td>0.630543</td>\n",
" <td>4.229867</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.289100</td>\n",
" <td>0.673221</td>\n",
" <td>16.735961</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>129</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.290402</td>\n",
" <td>0.650772</td>\n",
" <td>25.974728</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>131</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.272160</td>\n",
" <td>0.620429</td>\n",
" <td>14.686236</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>132</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.241405</td>\n",
" <td>0.595513</td>\n",
" <td>18.657578</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>134</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.269911</td>\n",
" <td>0.609574</td>\n",
" <td>3.106903</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>135</th>\n",
" <td>1833-010719-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.273069</td>\n",
" <td>0.651265</td>\n",
" <td>6.213807</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1154</th>\n",
" <td>1839-120619-3</td>\n",
" <td>True</td>\n",
" <td>1839</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.273572</td>\n",
" <td>0.611548</td>\n",
" <td>5.407135</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1155</th>\n",
" <td>1834-110319-5</td>\n",
" <td>False</td>\n",
" <td>1834</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>5</td>\n",
" <td>mecl</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>0.276394</td>\n",
" <td>0.585645</td>\n",
" <td>27.008837</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1156</th>\n",
" <td>1834-110319-5</td>\n",
" <td>False</td>\n",
" <td>1834</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>5</td>\n",
" <td>mecl</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>0.249700</td>\n",
" <td>0.569364</td>\n",
" <td>18.304313</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1174</th>\n",
" <td>1839-200619-2</td>\n",
" <td>False</td>\n",
" <td>1839</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>0.249357</td>\n",
" <td>0.517805</td>\n",
" <td>8.992236</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1184</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.275930</td>\n",
" <td>0.594526</td>\n",
" <td>5.288548</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1185</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.225575</td>\n",
" <td>0.277528</td>\n",
" <td>2.693978</td>\n",
" <td>False</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>True</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1186</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.244049</td>\n",
" <td>0.571337</td>\n",
" <td>3.425185</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1189</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.222604</td>\n",
" <td>0.576271</td>\n",
" <td>6.484767</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>True</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1191</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.189559</td>\n",
" <td>0.248665</td>\n",
" <td>3.564358</td>\n",
" <td>False</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>True</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1193</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.257469</td>\n",
" <td>0.636957</td>\n",
" <td>26.839270</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1194</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.252255</td>\n",
" <td>0.587372</td>\n",
" <td>4.589373</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1197</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.261129</td>\n",
" <td>0.592306</td>\n",
" <td>7.407060</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1199</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.277189</td>\n",
" <td>0.615988</td>\n",
" <td>9.221822</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1202</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.287132</td>\n",
" <td>0.616235</td>\n",
" <td>7.835622</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1204</th>\n",
" <td>1833-260619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.300175</td>\n",
" <td>0.610068</td>\n",
" <td>9.358786</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1208</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.293775</td>\n",
" <td>0.657679</td>\n",
" <td>7.071948</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1214</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.252895</td>\n",
" <td>0.600200</td>\n",
" <td>15.695836</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1215</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.271023</td>\n",
" <td>0.699617</td>\n",
" <td>11.768979</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1217</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.343906</td>\n",
" <td>0.698383</td>\n",
" <td>4.442023</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1218</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.304748</td>\n",
" <td>0.641151</td>\n",
" <td>3.102590</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1219</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.277708</td>\n",
" <td>0.585645</td>\n",
" <td>6.900656</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1220</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.294291</td>\n",
" <td>0.639177</td>\n",
" <td>22.458685</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1221</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.258204</td>\n",
" <td>0.608094</td>\n",
" <td>3.767155</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" </tr>\n",
" <tr>\n",
" <th>1223</th>\n",
" <td>1833-200619-3</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline ii</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.276894</td>\n",
" <td>0.623636</td>\n",
" <td>12.778706</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>1255</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
" <td>1833</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
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" <td>0.277537</td>\n",
" <td>0.570597</td>\n",
" <td>5.734302</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>1257</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
" <td>1833</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
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" <td>0.248774</td>\n",
" <td>0.604394</td>\n",
" <td>2.814742</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>1263</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
" <td>1833</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
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" <td>0.280033</td>\n",
" <td>0.560729</td>\n",
" <td>4.760330</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>1264</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
" <td>1833</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
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" <td>0.281934</td>\n",
" <td>0.627089</td>\n",
" <td>15.890929</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>1268</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
" <td>1833</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
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" <td>0.266512</td>\n",
" <td>0.594033</td>\n",
" <td>2.704037</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>1275</th>\n",
" <td>1833-010719-2</td>\n",
" <td>False</td>\n",
" <td>1833</td>\n",
" <td>11.0</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2</td>\n",
" <td>ms</td>\n",
" <td>True</td>\n",
" <td>stim i</td>\n",
" <td>...</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>NaN</td>\n",
" <td>NaN</td>\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" <td>0.257098</td>\n",
" <td>0.545188</td>\n",
" <td>5.292658</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" </tbody>\n",
"</table>\n",
new selection of grid cells color changes and histogram overview of change
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"<p>271 rows × 73 columns</p>\n",
spike lfp analysis
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"</div>"
],
"text/plain": [
" action baseline entity frequency i ii session \\\n",
"17 1839-120619-4 False 1839 30.0 False True 4 \n",
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"34 1833-260619-1 True 1833 NaN True False 1 \n",
"35 1833-260619-1 True 1833 NaN True False 1 \n",
"39 1833-260619-1 True 1833 NaN True False 1 \n",
"40 1833-260619-1 True 1833 NaN True False 1 \n",
"42 1833-260619-1 True 1833 NaN True False 1 \n",
"44 1833-260619-1 True 1833 NaN True False 1 \n",
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"57 1834-150319-3 True 1834 NaN False True 3 \n",
"76 1834-120319-4 False 1834 30.0 False True 4 \n",
"87 1849-280219-4 False 1849 30.0 False True 4 \n",
"106 1849-110319-2 False 1849 11.0 True False 2 \n",
"124 1833-010719-1 True 1833 NaN True False 1 \n",
"125 1833-010719-1 True 1833 NaN True False 1 \n",
"126 1833-010719-1 True 1833 NaN True False 1 \n",
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"... ... ... ... ... ... ... ... \n",
"1154 1839-120619-3 True 1839 NaN False True 3 \n",
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"1223 1833-200619-3 True 1833 NaN False True 3 \n",
"1255 1833-010719-2 False 1833 11.0 True False 2 \n",
"1257 1833-010719-2 False 1833 11.0 True False 2 \n",
"1263 1833-010719-2 False 1833 11.0 True False 2 \n",
"1264 1833-010719-2 False 1833 11.0 True False 2 \n",
"1268 1833-010719-2 False 1833 11.0 True False 2 \n",
"1275 1833-010719-2 False 1833 11.0 True False 2 \n",
"\n",
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" stim_location stimulated tag ... t_i_peak p_i_peak \\\n",
"17 ms True stim ii ... NaN NaN \n",
"19 ms True stim ii ... NaN NaN \n",
"21 ms True stim ii ... 0.0008 0.000880 \n",
"29 ms True stim ii ... NaN NaN \n",
"30 ms True stim ii ... 0.0005 0.002365 \n",
"31 ms True stim ii ... NaN NaN \n",
"33 NaN False baseline i ... NaN NaN \n",
"34 NaN False baseline i ... NaN NaN \n",
"35 NaN False baseline i ... NaN NaN \n",
"39 NaN False baseline i ... NaN NaN \n",
"40 NaN False baseline i ... NaN NaN \n",
"42 NaN False baseline i ... NaN NaN \n",
"44 NaN False baseline i ... NaN NaN \n",
"46 NaN False baseline i ... NaN NaN \n",
"47 NaN False baseline i ... NaN NaN \n",
"49 NaN False baseline i ... NaN NaN \n",
"54 ms True stim i ... NaN NaN \n",
"57 NaN False baseline ii ... NaN NaN \n",
"76 ms True stim ii ... 0.0044 0.018315 \n",
"87 ms True stim ii ... NaN NaN \n",
"106 ms True stim i ... 0.0026 0.002400 \n",
"124 NaN False baseline i ... NaN NaN \n",
"125 NaN False baseline i ... NaN NaN \n",
"126 NaN False baseline i ... NaN NaN \n",
"128 NaN False baseline i ... NaN NaN \n",
"129 NaN False baseline i ... NaN NaN \n",
"131 NaN False baseline i ... NaN NaN \n",
"132 NaN False baseline i ... NaN NaN \n",
"134 NaN False baseline i ... NaN NaN \n",
"135 NaN False baseline i ... NaN NaN \n",
"... ... ... ... ... ... ... \n",
"1154 NaN False baseline ii ... NaN NaN \n",
"1155 mecl True stim i ... NaN NaN \n",
"1156 mecl True stim i ... NaN NaN \n",
"1174 ms True stim i ... NaN NaN \n",
"1184 NaN False baseline ii ... NaN NaN \n",
"1185 NaN False baseline ii ... NaN NaN \n",
"1186 NaN False baseline ii ... NaN NaN \n",
"1189 NaN False baseline ii ... NaN NaN \n",
"1191 NaN False baseline ii ... NaN NaN \n",
"1193 NaN False baseline ii ... NaN NaN \n",
"1194 NaN False baseline ii ... NaN NaN \n",
"1197 NaN False baseline ii ... NaN NaN \n",
"1199 NaN False baseline ii ... NaN NaN \n",
"1202 NaN False baseline ii ... NaN NaN \n",
"1204 NaN False baseline ii ... NaN NaN \n",
"1208 NaN False baseline ii ... NaN NaN \n",
"1214 NaN False baseline ii ... NaN NaN \n",
"1215 NaN False baseline ii ... NaN NaN \n",
"1217 NaN False baseline ii ... NaN NaN \n",
"1218 NaN False baseline ii ... NaN NaN \n",
"1219 NaN False baseline ii ... NaN NaN \n",
"1220 NaN False baseline ii ... NaN NaN \n",
"1221 NaN False baseline ii ... NaN NaN \n",
"1223 NaN False baseline ii ... NaN NaN \n",
"1255 ms True stim i ... NaN NaN \n",
"1257 ms True stim i ... NaN NaN \n",
"1263 ms True stim i ... NaN NaN \n",
"1264 ms True stim i ... NaN NaN \n",
"1268 ms True stim i ... NaN NaN \n",
"1275 ms True stim i ... NaN NaN \n",
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"\n",
new selection of grid cells color changes and histogram overview of change
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" half_width peak_to_trough average_firing_rate bs bs_stim bs_ctrl \\\n",
"17 0.283497 0.606614 9.779867 True 1.0 NaN \n",
"19 0.261815 0.633750 7.437802 True 1.0 NaN \n",
"21 0.242524 0.534827 2.265039 True 1.0 NaN \n",
"29 0.279806 0.598967 10.924422 True 1.0 NaN \n",
"30 0.265158 0.581451 3.984881 True 1.0 NaN \n",
"31 0.246920 0.570844 3.497452 True 1.0 NaN \n",
"33 0.272875 0.602667 5.945508 True NaN 1.0 \n",
"34 0.226452 0.274814 2.860048 False NaN 0.0 \n",
"35 0.247266 0.570104 3.365674 True NaN 1.0 \n",
"39 0.284542 0.644111 17.471520 True NaN 1.0 \n",
"40 0.259920 0.581698 5.891739 True NaN 1.0 \n",
"42 0.263630 0.596746 13.436847 True NaN 1.0 \n",
"44 0.281399 0.607354 17.446704 True NaN 1.0 \n",
"46 0.285816 0.603160 7.914246 True NaN 1.0 \n",
"47 0.279177 0.585152 10.840470 True NaN 1.0 \n",
"49 0.282336 0.711705 5.890705 True NaN 1.0 \n",
"54 0.270286 0.573804 14.025342 True 1.0 NaN \n",
"57 0.277867 0.588852 17.162446 True NaN 1.0 \n",
"76 0.285028 0.578245 34.841257 True 1.0 NaN \n",
"87 0.272793 0.570844 10.825754 True 1.0 NaN \n",
"106 0.230947 0.561223 2.339767 True 1.0 NaN \n",
"124 0.271262 0.615002 2.868000 True NaN 1.0 \n",
"125 0.307694 0.659653 6.912052 True NaN 1.0 \n",
"126 0.267708 0.630543 4.229867 True NaN 1.0 \n",
"128 0.289100 0.673221 16.735961 True NaN 1.0 \n",
"129 0.290402 0.650772 25.974728 True NaN 1.0 \n",
"131 0.272160 0.620429 14.686236 True NaN 1.0 \n",
"132 0.241405 0.595513 18.657578 True NaN 1.0 \n",
"134 0.269911 0.609574 3.106903 True NaN 1.0 \n",
"135 0.273069 0.651265 6.213807 True NaN 1.0 \n",
"... ... ... ... ... ... ... \n",
"1154 0.273572 0.611548 5.407135 True NaN 1.0 \n",
"1155 0.276394 0.585645 27.008837 True 1.0 NaN \n",
"1156 0.249700 0.569364 18.304313 True 1.0 NaN \n",
"1174 0.249357 0.517805 8.992236 True 1.0 NaN \n",
"1184 0.275930 0.594526 5.288548 True NaN 1.0 \n",
"1185 0.225575 0.277528 2.693978 False NaN 0.0 \n",
"1186 0.244049 0.571337 3.425185 True NaN 1.0 \n",
"1189 0.222604 0.576271 6.484767 True NaN 1.0 \n",
"1191 0.189559 0.248665 3.564358 False NaN 0.0 \n",
"1193 0.257469 0.636957 26.839270 True NaN 1.0 \n",
"1194 0.252255 0.587372 4.589373 True NaN 1.0 \n",
"1197 0.261129 0.592306 7.407060 True NaN 1.0 \n",
"1199 0.277189 0.615988 9.221822 True NaN 1.0 \n",
"1202 0.287132 0.616235 7.835622 True NaN 1.0 \n",
"1204 0.300175 0.610068 9.358786 True NaN 1.0 \n",
"1208 0.293775 0.657679 7.071948 True NaN 1.0 \n",
"1214 0.252895 0.600200 15.695836 True NaN 1.0 \n",
"1215 0.271023 0.699617 11.768979 True NaN 1.0 \n",
"1217 0.343906 0.698383 4.442023 True NaN 1.0 \n",
"1218 0.304748 0.641151 3.102590 True NaN 1.0 \n",
"1219 0.277708 0.585645 6.900656 True NaN 1.0 \n",
"1220 0.294291 0.639177 22.458685 True NaN 1.0 \n",
"1221 0.258204 0.608094 3.767155 True NaN 1.0 \n",
"1223 0.276894 0.623636 12.778706 True NaN 1.0 \n",
"1255 0.277537 0.570597 5.734302 True 1.0 NaN \n",
"1257 0.248774 0.604394 2.814742 True 1.0 NaN \n",
"1263 0.280033 0.560729 4.760330 True 1.0 NaN \n",
"1264 0.281934 0.627089 15.890929 True 1.0 NaN \n",
"1268 0.266512 0.594033 2.704037 True 1.0 NaN \n",
"1275 0.257098 0.545188 5.292658 True 1.0 NaN \n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
"\n",
new selection of grid cells color changes and histogram overview of change
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" ns_inhibited ns_not_inhibited \n",
"17 False False \n",
"19 False False \n",
"21 False False \n",
"29 False False \n",
"30 False False \n",
"31 False False \n",
"33 False False \n",
"34 False True \n",
"35 False False \n",
"39 False False \n",
"40 False False \n",
"42 False False \n",
"44 False False \n",
"46 False False \n",
"47 False False \n",
"49 False False \n",
"54 False False \n",
"57 False False \n",
"76 False False \n",
"87 False False \n",
"106 False False \n",
"124 False False \n",
"125 False False \n",
"126 False False \n",
"128 False False \n",
"129 False False \n",
"131 False False \n",
"132 False False \n",
"134 False False \n",
"135 False False \n",
"... ... ... \n",
"1154 False False \n",
"1155 False False \n",
"1156 False False \n",
"1174 False False \n",
"1184 False False \n",
"1185 False True \n",
"1186 False False \n",
"1189 False True \n",
"1191 False True \n",
"1193 False False \n",
"1194 False False \n",
"1197 False False \n",
"1199 False False \n",
"1202 False False \n",
"1204 False False \n",
"1208 False False \n",
"1214 False False \n",
"1215 False False \n",
"1217 False False \n",
"1218 False False \n",
"1219 False False \n",
"1220 False False \n",
"1221 False False \n",
"1223 False False \n",
"1255 False False \n",
"1257 False False \n",
"1263 False False \n",
"1264 False False \n",
"1268 False False \n",
"1275 False False \n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
"\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"[271 rows x 73 columns]"
spike lfp analysis
2019-10-17 17:44:01 +00:00
]
},
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 22,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gridcell_sessions"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 23,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [],
"source": [
new selection of grid cells color changes and histogram overview of change
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"data.loc[:,'gridcell'] = np.nan\n",
"data['gridcell'] = data.isin(gridcell_sessions)\n",
"\n",
"data.loc[data.eval('not gridcell and bs'), 'bs_not_gridcell'] = True\n",
"data.bs_not_gridcell.fillna(False, inplace=True)"
spike lfp analysis
2019-10-17 17:44:01 +00:00
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 24,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>action</th>\n",
" <th>baseline</th>\n",
" <th>entity</th>\n",
" <th>frequency</th>\n",
" <th>i</th>\n",
" <th>ii</th>\n",
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" <th>tag</th>\n",
" <th>...</th>\n",
" <th>half_width</th>\n",
" <th>peak_to_trough</th>\n",
" <th>average_firing_rate</th>\n",
" <th>bs</th>\n",
" <th>bs_stim</th>\n",
" <th>bs_ctrl</th>\n",
new selection of grid cells color changes and histogram overview of change
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" <th>ns_inhibited</th>\n",
" <th>ns_not_inhibited</th>\n",
spike lfp analysis
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" <th>gridcell</th>\n",
new selection of grid cells color changes and histogram overview of change
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" <th>bs_not_gridcell</th>\n",
spike lfp analysis
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" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>0.272875</td>\n",
" <td>0.602667</td>\n",
" <td>5.945508</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" <td>True</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>0.226452</td>\n",
" <td>0.274814</td>\n",
" <td>2.860048</td>\n",
" <td>False</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>True</td>\n",
spike lfp analysis
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" <td>True</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>0.247266</td>\n",
" <td>0.570104</td>\n",
" <td>3.365674</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" <td>True</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>0.284542</td>\n",
" <td>0.644111</td>\n",
" <td>17.471520</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" <td>True</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>1833-260619-1</td>\n",
" <td>True</td>\n",
" <td>1833</td>\n",
" <td>NaN</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>False</td>\n",
" <td>baseline i</td>\n",
" <td>...</td>\n",
" <td>0.259920</td>\n",
" <td>0.581698</td>\n",
" <td>5.891739</td>\n",
" <td>True</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
" <td>False</td>\n",
spike lfp analysis
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" <td>True</td>\n",
new selection of grid cells color changes and histogram overview of change
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" <td>False</td>\n",
spike lfp analysis
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" </tr>\n",
" </tbody>\n",
"</table>\n",
new selection of grid cells color changes and histogram overview of change
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"<p>5 rows × 75 columns</p>\n",
spike lfp analysis
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"</div>"
],
"text/plain": [
" action baseline entity frequency i ii session \\\n",
"33 1833-260619-1 True 1833 NaN True False 1 \n",
"34 1833-260619-1 True 1833 NaN True False 1 \n",
"35 1833-260619-1 True 1833 NaN True False 1 \n",
"39 1833-260619-1 True 1833 NaN True False 1 \n",
"40 1833-260619-1 True 1833 NaN True False 1 \n",
"\n",
new selection of grid cells color changes and histogram overview of change
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" stim_location stimulated tag ... half_width peak_to_trough \\\n",
"33 NaN False baseline i ... 0.272875 0.602667 \n",
"34 NaN False baseline i ... 0.226452 0.274814 \n",
"35 NaN False baseline i ... 0.247266 0.570104 \n",
"39 NaN False baseline i ... 0.284542 0.644111 \n",
"40 NaN False baseline i ... 0.259920 0.581698 \n",
spike lfp analysis
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"\n",
new selection of grid cells color changes and histogram overview of change
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" average_firing_rate bs bs_stim bs_ctrl ns_inhibited \\\n",
"33 5.945508 True NaN 1.0 False \n",
"34 2.860048 False NaN 0.0 False \n",
"35 3.365674 True NaN 1.0 False \n",
"39 17.471520 True NaN 1.0 False \n",
"40 5.891739 True NaN 1.0 False \n",
spike lfp analysis
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"\n",
new selection of grid cells color changes and histogram overview of change
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" ns_not_inhibited gridcell bs_not_gridcell \n",
"33 False True False \n",
"34 True True False \n",
"35 False True False \n",
"39 False True False \n",
"40 False True False \n",
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"\n",
new selection of grid cells color changes and histogram overview of change
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"[5 rows x 75 columns]"
spike lfp analysis
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]
},
new selection of grid cells color changes and histogram overview of change
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"execution_count": 24,
spike lfp analysis
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.query('baseline and Hz11 and gridcell').head()"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
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"execution_count": 41,
spike lfp analysis
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"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
new selection of grid cells color changes and histogram overview of change
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"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAewAAAFGCAYAAACorazoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzt3Xec3FW9//HXZjfZJJtKQk0glMCHKiKCcAGJiJXmFeF3kZZQVBABLyhcQcRCE0WlyVWUKChIlRJUioAXEESaQPQTauiGNCC7KVvm98c5w353M3VnZmdm5/18PPbxnZnv+X7nM5PJfOac7ylNqVQKERERqW3Dqh2AiIiI5KeELSIiUgeUsEVEROqAEraIiEgdUMIWERGpA0rYIiIidUAJW0REpA4oYYuIiNQBJWwREZE6oIQtIiJSB5SwRURE6oAStoiISB1QwhYREakDStgiIiJ1oKXaAUjtMrP3ufs/Mjw+Gzg83l3X3d8c1MD6yRZnLTGzTYEzgRnAZGAJMNfd96hiWHXNzGYA98S7/+Pu5w7gHLOJn2V3bypbcCXK9drM7EzgW/Huzu7+0OBGJ9WihC2rMbPxwHeAL1PDnxEzWwf4AbALsFGVw8nKzKYADwFrJB5eG/hndSISkXpUs1/GUlUXAEdUO4gC/AbYA5hf7UDy+Aq9yfp64KfACqCjahGJSN1RwpZMmqsdQIHqJc6t4rYTONzdlajLwN3vBWqmGVuk0tTpTKTy2uJ2gZK1iAyUErZI5aX/n3VVNQoRqWtqEpf39Ot9mn4sFW/e5+4zshy3IfA14JPAFOAdYC4wG/iVu6cyHRePHQ7MBA4A3ke41rsUeJJwvfcKd1/V75jZ9PZSB5iWiPNX7j6zX/m1gaOBjwIWn6MLWAQ8AlwD3JArzmLF9+TFfg8n45zv7hvGsunHvgrMAS4GdiU0oT8HnOrudyXOXfR7liG+jxI6FW4PrAW8BtwMnEN4b5bEorPcfXbBL7zvc+xGuH6/K6Fn/CLgPuCH7v6Imf2L8O/R59/MzGYCV8S7E4H9gP8hdCxcDPw9vvadyNNL3MxGEd6rQ4FNgZHAv4BfAD8r8HWMBT4PHBTPsWZ8LX8HfuHuv89xbMn/ViJpqmFLqfYn9HY+FtgYaCV8oe1O+NKdY2YZfxia2XTCF9fPgI8Rek4Pj8fvCVwGPGlmNtDgzOxwQuL8LmFI1boxxjZggxj/dcDNZlbta+LrAw8AHwdGA+OBDxCSNlD6e2ZmLWb2M+Au4D8J78FIYBPgv4EnCEm0JGZ2BvAXQqJaN8a4DvD/gL+a2fEFnupLhB9+BoyI5xjj7isKiGEa8BhwKbAz4UfDGOCDhI5/dxBee65zfAh4hvC+7g6sl3gtewM3mdkNZtaa4diKf76lsShhS9JlwHbArYnHtot/R2U55mJCx59LCDXsjwCnAe1x/6cIiaCPOCTr/4AtgFXx+L2AHQk1ql8B3cDmwD1mtm7i8DNiTI/G+28k4jwj8Rx7EL7sRxFqZt+J8exESNSXxOcG2CfHaxyI1xMxZYrz0xmOOZGQVL4P7EZIdme7+0vx9ZTynqX9gNDaAKF3/ZcIyeyzhAQ2hfADZsDM7CTg2/HuvwktB/8BfIJQs20CfkJhQ/HOAl4htKjsCpwM/LCAGNoItfnN40M3A/sS/u2PAuYRWlwOyHGOzYF7CT+keoBfx3PsTBhF4bHoZwkjK5LHluPfSqQPNYnLe+IEKG+a2eLEY0/kOWwlsIe7P5h47F4z+zPw13j/cEISSrqMUEt5B9jT3R/pt/8WM7seuIVQQ/sR8F8xppeBl81sWSy7Kkuc34nbLuAT7v73fvtvNLM/0vsD5QDgf3O+2gLFZs4nAAqIM20YIUGflnjs+sTtAb9nMY73AcfFu3OB3dx9ceL4m8zsx8AJBbzEjOKY83SyfgHY1d3fSBS5I77n1xJqzPmkCP926THrDxQYyjeAafH2We5+emLfw2Z2DXAnIflmczmhBp4C/p+7J/8tHorv9YPA1sAXzez89I8rSvy3EslENWwp1cX9kjUAcfalx+LdzZPN4ma2GaGmAuHLtP+XWfoctxFqIgAHmNl6hQZlZqMJTd+LgVszJOvkcyyNd6cUev4K+mmmB8v0ns2idyjcMf2SddrJhCbggTqS3l7xx/RL1ukYrwd+WeD57k0k64KY2TB6WxGcfv0yYgztwGGEmnOmc2xJmJAH4Mp+yTp9jncJrUkQvks/Fo+t+OdbGpMStpTq9hz7no3bYYTrsWmfpnf87J0Fnn8Y4Rp0Qdy9w913cPdJwOfyFE9PrbradchB9pq7v5plXznes73j9hV3/0umA929C/h5/lCz2iduXyN3nIW2ZAxk2s0PEq4TA/zO3bszFXL35wjX2TPZJ3H71zme63bCJY4x7p5+3yr++ZbGpCZxKVW2BANhNq+05Gdtu8Ttx4roc7NxoQWT3L0H3ruuuRGhg9XmwLaE66Lrx6LV/gH7So59Jb1nsUNd+v3Ld5ljtRaTQphZE6EnNMCjeXrdP07oBT88z2lzvSfZbJ64ne+1/o3MiXKzxO3HMuwH3vuB0/85BvXzLY1DCVtK9W6B5ZIzUk0e4HNNLPYAM5sKnERoosz2hdhD9ZM1hOud2ZT6nk2m9zUuzHPM6yU8V/q6dM7ncPeu2Fdi7TznzPWeZJM856I8Zf+d5xw97r4kS5lsBu3zLY1FCVtKNZCxy8nP3Y6EmlYh3irmSczsk4ROW22Jh98lDEN7hjAG+y7gJnqnD62mXO9lqe9Z8lptvuk8BzouONmJrJAfQIV8dgby+Uoek++1ZnsfS/luHJTPtzQeJWyphmRnp9fcfaA1uqzisJprCMm6kzAhyNWA92+qNbMx5X7+Cij1PVtCGEbUTJgoJZeB1vQWE5JlE73XkDOKTfSVqlEmO7rljIO+K6glpd/vYWY2schadsU/39KYlLClGp5O3N4JuDFbwThxxQzgJeCBHJ2y+juE3o5u33P372QqFCe8yNcsWwtKes9iE/Q/CNdXtzezYelr+xm8fyABuvsqM5tLaK3YLk/xrahcJ79kL/cd6Ds0rr9sr3Vu4va2hPHYq4k90p8lNN3f7O5nMjifb2lAtXDdTmpPti/ycvlT4vYxecqeD5xLqC33vwadK87piduPZi0VJlBJz3ZVyz9gy/Ge3Ra3a9PbYzyTw4qOrld6TPt6ZvaRHOUOz7GvJHGs+wvx7ufNLONsZma2JmGyn0zuStz+fI6n25HwHr+f3iFz5fp8i/ShhC2ZrEzfqERzcRwTnR5Os6eZfSNTuThj1m7x7hOEmaMyxZkpxmSnp09lOf+OwEWJh6o9rCurMr1nP6V3De5L4tSd/Y8/gjAj10BdRu/ogEvNbLUOWHEGuq+U8ByF+FHcTo1x9LmWHef4voIsU5PGeQTSY/ePMLOP9y8TW2cujXe7CLPqlfPzLdJHLdcopHqS1wDPNrNfA93u/ngZn+MowhfiOOAsM9udMG3lfMJ8zQcTpnyE0AnqCxmGCaXjnGRm/0MY89rh7nMJzaDfIFxPPTZOpHIDIZFPIUwPeRB9hxWNM7Omci4CUmYlvWfu/oaZfZmQqKYCj5rZeYTZw9oIM23NKiVAd58fF5E5lzC86gkz+z6hg98oQm/9Y+j7vlfi/b6U8Hp2IbymTc3sQsJ7tSlhutwPEKbQbctyjqMI48BHAreZ2c8JU5y2E5r0T47nAjjX3Z/vd2ypn2+RPlTDlkxuIXRQglATegTIuiLRQLj7s4TFFF6KD30c+B3hC/JGQlN1E6Gz1H5ZZotKXhs8O8b503j+J4D0dJRNhC/t2+L5byA0+w4nTFyRnvBiBH2b0mtKOd6zuPLWsYSOeJMIU8Y+QJhH/AjCtdgL+h9XZJzn0VvDnUKYN/xB4G7CtKdNwCmJQ1ZSZvH6/Kfjc0IYb38t8DBwFSFZP0aYWz3bOZ4kzH++kPBZOZbQ3H0/YeKXdLK+kMQc9vHYcny+RfpQwpbVxGS3L2Eu8GXAcqAz1lLL/TxbEJZ5vJMwJraTMPTqUcJc4Ju7+x+zHH8b4Vr
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
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"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
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"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 525x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"\n",
"density = True\n",
"cumulative = True\n",
"histtype = 'step'\n",
"lw = 2\n",
"bins = {\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" 'theta_energy': np.arange(0, 2.1, .03),\n",
" 'theta_peak': np.arange(0, 1, .03),\n",
" 'theta_freq': np.arange(4, 12, .1),\n",
" 'theta_half_width': np.arange(0, 5, .1)\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
"}\n",
"xlabel = {\n",
" 'theta_energy': 'Theta coherence energy',\n",
" 'theta_peak': 'Theta peak coherence',\n",
" 'theta_freq': '(Hz)',\n",
" 'theta_half_width': '(Hz)',\n",
"}\n",
"\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
spike lfp analysis
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" for key in bins:\n",
" fig = plt.figure(figsize=(3.5,2.2))\n",
" plt.suptitle(key + ' ' + cell_type)\n",
" legend_lines = []\n",
" for color, query, label in zip(colors, queries, labels):\n",
" data.query(query + ' and ' + cell_type)[key].hist(\n",
" bins=bins[key], density=density, cumulative=cumulative, lw=lw, \n",
" histtype=histtype, color=color)\n",
" legend_lines.append(matplotlib.lines.Line2D([0], [0], color=color, lw=lw, label=label))\n",
" plt.xlabel(xlabel[key])\n",
" plt.legend(\n",
" handles=legend_lines,\n",
" bbox_to_anchor=(1.04,1), borderaxespad=0, frameon=False)\n",
" plt.tight_layout()\n",
" plt.grid(False)\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" plt.xlim(-0.05, bins[key].max() - bins[key].max()*0.02)\n",
" despine()\n",
spike lfp analysis
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" figname = f'spike-lfp-coherence-histogram-{key}-{cell_type}'.replace(' ', '-')\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.png', \n",
" bbox_inches='tight', transparent=True)\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.svg', \n",
" bbox_inches='tight', transparent=True)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 43,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [],
"source": [
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"data['stim_strength'] = data.stim_p_max / data.theta_peak"
spike lfp analysis
2019-10-17 17:44:01 +00:00
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 47,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
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"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
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"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
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"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcEAAAFGCAYAAAASDiSIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAXEQAAFxEByibzPwAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzt3Xn85XPd//HHbMKMZQwiu8GLkSwVuVDaxHVZylLZh4uipF9XlOLKUknUdSWmSMme/ZKyFBJZhhLZ8hrbUCLLGGGMMfP9/v54vY/vx5mzn89Zvt/P8367fW+f7zmf5bzP53zOeX3e+6jBwUFERESKaHSvEyAiItIrCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYCoIiIlJYY3udgGaY2bvc/d4Kz58F7Jserujuz3Q1YX2i2vkpKjNbBFjT3R8qe3514PH08HR3P6jbaZPmder67vT1kMfvk5nNBFYD3N3XzTy/Om2m3cymAj9PD3d39wsrbDMBWN7dH2v2+HnJnkd3H5XXcYdFTtDMljKzk4E/9zot/cjM1jKza4Af9jot/cLMPgLcC3y612mR9pjZCmZ2HvDLXqeliMzsU8BDwPt7nZZOGC45wf8B9u91IvrYb4A1gZt6nZB+YGarANf1Oh2Sm/OBDwFP9DohRWNmWwEL5QxHkuESBMfUWunuU4GpXUlJf6p5fgpI52Nk6ejn6e4zgdyK1zrB3Vfv4LHPAs6qsnrEf5eGRXGoiIhIJygIiohIYY0aHBzs2ouZmQGfAz4MrEEE4eeBu4DLgQvcfX5m+2OAo6sc7iZ33zptdxZVWl9lWlV9390PM7P/AA4B3g1MAJ4ELgNOdPeX0j4bAV8GPggsl9L4O+Cb7j6jjVNQk5l9mKj7/DfgHcA84BngFuBsd/992fa/Bz5Q5XDHuvsxabuZxDk4GfgOcAqwLVEENBP4jrtfkDnuKOCTwB7Ae4BlgZeBvxKNE05z91eqvIfSBfUld/+Bme0MHABsAkwE/gncCPzA3e+ucz52AD4LbAoslfa9Dviuu88ws7nA28rea60L+oPu/vvyFnXAwcDeRJH6hsDiwFPAtSmdj9RKZ43053Iumr0u8pL5Xv3F3Tcys7WB/wd8DFgJmEM0PjonpWOgxrGWJN77TsA7gSWAF4C7gUuAc7Pf/bLXr+TsVA3StlotLMtaTk4EBohzsDNRDz8KeIT4/TrZ3f9V4fhnkfl9AhYFDie+gysB/wIeJIokz3b3ha7hRluHEr9tX0ivtw4wF7gf+AXwU3d/o8Kxs+9xd3e/sOy4layRipGzx1klvfbHgNWBRYCngT8Qvxm31zgeZrYY8R3cG1ibOE8PAT8DfgKcyXBuHWpmexBfmEOB9YkfmkWBlYkvxtnAH83s7R1Mw2nAr4mLbzlgMcCArwN/MLPxZnYAcCewF3GBLkL88OwF/MnMNuxQ2k4FricCz+rpdScAaxEXxo1mdq6ZtVOPuyRwM7Ab8SM0gfhBeiqTjuWJi/ZCYEfivS8CTAK2BE4C3Mw2r/NaY8zsfOIGYzvg7ek4qwD7EOfywEo7mtloM/sJcCXwH8RnVdp3f+AvZrZLs2++iiWIwHo2cdOzDHFdTgY+D9xtZh9r8zXaORfduC7qSuf7HuImdjJxjpYBtiZ+nH5jZm+rsu8HiR+z7xMtDJcBxgErEOfjTOI8T+7ke8iBAfcBxxI3S6Xv0EbAccD9KXjUsgtxM/k5Ioi+jbi+P0AEoqva+CwnAL8nGhJuSPy+TQS2An4E3GVmK7Z47JrM7D+BGURwfxfxW7MokdnZB7jNzE43s3FV9l+NaP3/I2Bz4sZ7AnET/mPgt+l4uetKEDSztYgLfRHi7uJg4gd1cyK4lO4QNiJOQslpwMbArzLPbZz+DmgyGfsSuQoHDgS2IO44Zqb1GwCXEndT/ySC9ebAvxOtLyEu+pObfN26zGxv4gcXooXn7sBmxBfjUCK3CnGuDs7segBxLp5Oj+9i6PycVuGlSneHP0vH3hE4xd1vSukYT+RMtgAGgfOATxA5se2IHORcIjD+1szWr/G2DiN+uP8KfAZ4XzrGRWn9aOAUM1u1wr4nE58RwKOZ/XckAsmixJ3tIhX23ZgInCWnM3RO/lRh+z2Ikol7ifO5BZELvjGtnwCcY2ZL1Hiv9bR0Ltq4LvK2KtFCE+BE4nxtCRxB5GIAPkLkkN4i3SxdReSAStfUjsT7+DTx4wZxM/aHsh/pbxCf213p8dMMfZbfyOF9NesK4lz8gngP7wP2I378IW5qflznGKcSucdpxM34B4EjgVfT+u2A/2oxfXsQ1++DKV3vI67lW9P6DWg8yP6DOM/Zm7OjGTr//yg9mXKSPyW+l48TpWhbESUXBxI3TxDX/k/KXyj97twElHK4v2To/B5AnN8PEzfvuetW69A9iTueBUSRVLap83Qzu5i4g/k34BNmtqy7P5+KNZ8xs1mljd39HlqzLPFDt1WmyOI2M7ubKC6AuChnApu5+7OlHc3sN8B04L3A+81saXef3WI6Kil1/3gQ2Mbd52XW3Wxm/5fSPpG4kE4BKBXTmVlp+1fqnJ/RRJFz9gYie4PxbWAKMB/4hLv/umz/a83sHOKCnUAE0/dVea0VgBuA7d19btkxXgQOIq6J3YHvllaa2cbEXTJEjvwj7v5yNr1m9mXge5Ve1N3vMbPsZ/NMA9fM5UQx0Jvn3cwuJX68twOWJ66NS+ocp5qWzgUtXhcdMJH4kd6y7FzeamY3AbcRP+xTeetnOYa4+V2MKEb8lLtfmtn/TuAiM/sGkbtakbhp2RHA3Z8EnjSzUtH7vDa+/3lYATjQ3X+aee4OM7uC+IxWBD5mZivU6BD/OvAhd78t89zvzex3DGUG9iVuNpo1ivhubufur2XSdxkRuD9JBLDPEkG4qnSt3WNmS2eefrL8/JvZOzLHugHYyd1fzWxyeyoOPoe4vqea2UXufm1mm68TRb0A33b3ozLr7jCzC4nSmnqlTy3pVnHoCmn5Cpk7iJJUTn000dn7Sx1M11HlZfbu/gBxh15ybDYApm0GGAoWo4jioDyVzs8TZT90pdf/O3HneyKRY2inPLzinWq62Et3fWdUCICltPyJoS/oZma2WY3XOrTsR7/k9Mz/5cXLXyA+/0Fg37IAWErD94kvXB5eBz5Tft5TvUz2XL2zzddp5Vx087qo50eVApC7TycCMcC6ZUWiOzB0d//jsgCYPcZxxE0wwA5mNiWfJOfuj2UBEIB0Q3xxejiKKA6s5tSyAFg6xnSGBgNZt8Ui0deBPTMBsHTsAeK7/VJ6Ks9Sg88TVVvzgX3KAmDp9een1yy9/hdL68xsNEO/O06FNiDpmPsQN1K561YQLA1btRRwiZmtV76Bu1/v7l9095PLg1BOBhgq4ir3VOb/aj+u2TRNyCVFQ0rnZ1sz+3aql3sLdz/V3b/q7j+pVHHeoPlULhKEqNtZPP1fr6P51Zn/P1xlm6fc/cEq6x7N/P9mMWP6QpSKMm/3suHOypxeY10z7nT3F6qsezjz/zJtvEbT5yLp1nXRiN/WWJd9D9nvRrYutd7nla0G2bbRRHVZo+egVtH51TXWla630cRvZbOudvenKq1IN/9XpIfrpxxcHkrf1wfdfaEMTub1X2KoWPb9mbrB9xB1ogAXufuCKvs/QrRnyF23ikPPISpMVyIawexkZo8RP7bXA9fnXLxYyfPVWjQSd1AlTzewTd533N8Dtic+j68DR5jZn4lzcx1wS6WcQAuer5IbgSgmKbk8GvI2ZM0qz8+ssU/2c8hegysSRY9QPViX3FFnfaP+XmNd9ly1812ZWWNdtXMB3bsuGjGzxrpq7+GdmfX3U9v0zP8bNJ6srppZY12tzzGrk9dbve/E3Qy1Ut2ACqVyzUi51dJn9a46LbOzFicah/2doZICGKo7rOZO4mY9V13JCbr7i0TFefZCX5Mom74EeN7MbjCzPTtYpLNQsVol5c20u8HdbyU
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 480x330 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"\n",
"density = True\n",
"cumulative = True\n",
"histtype = 'step'\n",
"lw = 2\n",
"bins = {\n",
" 'stim_energy': np.arange(0, .4, .01),\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" 'stim_half_width': np.arange(0, 1.5, .01),\n",
spike lfp analysis
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" 'stim_p_max': np.arange(0, 1, .01),\n",
" 'stim_strength': np.arange(0, 50, 1)\n",
"}\n",
"xlabel = {\n",
" 'stim_energy': 'Coherence energy',\n",
" 'stim_half_width': '(Hz)',\n",
" 'stim_p_max': 'Peak coherence',\n",
" 'stim_strength': 'Ratio',\n",
"}\n",
"# key = 'theta_energy'\n",
"# key = 'theta_peak'\n",
new selection of grid cells color changes and histogram overview of change
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"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
spike lfp analysis
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" for key in bins:\n",
" fig = plt.figure(figsize=(3.2,2.2))\n",
" plt.suptitle(key + ' ' + cell_type)\n",
" legend_lines = []\n",
" for color, query, label in zip(colors[1::2], queries[1::2], labels[1::2]):\n",
" data.query(query + ' and ' + cell_type)[key].hist(\n",
" bins=bins[key], density=density, cumulative=cumulative, lw=lw, \n",
" histtype=histtype, color=color)\n",
" legend_lines.append(matplotlib.lines.Line2D([0], [0], color=color, lw=lw, label=label))\n",
" plt.xlabel(xlabel[key])\n",
" plt.legend(\n",
" handles=legend_lines,\n",
" bbox_to_anchor=(1.04,1), borderaxespad=0, frameon=False)\n",
" plt.tight_layout()\n",
" plt.grid(False)\n",
" plt.xlim(-0.05, bins[key].max() - bins[key].max()*0.02)\n",
new selection of grid cells color changes and histogram overview of change
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" despine()\n",
spike lfp analysis
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" figname = f'spike-lfp-coherence-histogram-{key}-{cell_type}'.replace(' ', '-')\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.png', \n",
" bbox_inches='tight', transparent=True)\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.svg', \n",
" bbox_inches='tight', transparent=True)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 28,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"from septum_mec.analysis.plotting import plot_bootstrap_timeseries"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 29,
spike lfp analysis
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"metadata": {},
"outputs": [],
"source": [
"coher = pd.read_feather(output_path / 'data' / 'coherence.feather')\n",
"freqs = pd.read_feather(output_path / 'data' / 'freqs.feather')"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 30,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [],
"source": [
"freq = freqs.T.iloc[0].values\n",
"\n",
"mask = (freq < 100)"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 31,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 750x300 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"image/png": "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
"text/plain": [
"<Figure size 750x300 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
spike lfp analysis
2019-10-17 17:44:01 +00:00
"text/plain": [
"<Figure size 750x300 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" fig, axs = plt.subplots(1, 2, sharex=True, sharey=True, figsize=(5,2))\n",
" axs = axs.repeat(2)\n",
" for i, (ax, query) in enumerate(zip(axs.ravel(), queries)):\n",
" selection = [\n",
" f'{r.action}_{r.channel_group}_{r.unit_name}' \n",
" for i, r in data.query(query + ' and ' + cell_type).iterrows()]\n",
" values = coher.loc[mask, selection].dropna(axis=1).to_numpy()\n",
" values = 10 * np.log10(values)\n",
" plot_bootstrap_timeseries(freq[mask], values, ax=ax, lw=1, label=labels[i], color=colors[i])\n",
" # ax.set_title(titles[i])\n",
" ax.set_xlabel('Frequency Hz')\n",
" ax.legend(frameon=False)\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" ax.set_ylim(-30, 0)\n",
spike lfp analysis
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" axs[0].set_ylabel('Coherence')\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" despine()\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" figname = f'spike-lfp-coherence-{cell_type}'.replace(' ', '-')\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.png', \n",
" bbox_inches='tight', transparent=True)\n",
" fig.savefig(\n",
" output_path / 'figures' / f'{figname}.svg', \n",
" bbox_inches='tight', transparent=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Store results in Expipe action"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 48,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [],
"source": [
"action = project.require_action(\"stimulus-spike-lfp-response\")"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 49,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/data/freqs.feather',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/data/coherence.feather',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_not_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-gridcell.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_not_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-gridcell.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-not-bs.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-not-bs.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_not_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-not-bs.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-not-bs.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-gridcell.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_not_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-not-bs.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-not-bs.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_not_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-not-bs.svg',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_inhibited.svg',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-gridcell.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-gridcell.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-not-bs.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-gridcell.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-gridcell.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-gridcell.png',\n",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_not_inhibited.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.svg',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_not_inhibited.png',\n",
spike lfp analysis
2019-10-17 17:44:01 +00:00
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-gridcell.png',\n",
" '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-not-bs.svg']"
]
},
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 49,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"copy_tree(output_path, str(action.data_path()))"
]
},
{
"cell_type": "code",
new selection of grid cells color changes and histogram overview of change
2019-10-22 10:22:00 +00:00
"execution_count": 50,
spike lfp analysis
2019-10-17 17:44:01 +00:00
"metadata": {},
"outputs": [],
"source": [
"septum_mec.analysis.registration.store_notebook(action, \"20_stimulus-spike-lfp-response.ipynb\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
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"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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