Social structure and individuals' behavior shaped by group composition in long-term tracking of rats

<p>Trajectory data and behavioral metrics from long-term tracking of groups of rats.&nbsp; Experiments performed in 2012 at&nbsp;E&ouml;tv&ouml;s Lor&aacute;nd University, Budapest, Hungary.</p> <p>The data here is used in the following publication.&nbsp;See the publication for information on experimental structure and notation.<br> Nagy, M&aacute;t&eacute;, Jacob Davidson, G&aacute;bor V&aacute;s&aacute;rhelyi, D&aacute;niel &Aacute;bel, Enikő Kubinyi, Ahmed El Hady, and Tam&aacute;s Vicsek. 2023. &ldquo;Social Structure and Individuals&rsquo; Behavior Shaped by Group Composition in Long-Term Tracking of Rats.&rdquo; bioRxiv. <a href="https://doi.org/10.1101/2023.03.18.533183">https://doi.org/10.1101/2023.03.18.533183</a>.</p> <p>Github repository to reproduce results in the paper:&nbsp;<a href="https://github.com/jacobdavidson/ratsocialgroups">github.com/jacobdavidson/ratsocialgroups</a><br> Github repositories used for tracking and computation of behavioral metrics: <a href="https://github.com/vasarhelyi">github.com/vasarhelyi</a></p> <p>The behavioral metrics, approach-avoidance networks, individual labels and group membership information, and behavioral assay&nbsp;data needed to reproduce the results in the publication are included in the zip&nbsp; file&nbsp;<a href="https://zenodo.org/api/files/969c78d4-1d30-4926-ac6e-141136cd3564/metrics-networks-labels.zip">metrics-networks-labels.zip</a>.&nbsp; This includes the following files in .csv format:</p> <p><strong>Naming/labels:</strong></p> <ul> <li><strong>uidlabels.csv</strong>: References the ranked-mass labels used in the paper&nbsp;to the 3-color-code labels that identify each rat from the tracking.&nbsp; &quot;Group&quot; is the membership during the original groups (Period 1), and &quot;GroupG&quot; is membership during the remixed groups (Period 3). <table> <tbody> <tr> <td>&nbsp;</td> <td> <p><strong>masslabel</strong></p> </td> <td> <p><strong>GroupMassRank-Exp7</strong></p> </td> <td> <p><strong>Group</strong></p> </td> <td> <p><strong>GroupG</strong></p> </td> </tr> <tr> <td> <p><strong>GOB</strong></p> </td> <td> <p>a5</p> </td> <td> <p>5.0</p> </td> <td> <p>A1</p> </td> <td> <p>G3</p> </td> </tr> <tr> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> </tr> </tbody> </table> </li> <li><strong>groupnames.csv</strong>:&nbsp; Group membership information for each rat, during each experimental period <table> <tbody> <tr> <td> <p><strong>Experiments</strong></p> </td> <td> <p><strong>GOB</strong></p> </td> <td> <p><strong>OBG</strong></p> </td> <td> <p><strong>...</strong></p> </td> </tr> <tr> <td> <p><strong>1-7</strong></p> </td> <td> <p>A1</p> </td> <td> <p>A1</p> </td> <td> <p>...</p> </td> </tr> <tr> <td> <p><strong>...</strong></p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> </tr> </tbody> </table> </li> </ul> <p><strong>Behavioral metrics and approach-avoidance networks:</strong></p> <ul> <li><strong>metrics.csv:&nbsp;</strong>Behavioral metrics for each rat, calculated for each experiment. <table> <tbody> <tr> <td> <p><strong>Experiment</strong></p> </td> <td> <p><strong>metric</strong></p> </td> <td> <p><strong>GOB</strong></p> </td> <td> <p><strong>OBG</strong></p> </td> <td> <p><strong>...</strong></p> </td> </tr> <tr> <td> <p><strong>1</strong></p> </td> <td> <p>AA</p> </td> <td> <p>0</p> </td> <td> <p>0.690964</p> </td> <td> <p>...</p> </td> </tr> <tr> <td> <p><strong>...</strong></p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> </tr> </tbody> </table> </li> <li><strong>Networks-Period1+Period3.csv: </strong>Approach-avoidance interaction networks for the groups of 7 rats in Period 1 and Period 3.&nbsp;&nbsp; <table> <tbody> <tr> <td> <p><strong>Experiment</strong></p> </td> <td> <p><strong>DayNight</strong></p> </td> <td> <p><strong>Group</strong></p> </td> <td> <p><strong>index</strong></p> </td> <td> <p><strong>winner</strong></p> </td> <td> <p><strong>loser0</strong></p> </td> <td> <p><strong>loser1</strong></p> </td> <td> <p><strong>loser2</strong></p> </td> <td> <p><strong>loser3</strong></p> </td> <td> <p><strong>loser4</strong></p> </td> <td> <p><strong>loser5</strong></p> </td> <td> <p><strong>loser6</strong></p> </td> </tr> <tr> <td> <p><strong>1</strong></p> </td> <td> <p>Day</p> </td> <td> <p>A1</p> </td> <td> <p>0</p> </td> <td> <p>GOB</p> </td> <td> <p>0</p> </td> <td> <p>0</p> </td> <td> <p>0</p> </td> <td> <p>0</p> </td> <td> <p>0</p> </td> <td> <p>0</p> </td> <td> <p>0</p> </td> </tr> <tr> <td> <p><strong>...</strong></p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> </tr> </tbody> </table> </li> <li><strong>Networks-Experiment8.csv</strong> and&nbsp;<strong>Networks-Experiment9.csv:&nbsp;</strong>Approach-avoidance interaction networks for the larger combined groups in the experiments during&nbsp;Period 2.&nbsp;</li> </ul> <p>&nbsp;</p> <p><strong>Behavioral assays results:</strong></p> <ul> <li><strong>IndividualTests.csv</strong>:&nbsp; Individual behavioral assay test results for the black and white box, elevated plus-maze, and canopy tests. <table> <tbody> <tr> <td> <p><strong>ID</strong></p> </td> <td> <p><strong>BWB-All Frames</strong></p> </td> <td> <p><strong>BWB-Black</strong></p> </td> <td> <p><strong>...</strong></p> </td> </tr> <tr> <td> <p><strong>BGP</strong></p> </td> <td> <p>7500</p> </td> <td> <p>6860</p> </td> <td> <p>...</p> </td> </tr> <tr> <td> <p><strong>...</strong></p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> </tr> </tbody> </table> </li> <li><strong>PairedTests.csv:&nbsp; </strong>Pairwise social interaction behavioral assay test results for tests with unfamiliar and familiar rats <table> <tbody> <tr> <td> <p><strong>rat_ID</strong></p> </td> <td> <p><strong>rat_group_N</strong></p> </td> <td> <p><strong>freq_standup_unfam1</strong></p> </td> <td> <p><strong>...</strong></p> </td> </tr> <tr> <td> <p><strong>BGP</strong></p> </td> <td> <p>2</p> </td> <td> <p>28</p> </td> <td> <p>...</p> </td> </tr> <tr> <td> <p><strong>...</strong></p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> <td> <p>...</p> </td> </tr> </tbody> </table> </li> </ul> <p>&nbsp;</p> <p><strong>Trajectory data</strong>&nbsp;is included as multiple text files for each experiment in TSV format.&nbsp; #t is frame number,&nbsp;Color_code_name identifies each rat,&nbsp;Real_recognition(1)_or_virtual(0) = 1 is a detection of the rat&#39;s color codes while 0 is an interpolated value, x,y, and Orientation are the position and orientation of the rat.</p> <table> <tbody> <tr> <td>#t</td> <td>Color_code_name</td> <td>Real_recognition(1)_or_virtual(0)&nbsp;</td> <td>x</td> <td>y</td> <td>Orientation</td> </tr> <tr> <td>0</td> <td>ORG</td> <td>0</td> <td>872.4000</td> <td>778.7000</td> <td>-79.5000</td> </tr> <tr> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> </tr> </tbody> </table> <p>&nbsp;</p> <p><strong>Time-lapse video of the entire experiment:</strong>&nbsp;&nbsp;<a href="https://zenodo.org/api/files/969c78d4-1d30-4926-ac6e-141136cd3564/ratlab_timelapse_entire_exp.avi?versionId=a58df78d-1291-4301-9763-86a97b9e146c">ratlab_timelapse_entire_exp.avi</a></p>