Adult neurogenesis improves spatial information encoding in the mouse hippocampus - hM4Di Controls Part 2

<p><strong>In vivo two-photon imaging dataset for Frechou et al. "Adult neurogenesis improves spatial information encoding in the mouse hippocampus"</strong></p> <p>This dataset includes data from CNO-induced chemogenetic silencing experiments in hM4Di-(control) mice. There is another Zenodo dataset with the remaining hM4Di-(control) mice <a href="https://doi.org/10.5281/zenodo.10913386">here</a>. The folder for each mouse includes baseline (pre) and post-CNO (cno) recordings.</p> <p>For each recording we included raw imaging data consisting of:</p> <ul> <li>Individual frames (.tif files) from 3 consecutive 3 min Ca2+ imaging movies (which were concatenated for analysis)</li> <li>Microscope settings metadata (Experiment.xml)</li> <li>Mouse location data (Episode001.h5 in SyncData folder) containing rotary encoder and RFID data</li> </ul> <p>Some analyzed data is also included:</p> <ul> <li>Suite2p analysis data (<strong>Suite2p</strong> folder)</li> <li><strong>fluorescence.npy&nbsp;</strong>contains raw fluorescence data (the F output of Suite2p data extraction). Rows are individual cells and columns are frames (i.e. timepoints) acquired at 15.253 Hz.</li> <li><strong>positions.npy&nbsp;</strong>contains the position of the mouse on the treadmill belt indexed from 0 to 100.</li> </ul> <p>Both NumPy(.npy) files are the output of the Preprocessing.py code, part of the analysis pipeline used for data analysis in the original publication, which can be found at <a href="https://github.com/GoncalvesLab/Frechou-et-al-Neurogenesis">https://github.com/GoncalvesLab/Frechou-et-al-Neurogenesis</a></p> <p>Refer to the original publication for additional information. The sex of individual mice is as follows:</p> <table> <tbody> <tr> <td><strong>Group</strong></td> <td><strong>Mouse #</strong></td> <td><strong>Sex</strong></td> </tr> <tr> <td>hM4Di-</td> <td>M4</td> <td>F</td> </tr> <tr> <td>&nbsp;</td> <td>M5</td> <td>F</td> </tr> <tr> <td>&nbsp;</td> <td>&nbsp;</td> <td>&nbsp;</td> </tr> </tbody> </table>