This readme file was generated on 2024-03-12 by Vivek Agarwal GENERAL INFORMATION Title of Dataset: Calcium imaging of glomeruli in the olfactory bulb of the mouse in response to thirty-five monomolecular odors Author Name: Vivek K. Agarwal Institution: New York University, Center for Data Science Email: vka244@nyu.edu Author Name: Joshua S. Harvey Institution: NYU School of Medicine, Neuroscience Institute Email: Joshua.Harvey@nyulangone.org PI Name: Dmitry Rinberg Institution: Center for Neural Science, New York University Email: rinberg@nyu.edu PI Name: Vasant Dhar Institution: Stern School of Business, New York University Email: vd1@stern.nyu.edu Date of data collection: Data collected over July - August 2019. Geographic location of data collection: NYU Langone Health, Rinberg Lab, Neuroscience Institute Funding sources: The collection of data was supported by NIH BRAIN Initiative Grant U19NS112953. *** SHARING/ACCESS INFORMATION Licenses/restrictions placed on the data: CC-BY-NC-SA 4.0 (Attribution-NonCommercial-ShareAlike 4.0 International) Links to other publicly accessible locations of the data: The dataset will be linked to the ‘pyrfume’ library (can be used with Python) subsequently. Was data derived from another source? No, the data was collected via experiments conducted at Rinberg Lab. Recommended citation for this dataset: Vivek K. Agarwal, Joshua S. Harvey, Hiro Nakayma, Dmitry Rinberg, Vasant Dhar. Calcium imaging of glomeruli in the olfactory bulb of the mouse in response to thirty-five monomolecular odors. https://doi.org/10.58153/j2932-aaf14 *** DATA & FILE OVERVIEW The folder contains two subfolders - test_mouse_data and train_mouse_data. Each subfolder contains folders for 35 odors. Each odorant sub subfolder contains a video file that has been converted into a .tif file. A sample .tif file for the training dataset (for example, in the case of 2_3_Pentanedione) will look as 1952_072519_100hz_Set52_145r4_121.tif The name of the .tif files can be understood as following: [Mouse I.D. number]_[mmddyy (date of experiment)]_[camera FPS]_[odorant set]_[total number of tests]_[trial number].tif The data is arranged similarly and with the same naming convention for the test_mouse_data folder. A sample .tif file name for the test dataset (for example in case of 2_3_Pentanedione) will look as 1953_072619_100hz_Set52_145r4_119.tif. The name of the .tif file in the test dataset can be understood similar to the training dataset. Please note the different mouse I.D. number, 1953, for the test dataset. The data currently contain video files for 35 odorants, with the goal of extending the dataset to include more odors. The database will be updated on a regular basis as we collect more data. File List: olfaction_data_35_odors/ # This is the main folder that comprises train and test subfolders │ └── train_mouse_data/ # This contains Training data video files for 35 odors as listed. ├── 2_3_pentanedione [ 11 files] │   ├── 1952_072519_100hz_Set52_145r4_004.tif │   ├── 1952_072519_100hz_Set52_145r4_018.tif │   ├── 1952_072519_100hz_Set52_145r4_029.tif │   ├── 1952_072519_100hz_Set52_145r4_044.tif . . . ├── 2_ethylbutyric_acid [ 11 files] ├── 2_methyl_butyraldehyde [11 files] ├── 2_methyl_valeraldehyde [11 files] ├── 2_methylhexanoic_acid [11 files] ├── 2_ethylhexanal [11 files] ├── 2_heptanone [11 files] ├── 33_dimethylbutyricacid [11 files] ├── 3_methylvalericacid [11 files] ├── 3_heptanone [11 files] ├── 4_methylvalericacid [14 files] ├── 5_methyl_2_hexanone [10 files] ├── acetic_acid [13 files] ├── butyl_acetate [11 files] ├── cyclopentane_carboxylic_acid [15 files] ├── ET [Ethyl Tiglate, 18 files] ├── ethyl_butyrate [10 files] ├── heptanoic_acid [10 files] ├── MVT [Methyl Valerate, 11 files] ├── methyl_benzoate [10 files] ├── pentyl_acetate [10 files ├── salicyl_aldehyde [10 files] ├── benzaldehyde [14 files] ├── butyraldehyde [11 files] ├── butyric_acid [11 files] ├── cinnamaldehye [13 files] ├── ethyl_valerate[11 files] ├── geraniol [11 files] ├── heptyl_acetate [11 files] ├── isobutyric_acid [11 files] ├── m_anisaldehyde [11 files] ├── n_methylpiperidine [14 files] ├── p_anisaldehyde [11 files] ├── propionic_acid [10 files] ├── valeric_acid[11 files] └── test_mouse_data/ # This contains Testing data video files for 35 odors as listed. │ 2_3_pentanedione [10 files] │   │   ├── 1953_072619_100hz_Set52_145r4_009.tif │   │   ├── 1953_072619_100hz_Set52_145r4_018.tif │   . . . ├── 2_ethylbutyric_acid [11 files] ├── 2_ethylhexanal [10 files] ├── 2_heptanone [11 files] ├── 2_methyl_butyraldehyde [12 files] ├── 2_methyl_valeraldehyde [11 files] ├── 2_methylhexanoic_acid [11 files] ├── 33_dimethylbutyricacid [11 files] ├── 3_methylvalericacid [11 files] ├── 3_heptanone [11 files] ├── 4_methylvalericacid [10 files] ├── 5_methyl_2_hexanone [10 files] ├── acetic_acid [ 12 files] ├── butyl_acetate [11 files] ├── cyclopentane_carboxylic_acid [13 files] ├── ET [Ethyl Tiglate, 14 files] ├── ethyl_butyrate [11 files] ├── heptanoic_acid [11 files] ├── MVT/ [Methyl Valerate, 11 files] ├── methyl_benzoate [11 files] ├── pentyl_acetate [11 files] ├── salicyl_aldehyde [10 files] ├── benzaldehyde [11 files] ├── butyraldehyde [11 files] ├──butyric_acid [9 files] ├── cinnamaldehyde [10 files] ├── ethyl_valerate [11 files] ├── geraniol [11 files] ├── heptyl_acetate [11 files] ├── isobutyric_acid [11 files] ├── m_anisaldehyde [10 files] ├── n_methylpiperidine [16 files] ├── p_anisaldehyde [11 files] ├──propionic_acid [11 files] ├── valeric_acid [10 files] *** METHODOLOGICAL INFORMATION Description of methods used for collection/generation of data: Wide-field 1-photon calcium imaging was recorded at a frame rate of 100 Hz, in Thy1-GCaMP6f mice implanted with cranial windows over the olfactory bulb. The work was done under IACUC Protocol at NYU Langone Health, #IA16-00197. Mice were head-fixed during imaging, with monomolecular odors presented for 2 seconds during each trial. The odors were presented to the animals in randomized order. Some odors were presented more frequently, and were injected in between different odors to randomize the trial. Due to this randomization, some odors have a different number of videos than other odors. Instrument- or software-specific information needed to interpret the data: The .tif files can be read and worked on with Python libraries. A sample code for reading and processing the data using python will be linked. People involved with sample collection, processing, analysis and/or submission: The data was collected by Hiro Nakayama at Rinberg Lab. The processing of video files and its conversion to .tif files was done by Joshua S. Harvey. The computational image processing of video files for analysis and submission to archive was done by Vivek K. Agarwal and Joshua S. Harvey.