DOI: 10.5061/dryad.dncjsxm7c
title: Data from: Direct piriform-to-auditory cortical projections shape auditory-olfactory integration

description: In a real-world environment, the brain must integrate information from
 multiple sensory modalities, including the auditory and olfactory systems.
 However, little is known about the neuronal circuits governing how odors
 influence and modulate sound processing. Here, we investigated the
 mechanisms underlying auditory-olfactory integration using anatomical,
 electrophysiological, and optogenetic approaches, focusing on the auditory
 cortex as a key locus for cross-modal integration. First, retrograde and
 anterograde viral tracing strategies revealed a direct projection from the
 piriform cortex to the auditory cortex. Next, using in vivo
 electrophysiological recordings of neuronal activity in the auditory
 cortex of awake male or female mice, we found that odors modulate auditory
 cortical responses to sound. Finally, we used in vivo optogenetic
 manipulations during electrophysiology to demonstrate that olfactory
 modulation in auditory cortex, specifically, odor-driven enhancement of
 sound responses, depends on direct input from the piriform cortex.
 Together, our results identify a novel role of piriform-to-auditory
 cortical circuitry in shaping olfactory modulation in the auditory cortex,
 shedding new light on the neuronal mechanisms underlying
 auditory-olfactory integration.
description: # Data from Vogler et al., 2024 **Direct piriform-to-auditory cortical
 projections shape auditory-olfactory integration** Nathan W. Vogler, Ruoyi
 Chen, Alister Virkler, Violet Y. Tu, Jay A. Gottfried, and Maria N. Geffen
 [https://doi.org/10.5061/dryad.dncjsxm7c](https://doi.org/10.5061/dryad.dncjsxm7c) Contains source data for figures in Vogler et al., 2024 Code (Python Jupyter notebooks) for analyzing data is included here (Zenodo) and also available on Github: [https://github.com/geffenlab/Vogler_2024](https://github.com/geffenlab/Vogler_2024) * Requires Python 3 (Anaconda Distribution); Requires source data to be in same folder as Jupyter notebook(s); Creates Figure pdfs in same folder ## Description of the data and file structure **DATA:** Source data for **Figures 1 & 2** (Anatomy); used by Code_1_2_Anatomy.ipynb : * Data_1_Anatomy_cellcounts.xlsx * Excel workbook: Cell counts from retrograde tracing experiments. Number of cells labeled with GFP/tdTomato in anterior and posterior piriform cortex (Figures 1C and 1G). * Data_2C_Anatomy_AC_region_table.csv * Comma-separated value file: Cell counts from anterograde tracing experiments, by cortical region. Number of cells labeled with tdTomato across auditory cortical regions (Figure 2C). * Data_2D_Anatomy_AC_depths.mat * MATLAB formatted data: Cell counts from anterograde tracing experiments, by cortical layer. Depth distribution (normalized cortical depth, arbitrary units) of labeled cells in each auditory cortical region (Figure 2D). MATLAB objects: allDepths, Au1_depths, AuD_depths, AuV_depths, TeA_depths. Source data for **Figure 3** (Schematics/examples); used by Code_3_Schematics.ipynb : * Data_3B_example_sniff.pickle * Python Dictionary: Mouse sniff trace (arbitrary units) for example trial during in vivo electrophysiology in auditory cortex (Figure 3B). * Data_3D_example_raster.pickle * Python Dictionary: Example raster plot (neuronal spiking) from a recorded unit (Figure 3D). * Data_3F_example_raster_opto.pickle * Python Dictionary: Example raster plot (neuronal spiking) from a recorded unit with optogenetics (Figure 3F).  * Data_3G_example_plot_opto.pickle * Python Dictionary: Average firing rates (Hz) of example recorded unit in response to various sound levels (Figure 3G). * Data_3H_example_psth_opto.pickle * Python Dictionary: Peristimulus time histogram (PSTH) of example recorded unit in response to 15 dB SNR sound (Figure 3H). Source data for **Figure 4** (Electrophysiology); used by Code_4_Ephys.ipynb : * Data_4_Ephys.pickle * Python Pandas DataFrame: Stimuli and neuronal spiking data (Figure 4A-L). Source data for **Figure 5** (Electrophysiology & Optogenetics: stGtACR1); used by Code_5_Ephys_Opto_stGtACR1.ipynb : * Data_5_Ephys_Opto_stGtACR1.pickle * Python Pandas DataFrame: Stimuli and neuronal spiking data (Figure 5A-J). Source data for **Figure 6** (Electrophysiology & Optogenetics: Control); used by Code_6_Ephys_Opto_Control.ipynb : * Data_6_Ephys_Opto_Control.pickle * Python Pandas DataFrame: Stimuli and neuronal spiking data (Figure 6B-G). **SOFTWARE:** * Code_1_2_Anatomy.ipynb * Source data: * Data_1_Anatomy_cellcounts.xlsx * Data_2C_Anatomy_AC_region_table.csv * Data_2D_Anatomy_AC_depths.mat * Produces: * Figure 1C, Figure 1G, Figure 2D, Figure 2E * Code_3_Schematics.ipynb * Source data: * Data_3B_example_sniff.pickle * Data_3D_example_raster.pickle * Data_3F_example_raster_opto.pickle * Data_3G_example_plot_opto.pickle * Data_3H_example_psth_opto.pickle * Produces: * Figure 3B, Figure 3D, Figure 3F, Figure 3G, Figure 3H * Code_4_Ephys.ipynb * Source data: * Data_4_Ephys.pickle * Produces:  * Figure 4ABCDE, Figure 4FGHIJ, Figure 4KL * Code_5_Ephys_Opto_stGtACR1 * Source data: * Data_5_Ephys_Opto_stGtACR1.pickle * Produces: * Figure 5ABCD, Figure 5EFGH, Figure 5IJ * Data_6Eleft_LEDindex_stGtACR1.pickle * Data_6Eright_LEDindexAM_stGtACR1.pickle * Code_6_Ephys_Opto_Control * Source data: * Data_6_Ephys_Opto_Control.pickle * Data_6Eleft_LEDindex_stGtACR1.pickle (from Code_5_Ephys_Opto_stGtACR1) * Data_6Eright_LEDindexAM_stGtACR1.pickle (from Code_5_Ephys_Opto_stGtACR1) * Produces: * Figure 6BCDEFG