Single-unit auditory nerve fibre responses of young-adult and aging gerbils
Data files
Apr 15, 2024 version files 26.81 GB
-
all_AN_data.mat
100.56 MB
-
Data_Structure.pdf
367.74 KB
-
G150717.mat
52.69 MB
-
G150730.mat
340.18 MB
-
G150805.mat
103.99 MB
-
G150921.mat
218.34 MB
-
G150922.mat
779.20 MB
-
G150929.mat
62.35 MB
-
G151001.mat
1.04 GB
-
G151104.mat
467.39 MB
-
G151110.mat
90.66 MB
-
G151126.mat
406.24 MB
-
G151203.mat
389.54 MB
-
G151210.mat
252.55 MB
-
G160322.mat
12.76 MB
-
G160412.mat
27.35 MB
-
G160419.mat
144.18 MB
-
G160426.mat
1.99 MB
-
G160504.mat
582.35 MB
-
G160518.mat
104.44 MB
-
G160524.mat
30.32 MB
-
G160531.mat
164.62 MB
-
G160609.mat
25.07 MB
-
G160727.mat
6.04 MB
-
G160803.mat
178.69 MB
-
G160817.mat
186.67 MB
-
G160901.mat
344.50 MB
-
G161110.mat
297.38 MB
-
G170425.mat
187 MB
-
G170508.mat
16.71 MB
-
G170512_1.mat
913.64 MB
-
G170512_2.mat
620.18 MB
-
G170512_3.mat
876.89 MB
-
G170517.mat
23.56 MB
-
G170523.mat
357.81 MB
-
G170712.mat
13.74 MB
-
G170808.mat
9.71 MB
-
G171023.mat
439.07 MB
-
G171204.mat
13.99 MB
-
G171211.mat
496.28 MB
-
G171214.mat
21.92 MB
-
G171221.mat
8.96 MB
-
G180118.mat
38.48 MB
-
G180205.mat
72.81 MB
-
G180406.mat
540.44 MB
-
G180626.mat
59.84 MB
-
G180710.mat
728.51 MB
-
G180717.mat
66.42 MB
-
G190108.mat
372.22 MB
-
G190118.mat
170.09 MB
-
G190129.mat
315.65 MB
-
G190326.mat
224 MB
-
G190411.mat
433.94 MB
-
G190507.mat
36.05 MB
-
G190515.mat
129.21 MB
-
G190603_1.mat
541.54 MB
-
G190603_2.mat
754.05 MB
-
G190611.mat
80.03 MB
-
G190613.mat
70.49 MB
-
G190617.mat
997.67 MB
-
G190704.mat
130.62 MB
-
G190730.mat
19.42 MB
-
G190801.mat
280.85 MB
-
G190806.mat
181.28 MB
-
G190903.mat
83.12 MB
-
G190912.mat
183.57 MB
-
G190920.mat
7.56 MB
-
G191008.mat
148.30 MB
-
G191017.mat
66.04 MB
-
G191022.mat
215.63 MB
-
G191115.mat
554.28 MB
-
G191128.mat
395.84 MB
-
G191217.mat
140.58 MB
-
G191219.mat
7.07 MB
-
G200213.mat
598.06 MB
-
G200225.mat
632.20 MB
-
G200306.mat
295.06 MB
-
G200528.mat
599.91 MB
-
G200616.mat
277.55 MB
-
G200623.mat
650.61 MB
-
G200901.mat
97.41 MB
-
G201001_1.mat
493.42 MB
-
G201001_2.mat
513.52 MB
-
G201001_3.mat
459.22 MB
-
G201103.mat
273.52 MB
-
G201112.mat
186.17 MB
-
G201208.mat
157.15 MB
-
G201210.mat
127.97 MB
-
G201215.mat
137.04 MB
-
G201217.mat
19.76 MB
-
G201222.mat
133.30 MB
-
G211118.mat
496.75 MB
-
G211221.mat
370.92 MB
-
G220201.mat
164.12 MB
-
G220222.mat
58.26 MB
-
G220301.mat
97.36 MB
-
G220331.mat
106.22 MB
-
G220407.mat
9.85 MB
-
G220602.mat
36.82 MB
-
G220609.mat
248.39 MB
-
G220726.mat
52.19 MB
-
G220901.mat
223.82 MB
-
G220908.mat
236.44 MB
-
G220922.mat
111.13 MB
-
G221006.mat
10.49 MB
-
G221013.mat
7.74 MB
-
G221110.mat
44.20 MB
-
G230511.mat
63.40 MB
-
G230907.mat
113.31 MB
-
G231218.mat
143.11 MB
-
G240111.mat
114.57 MB
-
metadata.csv
5.43 KB
-
README.md
4.01 KB
Abstract
This dataset was collected to study the functional consequences of age-related hearing loss for the auditory nerve, which carries acoustic information from the periphery to the central auditory system. Using high-impedance glass electrodes, raw voltage traces and spike times were recorded from more than one thousand single fibres of the auditory nerve of young-adult, middle-aged, and old Mongolian gerbils raised in a quiet environment. The dataset contains not only responses to simple acoustic stimuli to characterize the fibres, but also to more complex stimuli, such as speech logatomes in background noise and Schroeder-phase stimuli. A software toolbox is provided to search through the dataset, to plot various analysed outcomes, and to give insight into the analyses. This dataset may serve as a valuable resource to test further hypotheses about age-related hearing loss. Additionally, it can aid in optimizing available computational models of the auditory system, which can contribute to, or eventually even fully replace, animal experiments.
README: Single-unit auditory nerve fibre responses of young-adult and aging gerbils
https://doi.org/10.5061/dryad.qv9s4mwn4 (opens in new window)
This dataset contains the raw and processed data derived from single-unit auditory nerve fibre recordings in young-adult and aging gerbils. Using high-impedance, glass electrodes, raw voltage traces and spike times were recorded from over one-thousand single fibres of the auditory nerve of Mongolian gerbils raised in a quiet environment. Software was written and tested in MATLAB version R2023b.
Description of the data and file structure
All raw, processed, and metadata of one animal is saved in one datafile ('G#.mat'). Such a .mat file contains one variable, 'exp', which is structured equally between all experiments. The content of each field in this struct is described in the document 'Data_Structure.pdf'. An overview of the metadata of each animal, e.g. age, hearing sensitivity, presented complex acoustic stimuli, number of single fibres, etc., can be found in 'metadata.csv'. Furthermore, there is one file with all animals combined into one struct called 'all_AN_data.mat'. In this file, the raw waveforms are removed to make the file size manageable. This file can be used to plot the outcomes of the analyses, e.g. best frequency vs. threshold of all fibres. For more details, please see the accompanying Data Descriptor manuscript.
Code to help search through the dataset
Three scripts are provided to help the user search through the full dataset as well as within a struct of one animal. check_dataset_metadata.m loops through the 'all_exp' struct and focusses on the metadata of the experiments. It recreates the metadata sheet, which can be used to select an animal of interest and investigate it further in check_dataset_animal.m. check_dataset_units.m loops through the 'all_exp' struct and focusses on the analysed outcomes of the single units. It can be used to plot any of these outcomes against each other, typically with the fibre’s best frequency on the horizontal axis. check_dataset_animal.m loops through the units of an ‘exp’ struct of one animal. It generates a scatterplot of the threshold against the best frequency of all the fibre’s recorded in that animal and a plot with all rate-level functions of that animal plotted in one graph. It also calls the function check_AN.m, which plots of a given recording the unfiltered first trial, the inter-spike interval histogram, the first 300 spike waveforms, and the median spike waveform +/- 95% confidence interval. The script also calls the function makePSTH.m, which is used to generate a peri-stimulus time histogram (PSTH) of all responses to tone bursts at or close to a given stimulus level above the fibre’s threshold.
Code to re-analyse the spike times for auditory nerve fibre characterization
The script call_extract_func.m calls all functions that were used to generate the analysed outcomes of one unit of one animal. These include the following functions:
1. BFextract_func.m, which generates the frequency-response curve to derive best frequency.
2. CFextract_func.m, which generates the receptive field and tuning curve to derive characteristic frequency, threshold, and Q10dB, a measure of frequency selectivity.
3. PHextract_func.m, which calculates vector strength and plots it as a function of stimulus level.
4. CLICKextract_func.m, which calculates click latency in three different ways and visually demonstrates the outcomes of each method.
5. RLFextract_func.m, which generates the rate-level function to derive threshold and rates at each stimulus level.
6. SRextract_func.m, which calculates the spontaneous rate from a long recording in silence.
Sharing/Access information
We plan to make both the data and the software also available in the Auditory Modeling Toolbox v1.6 under data_heeringa2024 and exp_heeringa2024.
Methods
The dataset presented here contains the raw waveforms and spike times from single auditory nerve fibres of young-adult, middle-aged, and old gerbils, while presenting a variety of acoustic stimuli to assess the functioning of the single fibres. Gerbils were anesthetized with ketamine/xylazine injections and auditory brainstem responses (a type of compound response) were recorded to derive a measure of their general hearing sensitivity. The auditory nerve was approached dorsally through the cerebellum and a sharp, high-impedance glass electrode was slowly moved through the nerve. Single-unit recordings were made for as long as the surgical preparation was stable. Afterwards, spikes in the data were identified, data files were organized into folders of one single unit, data were analysed to characterize the fibre, and a set of criteria was used to ensure the single unit derived from the auditory nerve bundle. Methods are described in detail in the accompanying manuscript.