Data from: Cochlear tuning in early aging estimated with three methods
Data files
Dec 30, 2025 version files 233.29 MB
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allData25-Jun-2024.csv
2.03 MB
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audioData_2024-05-13.csv
13.40 KB
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Cochlear-Tuning-in-Early-Aging-Estimated-with-Three-Methods-main.zip
25.86 KB
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indvLRFQ2024-06-28.csv
96.49 MB
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participantTestEar.csv
963 B
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README.md
4.62 KB
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sfPhase.csv
134.73 MB
Abstract
Age-related hearing loss (ARHL) currently affects over 20 million adults in the U.S., and its prevalence is expected to increase as the population ages. However, little is known about the earliest manifestations of ARHL, including its influence on auditory function beyond the threshold of sensation. This work explores the effects of early aging on frequency selectivity (i.e., ‘tuning’), a critical feature of normal hearing function. Tuning is estimated using both behavioral and physiological measures – fast psychophysical tuning curves (fPTC), distortion product otoacoustic emission level ratio functions (DPOAE LRFs), and stimulus-frequency OAE (SFOAE) phase gradient delay. All three measures were selected because they have high potential for clinical translation but have not been compared directly in the same sample of ears. Results indicate that there may be subtle changes in tuning during early aging, even in ears with clinically normal audiometric thresholds. Additionally, there are notable differences in tuning estimates derived from the three measures. Psychophysical tuning estimates are highly variable and statistically significantly different from OAE-derived tuning estimates, suggesting that behavioral tuning is uniquely influenced by factors not affecting OAE-based tuning. Across all measures, there is considerable individual variability that warrants future investigation. Collectively, this work suggests that age-related auditory decline begins in relatively young ears (< 60 years) and in the absence of traditionally defined “hearing loss.” These findings suggest the potential benefit of characterizing ARHL beyond threshold and establishing a gold standard for measuring frequency selectivity in humans.
https://doi.org/10.5061/dryad.7m0cfxq5d
Description of the data and file structure
Files include:
1) allData25-Jun-2024.csv: fPTC data for each participant, including derived Qerb estimates
2) audioData_2024-05-13.csv: Audiometric thresholds from participants
3) indvLRFQ2024-06-28.csv: DPOAE LRF data for each participant, including derived Qerb estimates
4) participantTestEar.csv: Test ear of each participant
5) sfPhase.csv: SFOAE phase data from each participant, including derived Qerb estimates. Note that Qerb*_*S is the column used for data analysis in this manuscript
6) Cochlear-Tuning-in-Early-Aging-Estimated-with-Three-Methods-main.zip: R Code used to analyze data and plot manuscript figures. This code is also available in a GitHub Repo (Public Archive).
Note that some of the.csv files contain data from participants who were not included in the final data set (e.g., a participant did not qualify for study but had audiometric thresholds tested). These participants are filtered out from the dataframes in the associated R code used for data plotting/analysis found here: https://github.com/cobycoburn/Cochlear-Tuning-in-Early-Aging-Estimated-with-Three-Methods
This repo is also linked to below.
Files and variables
File: audioData_2024-05-13.csv
Description: Audiometric threshold data
Variables
- ID: Participant ID
- Group: Participant age group
- Frequency: Test frequency (Hz)
- Left: Left ear audiometric threshold (dB HL)
- Right: Right ear audiometric threshold (dB HL)
File: allData25-Jun-2024.csv
Description: fPTC data
Variables
- id: Participant ID
- testEar: Participant test ear
- group: Participant age group
- probeFreq: Probe frequency (Hz)
- noiseFreq: Noise frequency (Hz)
- noiseLevel: Noise level (dB FPL)
- probeLevel: Probe level (dB FPL)
- L: Smoothed noise level (dB FPL; LOESS smoothed, 25% span)
- ftip: Tuning curve tip frequency (Hz)
- Ltip: Tuning curve tip level (dB SPL)
- BWerb: Equivalent rectangular bandwidth (ERB)
- Q10: Tuning factor (Q10)
- Qerb: Tuning factor (Qerb)
- sl_ltip: Tuning curve slope (low frequency side, tip)
- sl_ltail: Tuning curve slope (low frequency side, tail)
- sl_lfull: Tuning curve slope (low frequency side, full)
- sl_hfull: Tuning curve slope (high frequency side, full)
File: participantTestEar.csv
Description: Test ear of participants
Variables
- ID: Participant ID
- testEar: Participant test ear
File: indvLRFQ2024-06-28.csv
Description: DPOAE LRF data
Variables
- f1: f1 frequency (Hz)
- f2: f2 frequency (Hz)
- findx: Variable for indexing; not used in analysis
- r: f2/f1 ratio
- LRF: DPOAE level (SPL)
- NF: Noise floor level (SPL)
- type: DPOAE type (0 = unmirrored; 1 = mirrored)
- id: Participant ID
- Qerb: Tuning factor (Qerb)
- group: Participant age group
- highRatiom: Slope of high ratio side of curve
- highRatiob: Intercept of high ratio side of curve (not used)
- peak: Peak level of DPOAE LRF (dB SPL)
- f1indx: Variable for indexing; not used in analysis
File: sfPhase.csv
Description: SFOAE Phase Gradient Delay data
Variables
- f: Probe frequency (Hz)
- sf: SFOAE level (dB SPL)
- nf: Noise floor level (dB SPL)
- phi: SFOAE phase (cycles)
- snr: Signal-to-noise ratio (SNR) of SFOAE vs. Noise floor level
- id: Participant ID
- cf: Center frequency, averaged around 1/4 octave bands
- group: Participant age group
- Qerb_S: Tuning factor (Qerb) estimated using "Shera Method" (see Wilson et al. 2021). This is the tuning factor analyzed in the manuscript
- Qerb_M: Tuning factor (Qerb) estimated using "Moleti Method" (see Wilson et al. 2021). This is not used in the manuscript
Code/software
Cochlear-Tuning-in-Early-Aging-Estimated-with-Three-Methods-main.zip contains all code used to analyze and plot data.
- TuningManuscriptMain.R: Primary analysis script.
- audiogramTuningManuscript.R: Loads and plots audiogram data.
- LRFplot_TuningManuscript.R: Loads and plots DPOAE Level Ratio Function data.
- sfoaePhasePlot_TuningManuscript.R: Loads and plots SFOAE phase data.
- fptcPlot_TuningManuscript.R: Loads and plots fPTC data.
These same scripts are also available via GitHub:
https://github.com/cobycoburn/Cochlear-Tuning-in-Early-Aging-Estimated-with-Three-Methods
These data were collected as part of CCG's dissertation experiments at Northwestern University. They have subsequently been used to prepare a manuscript for publication. Associated code for plotting/data analysis for this manuscript can be found on GitHub: https://github.com/cobycoburn/Cochlear-Tuning-in-Early-Aging-Estimated-with-Three-Methods
