DOI: 10.7910/dvn/d9khxh
title: Replication Data for: Modeling the impact of cochlear nerve degeneration on speech recognition performance

description: Cochlear nerve degeneration (CND), the loss of synapses between inner hair cells and auditory nerve fibers (ANFs), has emerged as a leading candidate for the neural basis of "hidden hearing loss", a condition in which listeners experience speech-in-noise difficulties that cannot be fully explained by audiometric thresholds. This form of primary neural de-afferentation preferentially affects low- and medium-spontaneous rate (SR) fibers, which are critical for encoding acoustic features such as amplitude modulations, especially under challenging listening conditions such as noisy backgrounds. Although CND is well established in animal models and post-mortem human studies, its perceptual consequences remain poorly understood due to the inability to directly assess synaptic integrity in living humans. Here, we combine behavioral testing, physiologically grounded modeling of ANFs, and deep neural network (DNN) decoding to evaluate how SR-specific fiber loss degrades speech recognition in noise. Audiometric thresholds and word recognition scores for time-compressed, reverberant NU-6 words were obtained from 395 cognitively normal adults aged 18–80. To isolate the neural contribution to speech encoding, we simulated ANF activity using a phenomenological model of the auditory periphery under three CND profiles, varying the survival of SR fiber classes. Neurograms were input to two DNN architectures trained on speech classification tasks. While both networks achieved high accuracy, only the deeper, more constrained model produced recognition scores consistent with human performance and showed sensitivity to CND. These findings provide a mechanistic link between synaptopathy and speech-in-noise difficulties and establish a computational framework for evaluating the perceptual impact of hidden hearing loss
description: DATA AND FILE OVERVIEW
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NN_WR_training_example.ipynb or 
NN_WR_training_example.html - an example of code to train Neural Network models on Word Recognition tasks.

NN_WR_performance_example.ipynb or NN_WR_performance_example.html - an example of code to test NN performance on WR.

Age_WRS65_PTASt_PTAEHF.xlsx - Excel file containing participant ages, word recognition scores, and audiometric thresholds.
- “Subject ID#” - participant ID
- “Age” - participant age
- “WR65” - word recognition scores
- “PTASt” - audiometric thresholds measured at standard audiometric frequencies
- “PTAEHF” - audiometric thresholds measured at extended high frequencies
- “250” / “500” / “1000” / “2000” / “3000” / “4000” / “6000” / “8000” / “9000” / “10000” / “11200” / “12500” / “14000” / “16000” - audiometric thresholds were measured at the corresponding frequencies in Hz.
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Training_and_Test_Data_2025/psths_Training_SNRs_11_30/ - training data to train Neural Networks were generated at signal-to-noise ratios (SNRs) between 11 dB and 30 dB in 1 dB steps.
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Training_and_Test_Data_2025/psths_NormalHearing_SNRs_10_5_0dB / - “Normal Innervation” test data were generated at 10, 5, and 0 dB SNR.
Training_and_Test_Data_2025/psths_NormalHearing_SNRs_5_10_15dB/ - “Normal Innervation” test data were generated at -5, -10, and -15 dB SNR.
Training_and_Test_Data_2025/psths_NormalHearing_SNRs_20_25_30dB/ - “Normal Innervation” test data were generated at -20, -25, and -30 dB SNR.
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Training_and_Test_Data_2025/psths_CND_007_SNRs_10_5_0dB/ - “High-SR only” test data were generated at 10, 5, and 0 dB SNR.
Training_and_Test_Data_2025/psths_CND_007_SNRs_5_10_15dB/ - “High-SR only” test data were generated at -5, -10, and -15 dB SNR.
Training_and_Test_Data_2025/psths_CND_007_SNRs_20_25_30dB/ - “High-SR only” test data were generated at -20, -25, and -30 dB SNR.
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Training_and_Test_Data_2025/psths_CND_003_SNRs_10_5_0dB/ - “Severe Neural Loss” test data were generated at 10, 5, and 0 dB SNR.
Training_and_Test_Data_2025/psths_CND_003_SNRs_5_10_15dB/ - “Severe Neural Loss” test data were generated at -5, -10, and -15 dB SNR.
Training_and_Test_Data_2025/psths_CND_003_SNRs_20_25_30dB/ - “Severe Neural Loss” test data were generated at -20, -25, and -30 dB SNR.
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NN2_L16_N32_E500_25words_SNRs_11_30_dBs.keras - trained Neural Network 2
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The .keras file of trained Neural Network 1 exceeds file upload limit and can be available upon reasonable request.
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