ArticlePLoS computational biology2020
Spiking network optimized for word recognition in noise predicts auditory system hierarchy.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 38 citations in OpenAlex.
- Noise statistics drive background- and channel-specific interference in auditory midbrain representations of speech.bioRxiv : the preprint server for biology · 2026Article
- Rethinking hierarchy: the auditory system as an integrated cortical-subcortical network.Nature reviews. Neuroscience · 2026Review
- Temporal integration in human auditory cortex is predominantly yoked to absolute time.Nature neuroscience · 2025Article
- Temporal recurrence as a general mechanism to explain neural responses in the auditory system.Communications biology · 2025Article
- Interference of Mid-level Speech and Noise Statistics Underlies Human Speech Recognition Sensitivity in Natural Environmental Noise.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Models optimized for real-world tasks reveal the task-dependent necessity of precise temporal coding in hearing.Nature communications · 2024Article
- Models optimized for real-world tasks reveal the task-dependent necessity of precise temporal coding in hearing.bioRxiv : the preprint server for biology · 2024Article
- Snn and sound: a comprehensive review of spiking neural networks in sound.Biomedical engineering letters · 2024Review
- Noises on-How the Brain Deals with Acoustic Noise.Biology · 2024Review
- Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions.PLoS biology · 2023Article
- Human-Like Modulation Sensitivity Emerging through Optimization to Natural Sound Recognition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Encoding of speech in convolutional layers and the brain stem based on language experience.Scientific reports · 2023Article
- Quantitative models of auditory cortical processing.Hearing research · 2023Review
- Two stages of bandwidth scaling drives efficient neural coding of natural sounds.PLoS computational biology · 2023Article
- Inferring the basis of binaural detection with a modified autoencoder.Frontiers in neuroscience · 2023Article
- Multiscale temporal integration organizes hierarchical computation in human auditory cortex.Nature human behaviour · 2022Article
- Understanding Adaptive, Multiscale Temporal Integration In Deep Speech Recognition Systems.Advances in neural information processing systems · 2021Article
- Cascaded Tuning to Amplitude Modulation for Natural Sound Recognition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
The auditory neural code is resilient to acoustic variability and capable of recognizing sounds amongst competing sound sources, yet, the transformations enabling noise robust abilities are largely unknown. We report that a hierarchical spiking neural network (HSNN) optimized to maximize word recognition accuracy in noise and multiple talkers predicts organizational hierarchy of the ascending auditory pathway. Comparisons with data from auditory nerve, midbrain, thalamus and cortex reveals that the optimal HSNN predicts several transformations of the ascending auditory pathway including a sequential loss of temporal resolution and synchronization ability, increasing sparseness, and selectivity. The optimal organizational scheme enhances performance by selectively filtering out noise and fast temporal cues such as voicing periodicity, that are not directly relevant to the word recognition task. An identical network arranged to enable high information transfer fails to predict auditory pathway organization and has substantially poorer performance. Furthermore, conventional single-layer linear and nonlinear receptive field networks that capture the overall feature extraction of the HSNN fail to achieve similar performance. The findings suggest that the auditory pathway hierarchy and its sequential nonlinear feature extraction computations enhance relevant cues while removing non-informative sources of noise, thus enhancing the representation of sounds in noise impoverished conditions.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.