ArticleNature neuroscience2023
Dissecting neural computations in the human auditory pathway using deep neural networks for speech.
Article in Nature neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed, 96 citations in OpenAlex.
- Review
- Brain-AI convergence: Generative world models and hierarchical attention for human intelligence.Patterns (New York, N.Y.) · 2026Review
- An artificial neuromorphic interface for auditory restoration.Nature materials · 2026Article
- A Fine-grained Spatiotemporal ECoG Dataset during Speech Perception in Tonal Language.Scientific data · 2026Article
- Dual computational systems in the development and evolution of mammalian brains.Science advances · 2026Article
- A large-scale fMRI dataset for vision-language semantic association.Scientific data · 2026Article
- High-fidelity neural speech reconstruction through an efficient acoustic-linguistic dual-pathway framework.eLife · 2026Article
- Deep Sound Synthesis Matched to Brain Activity Recapitulates Preferential Responses to Speech and Music.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Animal behavioral analysis and neural encoding with transformer-based self-supervised pretraining.ArXiv · 2026Article
- Understanding the Brain as a Mentalizing Machine with a Symbol Grounding Function.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Review
- A deep neural network model of audiovisual speech recognition reports the McGurk effect.Psychonomic bulletin & review · 2026Article
- Healing Effects of Music, Healing Frequencies, and Binaural Beats for Traumatic Brain Injury and Stroke: A Review.Cureus · 2026Review
- Disentangling Superpositions: Interpretable Brain Encoding Model with Sparse Concept Atoms.bioRxiv : the preprint server for biology · 2026Article
- Article
- Article
- Neurons in auditory cortex integrate information within a constrained and context-invariant temporal window.Current biology : CB · 2025Article
- A Deep Neural Network Model of Audiovisual Speech Recognition Reports the McGurk Effect.bioRxiv : the preprint server for biology · 2025Article
- Temporal structure of natural language processing in the human brain corresponds to layered hierarchy of large language models.Nature communications · 2025Article
- Temporal integration in human auditory cortex is predominantly yoked to absolute time.Nature neuroscience · 2025Article
- CIRE: A Chinese EEG Dataset for decoding speech intention modulated by prosodic emotion.Scientific data · 2025Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
The human auditory system extracts rich linguistic abstractions from speech signals. Traditional approaches to understanding this complex process have used linear feature-encoding models, with limited success. Artificial neural networks excel in speech recognition tasks and offer promising computational models of speech processing. We used speech representations in state-of-the-art deep neural network (DNN) models to investigate neural coding from the auditory nerve to the speech cortex. Representations in hierarchical layers of the DNN correlated well with the neural activity throughout the ascending auditory system. Unsupervised speech models performed at least as well as other purely supervised or fine-tuned models. Deeper DNN layers were better correlated with the neural activity in the higher-order auditory cortex, with computations aligned with phonemic and syllabic structures in speech. Accordingly, DNN models trained on either English or Mandarin predicted cortical responses in native speakers of each language. These results reveal convergence between DNN model representations and the biological auditory pathway, offering new approaches for modeling neural coding in the auditory cortex.
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Registered trials
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.