ArticleNature communications2022
Imagined speech can be decoded from low- and cross-frequency intracranial EEG features.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.
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Who cites it
58 citing papers in PubMed, 1 synthesis or guideline pooled it, 186 citations in OpenAlex.
- Artificial intelligence for brain-to-speech decoding in paralysis: a systematic review.BMC medical informatics and decision making · 2026Pooled it
- A neural architecture for imagined and overt speech motor dynamics.Nature neuroscience · 2026Article
- Temporally structured motor and auditory representations in covert syllable production.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- 3D-Printable, Honeycomb-Inspired Tissue-Like Bioelectrodes for Patient-Specific Neural Interface.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Spatiotemporal Dynamics in Prespeech Semantic Category Decoding: An Intracranial EEG Study.eNeuro · 2026Article
- A general model based on Riemannian manifold for stable decoding movement trajectory from ECoG signals.iScience · 2026Article
- Early Prediction of Delirium in Postcardiac Surgery Patients: Machine Learning Model Development and External Validation.JMIR medical informatics · 2026Article
- Soft Multiaxial Strain Mapping Interface with AI-Driven Decoding for Silent Speech in Noise.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- An open dataset of multidimensional signals based on different speech patterns in pragmatic Mandarin.Scientific data · 2025Article
- Speech sequencing in the human precentral gyrus.Nature human behaviour · 2025Article
- Emerging Therapeutic Strategies in Intracerebral Hemorrhage: Enhancing Neurogenesis and Functional Recovery.MedComm · 2025Review
- Mimed speech as an intermediary state between overt and imagined speech production in an electrocorticography study.Scientific reports · 2025Article
- Heart Talk: Emotional Inner Speech Increases Heart Rate.Psychophysiology · 2025Article
- ArEEG: an Open-Access Arabic Inner Speech EEG Dataset.Scientific data · 2025Article
- Article
- ERP Signals During Speech Articulation: Does Auditory Feedback Mask Other Ongoing Cognitive-motor Processes?Brain topography · 2025Article
- Orbitofrontal High-Gamma Reflects Spike-Dissociable Value and Decision Mechanisms.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Stretchable and Wearable Sensors for Contact Touch and Gesture Recognition Based on Poling-Free Piezoelectric Polyester Elastomer.Polymers · 2025Article
- VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language.Scientific data · 2025Article
- Learning to operate an imagined speech Brain-Computer Interface involves the spatial and frequency tuning of neural activity.Communications biology · 2025Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 5 countries.
Funding
Abstract
Reconstructing intended speech from neural activity using brain-computer interfaces holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech has met limited success, mainly because the associated neural signals are weak and variable compared to overt speech, hence difficult to decode by learning algorithms. We obtained three electrocorticography datasets from 13 patients, with electrodes implanted for epilepsy evaluation, who performed overt and imagined speech production tasks. Based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future brain computer interfaces, and assessed their performance to discriminate speech items in articulatory, phonetic, and vocalic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings show that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding.
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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.