[PDF][PDF] Reconstructing language from brain signals and deconstructing adversarial thought-reading
Tang et al. 1 report a noninvasive brain-computer interface (BCI) that reconstructs perceived
and intended continuous language from semantic brain responses. The study offers new …
and intended continuous language from semantic brain responses. The study offers new …
Decoding the continuous motion imagery trajectories of upper limb skeleton points for EEG-based brain–computer interface
In the field of brain–computer interface (BCI), brain decoding using electroencephalography
(EEG) is an essential direction, and motion imagery EEG-based BCI can not only help …
(EEG) is an essential direction, and motion imagery EEG-based BCI can not only help …
[HTML][HTML] Ultrasensitive textile strain sensors redefine wearable silent speech interfaces with high machine learning efficiency
This work introduces a silent speech interface (SSI), proposing a few-layer graphene (FLG)
strain sensing mechanism based on thorough cracks and AI-based self-adaptation …
strain sensing mechanism based on thorough cracks and AI-based self-adaptation …
The speech neuroprosthesis
Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by
directly decoding speech from intact cortical activity has the potential to restore natural …
directly decoding speech from intact cortical activity has the potential to restore natural …
[HTML][HTML] Opportunities, pitfalls and trade-offs in designing protocols for measuring the neural correlates of speech
Decoding speech and speech-related processes directly from the human brain has
intensified in studies over recent years as such a decoder has the potential to positively …
intensified in studies over recent years as such a decoder has the potential to positively …
An interpretable deep learning model for speech activity detection using electrocorticographic signals
Numerous state-of-the-art solutions for neural speech decoding and synthesis incorporate
deep learning into the processing pipeline. These models are typically opaque and can …
deep learning into the processing pipeline. These models are typically opaque and can …
[HTML][HTML] Revealing the spatiotemporal brain dynamics of covert speech compared with overt speech: A simultaneous EEG-fMRI study
W Zhang, M Jiang, KAC Teo, R Bhuvanakantham… - NeuroImage, 2024 - Elsevier
Covert speech (CS) refers to speaking internally to oneself without producing any sound or
movement. CS is involved in multiple cognitive functions and disorders. Reconstructing CS …
movement. CS is involved in multiple cognitive functions and disorders. Reconstructing CS …
Speech and music recruit frequency-specific distributed and overlapping cortical networks
To what extent does speech and music processing rely on domain-specific and domain-
general neural networks? Using whole-brain intracranial EEG recordings in 18 epilepsy …
general neural networks? Using whole-brain intracranial EEG recordings in 18 epilepsy …
Speech imagery decoding as a window to speech planning and production
Speech imagery (the ability to generate internally quasi-perceptual experiences of speech
events) is a fundamental ability tightly linked to important cognitive functions such as inner …
events) is a fundamental ability tightly linked to important cognitive functions such as inner …
Self-Supervised Learning of Neural Speech Representations From Unlabeled Intracranial Signals
S Lesaja, M Stuart, JJ Shih, PZ Soroush… - IEEE …, 2022 - ieeexplore.ieee.org
Neuroprosthetics have demonstrated the potential to decode speech from intracranial brain
signals, and hold promise for one day returning the ability to speak to those who have lost it …
signals, and hold promise for one day returning the ability to speak to those who have lost it …