Closed-loop enhancement and neural decoding of cognitive control in humans. [PDF]
Nat Biomed Eng, 2023 Closed-loop electrical stimulation of the internal capsule of participants undergoing intracranial epilepsy monitoring improved the participants’ performance on a cognitive conflict task, and performance could be decoded from electrode activity. Deficits
Basu I +15 more
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Shared Graph Neural Network for Channel Decoding [PDF]
Applied Sciences, 2023 With the application of graph neural network (GNN) in the communication physical layer, GNN-based channel decoding algorithms have become a research hotspot.
Qingle Wu +5 more
doaj +2 more sources
Current Advances in Neural Decoding [PDF]
, 2019 Neural decoding refers to the extraction of semantically meaningful information from brain activity patterns. We discuss how advances in machine learning drive new advances in neural decoding. While linear methods allow for the reconstruction of basic stimuli from brain activity, more sophisticated nonlinear methods are required when reconstructing ...
Gerven, M.A.J. van +3 more
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A neural speech decoding framework leveraging deep learning and speech synthesis
Nature Machine IntelligenceRecent research has focused on restoring speech in populations with neurological deficits. Chen, Wang et al. develop a framework for decoding speech from neural signals, which could lead to innovative speech prostheses.
Orrin Devinsky +2 more
exaly +2 more sources
Hypernetwork Based Model-Driven Channel Neural Decoding
IEEE AccessChannel decoding algorithms based on model-driven deep learning, also known as channel neural decoding algorithms, have received a lot of attention in recent years.
Yuanhui Liang +4 more
doaj +3 more sources
An EEG Dataset for Multimodal Semantic Alignment and Neural Decoding during Reading and Listening [PDF]
Scientific DataEEG-based neural decoding requires large-scale benchmark datasets. Paired brain-language data across speaking, listening, and reading modalities are essential for aligning neural activity with the semantic representation of large language models (LLMs ...
Sitong Chen +10 more
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Multiscale fusion enhanced spiking neural network for invasive BCI neural signal decoding
Frontiers in NeuroscienceBrain-computer interfaces (BCIs) are an advanced fusion of neuroscience and artificial intelligence, requiring stable and long-term decoding of neural signals. Spiking Neural Networks (SNNs), with their neuronal dynamics and spike-based signal processing,
Yu Song +5 more
doaj +3 more sources
Fault-tolerant quaternary belief propagation decoding based on a neural network
Frontiers in Physics, 2023 The article discusses the challenge of finding an efficient decoder for quantum error correction codes for fault-tolerant experiments in quantum computing.
Naihua Ji +5 more
doaj +1 more source
Deep learning with convolutional neural networks for EEG decoding and visualization [PDF]
Human Brain Mapping, 2017 Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data.
R. Schirrmeister +8 more
semanticscholar +1 more source
High-resolution neural recordings improve the accuracy of speech decoding
Nature Communications, 2023 Patients suffering from debilitating neurodegenerative diseases often lose the ability to communicate, detrimentally affecting their quality of life.
Suseendrakumar Duraivel +12 more
doaj +1 more source