4 citations · 10 across the 9 of their papers we have counts for
9 papers
Towards unified brain-to-text decoding across speech production and perception
Zhizhang Yuan, Yang Yang, Gaorui Zhang +7
Speech production and perception are the main ways humans communicate daily. Prior brain-to-text decoding studies have largely focused on a single modality and alphabetic languages…
Brain4FMs: A Benchmark of Foundation Models for Electrical Brain Signal
Fanqi Shen, Enhong Yang, Jiahe Li +5
Brain foundation models (BFMs) are advancing neurotechnology by learning transferable representations from neural signals, with broad potential in clinical diagnosis and neuroscien…
Assembling the Mind's Mosaic: Towards EEG Semantic Intent Decoding
Jiahe Li, Junru Chen, Fanqi Shen +6
Enabling natural communication through brain-computer interfaces (BCIs) remains one of the most profound challenges in neuroscience and neurotechnology. While existing frameworks o…
NeuroSketch: A Practical Design Recipe for Neural Decoding
Gaorui Zhang, Zhizhang Yuan, Jialan Yang +4
Neural decoding is fundamental to brain-computer interfaces, with growing applications in healthcare. Previous research has focused on leveraging signal processing and deep learnin…
Deep Learning-Powered Electrical Brain Signals Analysis: Advancing Neurological Diagnostics
Jiahe Li, Xin Chen, Fanqi Shen +7
Neurological disorders pose major global health challenges, driving advances in brain signal analysis. Scalp electroencephalography (EEG) and intracranial EEG (iEEG) are widely use…
Brant-X: A Unified Physiological Signal Alignment Framework
Daoze Zhang, Zhizhang Yuan, Junru Chen +2
Physiological signals serve as indispensable clues for understanding various physiological states of human bodies. Most existing works have focused on a single type of physiologica…
BrainWave: A Brain Signal Foundation Model for Clinical Applications
Zhizhang Yuan, Fanqi Shen, Meng Li +4
Neural electrical activity is fundamental to brain function, underlying a range of cognitive and behavioral processes, including movement, perception, decision-making, and consciou…
MBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals
Donghong Cai, Junru Chen, Yang Yang +2
Brain signals are important quantitative data for understanding physiological activities and diseases of human brain. Most existing studies pay attention to supervised learning met…
BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning
Junru Chen, Yang Yang, Tao Yu +3
Epilepsy is one of the most serious neurological diseases, affecting 1-2% of the world's population. The diagnosis of epilepsy depends heavily on the recognition of epileptic waves…