9 papers
iFuzz-Meta: An Interpretable Fuzzy Learning Framework Bridging Top-Down and Bottom-Up Knowledge Integration
Xiaowei Jiang, Daniel Leong, Beining Cao +5
Interpretable representation learning remains a key challenge in modern neural computation, particularly when models are expected not only to perform but also to explain their reas…
Interpretable Fuzzy Modeling Reveals Population-Level Representation Differences in P300 Brain Computer Interfaces Across Neurodivergent and Neurotypical Cohorts
Xiaowei Jiang, Sudong Shang, Adrian Wilkinson +4
P300-based brain-computer interfaces (BCIs) are widely used for communication, but population heterogeneity may alter the neural patterns available for decoding. Prior work has mai…
SASLO: A Scene-Aware Spatial Layout Optimization System for AR-SSVEP
Beining Cao, Xiaowei Jiang, Charlie Li-Ting Tsai +3
Steady-state visual evoked potential (SSVEP) is widely used in brain-computer interfaces (BCIs) due to its reliability. With the integration of augmented reality (AR), AR-SSVEP ena…
Neural Spelling: A Spell-Based BCI System for Language Neural Decoding
Xiaowei Jiang, Charles Zhou, Yiqun Duan +3
Brain-computer interfaces (BCIs) present a promising avenue by translating neural activity directly into text, eliminating the need for physical actions. However, existing non-inva…
BrainStack: Neuro-MoE with Functionally Guided Expert Routing for EEG-Based Language Decoding
Ziyi Zhao, Jinzhao Zhou, Xiaowei Jiang +6
Decoding linguistic information from electroencephalography (EEG) remains challenging due to the brain's distributed and nonlinear organization. We present BrainStack, a functional…
Pretraining Large Brain Language Model for Active BCI: Silent Speech
Jinzhao Zhou, Zehong Cao, Yiqun Duan +9
This paper explores silent speech decoding in active brain-computer interface (BCI) systems, which offer more natural and flexible communication than traditional BCI applications.…