9 citations · 12 across the 22 of their papers we have counts for
28 papers
The Semantic Bottleneck: Leveraging Semantic Representations for Non-Invasive Speech Decoding
Gilad D. Landau, Dulhan Jayalath, Oiwi Parker Jones
Non-invasive speech decoding remains constrained by the low signal-to-noise ratio of neural recordings, which makes fine-grained reconstruction of phonemes or individual words diff…
A Roadmap for MEG Foundation Models
Philipp Thölke, Hamza Abdelhedi, Yorguin Mantilla-Ramos +7
Foundation models are beginning to reshape brain-signal analysis by moving the field beyond task-specific decoding pipelines toward reusable models pretrained on broad neural datas…
The 2026 PNPL Competition: Word Classification and Efficient Cross-Subject Generalisation in LibriBrain100
Francesco Mantegna, Gereon Elvers, Dulhan Jayalath +18
The ambition of the 2025 PNPL competition (Landau et al., 2025) was to launch a multi-year curriculum for non-invasive speech decoding. Designed to progress from foundational tasks…
A Common Measure of Communication for Speech Brain-Computer Interfaces
Dulhan Jayalath, Benjamin Ballyk, Oiwi Parker Jones
Speech brain-computer interfaces (speech BCIs) translate neural activity into language, offering a path towards restoring speech for people with paralysis and, more broadly, enabli…
LibriBrain100: One Hundred Hours of Broad and Deep MEG Data for Neural Speech Decoding at Scale
Francesco Mantegna, Dulhan Jayalath, Gereon Elvers +12
We introduce LibriBrain100, a large-scale MEG dataset for speech decoding designed from the ground up for reproducible, standardised evaluation. LibriBrain100 more than doubles the…
Physiological Noise Augmentation Improves Non-Invasive Brain-to-Speech
Benjamin Ballyk, Teyun Kwon, Miran Özdogan +1
Non-invasive brain-to-speech decoding aims to restore communication to patients suffering from neurodegenerative disease, without the risks of neurosurgery. Existing MEG- and EEG-b…