activity
20242026
collaborators

6 papers

stat.ML2026

Routing on the Stiefel Manifold: When Does Adaptive Subspace Selection Help for Cross-Domain EEG Decoding?

Isabella Costa Maia, Pedro L. C. Rodrigues, Salem Said +1

Cross-domain EEG decoding remains challenging despite advances in Riemannian deep learning: covariance matrices from different subjects occupy systematically distinct regions of th…

eess.SP2025

Improved Riemannian potato field: an Automatic Artifact Rejection Method for EEG

Davoud Hajhassani, Quentin Barthélemy, Jérémie Mattout +1

Electroencephalography (EEG) signal cleaning has long been a critical challenge in the research community. The presence of artifacts can significantly degrade EEG data quality, com…

cs.HC2025

The Riemannian Means Field Classifier for EEG-Based BCI Data

Anton Andreev, Grégoire Cattan, Marco Congedo

A substantial amount of research has demonstrated the robustness and accuracy of the Riemannian minimum distance to mean (MDM) classifier for all kinds of EEG-based brain--computer…

q-bio.NC2025

Tinnitus, lucid dreaming and awakening. An online survey and theoretical implications

Robin Guillard, Nicolas Dauman, Aurélien Cadix +4

(1) Background: Tinnitus is the perception of phantom sound in the absence of a corresponding external source. Previous studies reported that the presence of tinnitus is notably ab…

q-bio.NC2025

Why does tinnitus vary with naps? A polysomnographic prospective study exploring the somatosensory hypothesis

Robin Guillard, Vincent Philippe, Adam Hessas +6

Background: Tinnitus, defined as the conscious awareness of a noise without any identifiable corresponding external acoustic source, can be modulated by various factors. Among thes…

q-bio.NC2024

Nap-induced modulations of tinnitus -a cross-sectional database analysis

Robin Guillard, Martin Schecklmann, Jorge Simoes +8

The influence of naps on tinnitus was systematically assessed by exploring the frequency, clinical and demographic characteristics of this phenomenon. 9,724 data from two different…