Steady-state visual evoked potentials (SSVEPs) are widely used in cognitive neuroscience and brain-computer interfaces (BCIs), but the visual discomfort induced by plain luminance repetitive flickers limits their usability in mono- and especially …
Current electroencephalogram (EEG) decoding models are typically trained on small numbers of subjects performing a single task. Here, we introduce a large-scale, code-submission-based competition comprising two challenges. First, the Transfer …
Brain-computer interface (BCI) is a system that translates neural activity into commands, allowing direct communication between the brain and external devices. Despite its clinical application, BCI systems fail to robustly capture subjects’ intent …
Brain-Computer Interfaces (BCIs) based on motor imagery (MI) hold promise for restoring control in individuals with motor impairments. However, up to 30% of users remain unable to effectively use BCIs—a phenomenon termed “BCI inefficiency.” This …
Introduction: automatic movement recognition is often used to support various fields such as clinical, sports, and security. To date, there is a lack of a classification feature that is both interpretable and not movement-specific, characteristics …
This paper proposes a multilayer graph model for the community detection from multiple observations. This is a very frequent situation, when different estimators are applied to infer graph edges from signals at its nodes, or when different signal …
In signal processing, exploring complex systems through network representations has become an area of growing interest. This study introduces the modularity graph, a new graph-based feature, to highlight the relationship across the graph communities. …
Background Temporal lobe epilepsy (TLE) is characterized by alterations of brain dynamic at large scale associated with altered cognitive functioning. Interindividual variability of brain activity is a source of heterogeneity in this disorder. Here, …