TMS-evoked potential propagation reflects effective brain connectivity.

Cognition is achieved through communication between brain regions. Consequently, there is considerable interest in measuring effective connectivity. A promising effective connectivity metric is transcranial magnetic stimulation (TMS) evoked potentials (TEPs), an inflection in amplitude of the electroencephalogram recorded from one brain region as a result of TMS applied to another region.

Using data from cue presentations results in grossly overestimating semantic BCI performance.

Neuroimaging studies have reported the possibility of semantic neural decoding to identify specific semantic concepts from neural activity. This offers promise for brain-computer interfaces (BCIs) for communication. However, translating these findings into a BCI paradigm has proven challenging.

A Growing Bubble Speller Paradigm for Brain-Computer Interface Based on Event-related Potentials.

Objective: Event-related potentials (ERPs) reflect electropotential changes within specific cortical regions in response to specific events or stimuli during cognitive processes. The P300 speller is an important application of ERP-based brain-computer interfaces (BCIs), offering potential assistance to individuals with severe motor disabilities by decoding their electroencephalography (EEG) to communicate.

Methods: This study introduced a novel speller paradigm using a dynamically growing bubble (GB) visualization as the stimulus, departing from the conventional flash stimulus (TF).

Inter-participant transfer learning with attention based domain adversarial training for P300 detection.

A Brain-computer interface (BCI) system establishes a novel communication channel between the human brain and a computer. Most event related potential-based BCI applications make use of decoding models, which requires training. This training process is often time-consuming and inconvenient for new users.