Linked from

The 12 pages that link to Brain–computer interface, each with the reason it gives.

• ElectroencephalographyRelated: Some interfaces decode EEG features to control cursors, communication tools, or assistive devices.

• NeuroscienceRelated: Its performance tests how reliably neural signals can reveal intentions and actions.

• Motor controlRelated: It uses movement-related neural signals to control devices when ordinary motor output is limited.

• Functional magnetic resonance imagingRelated: Real-time fMRI has been used to decode signals and provide neurofeedback.

• TranshumanismRelated: It offers a direct technological route to augmenting communication and control.

• Neural codingRelated: Its performance depends on extracting useful signals from neural activity.

• MagnetoencephalographyRelated: MEG’s fast measurements can support research on decoding brain signals for device control.

• Locked-in syndromeRelated: It may provide communication when eye movements are too limited for gaze-based systems.

• Motor cortexRelated: Signals from motor cortical activity can control prostheses or computer cursors.

• Human brainRelated: Reliable interpretation of complex brain signals is still an open engineering problem.

• Emerging technologiesBroader topic: It connects emerging technology with medical treatment, accessibility, and questions about mental privacy.

• NeurophysicsRelated: It uses physical measurements and neural-signal models for practical control.