Brain-Computer Interface (BCI)

Brain-Computer Interfaces (BCIs), also known as Brain-Machine Interfaces (BMIs), are direct communication pathways between the brain’s electrical activity and an external device. They enable control of computers, prosthetics, or other machines without using standard peripheral nerves and muscles.

Core Concepts & Modalities

  • Invasive BCIs: Require surgical implantation for high-bandwidth signal capture. Examples include Neuralink and Utah Array electrodes.
  • Non-Invasive BCIs: Use external sensors (EEG, fNIRS) offering lower resolution but higher safety.
  • Signal Processing: Involves decoding neural spikes or field potentials into actionable commands via machine learning algorithms.
  • Applications: Medical rehabilitation (motor restoration, sensory feedback), communication for locked-in patients, and potential enhancement of cognitive functions.

Key Entities & Developments

  • Neuralink: Pioneering high-density electrode arrays for human implantation.
  • fda: Regulatory body overseeing clinical trials for investigational devices.
  • machine-learning: Critical for decoding complex neural patterns into user intent.

Recent Milestones & Updates

References