Brain-Computer Interface: Neuronal Signals and Arrow of Progress


Technical Landscape

  1. an electrical signal is transmitted along an axon.
  2. The electrical signal at the end of the axon is converted into a chemical signal and the axon releases neurotransmitters, a bunch of chemical messengers
  3. The chemical messengers travel from the synapse to the dendrite of the next neuron where it is converted back again to electrical signals.
  1. Action potentials (a temporary spike in the neuron’s membrane potential caused by ions flowing in and out of the neuron) along the axons connecting neurons
  2. Currents through the synapses connecting axons with neurons/dendrites
  3. Currents along dendrites from synapses to the soma of neurons
  • Electrocorticography(ECOG) where an electrode plate is in direct contact with the surface of the brain. Sometimes, semi-considered semi-invasive, it works similar to that of EEG but the electrodes are embedded in a thin pad that is placed right above the cortex. ECOG offers higher spatial resolution, better signal-to-noise ratio and wider frequency range than EEG. Almost all companies in this space such as Neuralink leverage ECOG for building invasive BCI.
  • Intracortical Microelectrodes are implantable devices that can be used in either sensory prosthetics such as cochlear implants as stimulating interfaces or as recording electrodes. While stimulating interfaces are effective in producing sufficiently high signal strength, current implantable microelectrodes are limited in capacity to record single- or multi-unit activity. ( Single unit BCIs detect the signal from a single area of brain cells, while multiunit BCIs detect from multiple areas.)
  1. Signal Acquisition: The first component is sensing and measuring the signals of the brain based on neuronal activity. Once this signal is acquired by electrodes on invasive/non-invasive devices, the signal is amplified and passed through an analogue-to-digital converter.
  2. Signal Pre-Processing: The raw signal is usually affected by noise(from the equipment) and other artefacts (eg. potential difference due to eyeball movement), particularly in EEG, and must be processed. Elements such as high-pass filters are used to clean the data.
  3. Signal Processing:
  • Feature Extraction is the first step where different characteristics such as user intent are decoded from the signal.
  • Classification: Once the necessary features are extracted, data is passed through classifiers running in parallel and fed into a convolutional neural network(CNN) to detect features in real-time.
  • Translation: The extracted information is then transferred to an algorithm that translates the information to instructions that can be executed by an external device.
  • Execution: A Feedback/External Device such as a computer or robotic arm receives the command to execute the task intended by the user.

Market Landscape




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I write about deeptech startups and trends innovating the future. Do visit and subscribe on my website where I track sci-fi startups.

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