Brain imaging technology


 There are two main types:
 Invasive technologies:
 In which sensors are implanted directly on or in the brain and non-invasive technologies, which measure brain activity using external sensors. Although invasive technologies provide high temporal and spatial resolution, they usually cover only very small regions of the brain.
 
Additionally, these techniques require surgical procedures that often lead to medical complications as the body adapts, or does not adapt, to the implants. Furthermore, once implanted, these technologies cannot be moved to measure different regions of the brain.
  Noninvasive technologies:
In these technology external sensors are used to measure electrical signals. Electroencephalography (EEG) presents the opportunity for inexpensive, portable, and safe devices, properties.

 Brain signals:
Through the recording and processing of direct brain electrical activity via signal processing and machine learning algorithms, BCIs enables communication and control to assistive devices. Although the aim of a BCI is to identify and translate brain electrical signals into commands, it is not a thought-reading device or systems able to literally translate arbitrary cognitive activities. BCIs are design for translation of well characterized a priori defined brain activity patterns through the use of machine learning techniques and patterns recognition methods into commands.
Considered as a control system, a BCI has an input (e.g. EEG), an output (e.g. control signal), and components that translate input into output, a protocol that determines the timing operation and in some cases some feedback is provided to the user (Figure .).
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           Figure

Exemplification on EEG (a), ECoG (b) and Single-neuron recording (c) electrode placement over the head

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