Brain-Computer Interface with Real-Time Brain Imaging

Functional magnetic resonance imaging is a specialized type of an MRI brain scan. fMRI is able to detect the specific brain activation/deactivation patterns that are directly correlated to the regulation of the brain’s blood flow. This type of brain imaging has been used to diagnose and interpret brain signals for many different conditions. In the past I've mentioned about brain computer interfaces which are a direct connection between a person’s brain and an external computer device. BCI’s have the capacity to directly translate a person's brain signals into specific electronic information. In the future brain computer interfaces may be used for people who are completely paralyzed. It could help them gain control of robotic arms or other appendages. Researchers have recently used real-time brain imaging (real-time functional MRI (rtfMRI)) for a brain-computer interface.

Here is the abstract for the paper.

Real-time functional MRI (rtfMRI) has been used as a basis for brain-computer interface (BCI) due to its ability to characterize region-specific brain activity in real-time. As an extension of BCI, we present an rtfMRI-based brain-machine interface (BMI) whereby 2-dimensional movement of a robotic arm was controlled by the regulation (and concurrent detection) of regional cortical activations in the primary motor areas. To do so, the subjects were engaged in the right- and/or left-hand motor imagery tasks. The blood oxygenation level dependent (BOLD) signal originating from the corresponding hand motor areas was then translated into horizontal or vertical robotic arm movement. The movement was broadcasted visually back to the subject as a feedback. We demonstrated that real-time control of the robotic arm only through the subjects’ thought processes was possible using the rtfMRI-based BMI trials.

So for this specific study the researchers took real time brain imaging readings from an area of the motor cortex. They were then able to translate those brain signals into moving a robotic arm vertically or horizontally. This type of brain imaging would allow a paralyzed person to control a robotic arm solely through using their mind.
At this point it is difficult to say how useful this will be. Doing real-time brain imaging especially fMRI may not be practical and may be much too expensive. It doesn’t seem like this would actually help many people who currently are paralyzed. This type of brain imaging is probably much better at reading brain signals than an EEG type device, however. Perhaps it would be on par with the brain-computer interfaces that are implanted directly within the brain. Even if this isn't useful, real time brain imaging may find more use as a rehabilitation tool. It would allow real-time feedback for a person to alter their own brain's functioning through neuroplastic mechanisms.

Brain-computer interfaces based on fMRI enable real-time feedback of circumscribed brain regions to learn volitional regulation of those regions. This is an emerging field of intense research, with potential for multiple applications in neuroscientific research in brain plasticity and reorganization, movement restoration due to stroke, clinical rehabilitation of emotional disorders, quality assurance of fMRI experiments, and teaching functional imaging. This article presents a general architecture of an fMRI-BCI, with descriptions of each of its subsystems, and factors influencing their performance.

This may definitely happen more often as real-time brain imaging gets cheaper and cheaper. Perhaps it will get to the point where people will have their own high resolution brain imaging devices in their homes.