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Brain week

22/03/2017

How the brain learns to use a brain-computer interface

Imagination motrice : contrôler le curseur à l’écran par la pensée - © Inria / Photo C. Morel

At the ICM, the Brain & Spine Institute in Paris, Fabrizio De Vico Fallani (Aramis team) uses brain-computer interfaces to analyse brain activity in subjects. His approach is distinctive in that it applies complex network theory to model interconnections within the brain. Within the NetBCI project, he is seeking to understand how a subject learns to use a brain-computer interface… with the ultimate aim of improving the performance of such interfaces.Brain week

Based at the ICM (theInstitut du cerveau et de la moelle épinière) at La Pitié Salpétrière Hospital in Paris, the Aramis team is developing mathematical tools to model the healthy and impaired brain. In particular, it is interested in understanding the ways in which the different regions of the brain interact like complex networks. For the last few months, Fabrizio De Vico Fallani, a researcher in the Aramis team, has been coordinating a new project called NetBCI (Networks for Brain-Computer Interface ), funded by the French National Research Agency (ANR) and the National Institutes of Health (NIH) in the US.

This research programme, which will run until 2020, aims to improve our understanding of the mechanisms at work in the brain of someone using a brain-computer interface, a system enabling the person to perform tasks through thought alone. "You can't exactly use these tools to read what is going on in the brain, " Fabrizio De Vico Fallani explained. On the other hand, the computer can decrypt the person's cortical signature as they think about performing a movement. "When a person imagines taking hold of an object, they produce electrical activity in the brain very similar to that observed when actually performing the gesture required. For paraplegic patients, for example, this holds out incredible hope. The brain-computer interface can be used to transmit information to the muscles. " Many research projects are looking into these systems and seeking to improve their performance. Fabrizio De Vico Fallani and the members of the NetBCI project team have an innovative focus to their research: they will study how the brain learns to use this interface.

Exploring the unknown learning mechanisms 

The experiments are held in the basement of the ICM. The subject is placed in front of a screen and wears a cap to which a series of electrodes are connected. He must then, purely by thinking about it, make a ball on the screen move so that it moves up against a vertical bar. On another interface, the subject looks at a table of letters and has to concentrate on one letter at a time to write a whole word. When the letter lights up on the screen, the computer detects a peak in electrical activity in the brain. It can then, one letter at a time, write the word that the subject is thinking of.  "When we first start using these computers, we can't perform the task. It takes several goes to get it right. But we still know very little about the brain mechanisms that are created during this learning process," the researcher told us. The subject comes back four times in all, to repeat the same exercise. And each time, he or she gets a little better. In the next room, Fabrizio De Vico Fallani records EEG activity in the brain, which is translated into figures, and then analyses changes that have occurred in the brain between each session.

Imagination motrice : contrôler le curseur à l’écran par la pensée - © Inria / Photo C. Morel

Brain networks

Rather than study what is happening at a specific point in the brain, the researchers look at the interactions between the various regions of the brain. They have found that, as the subject gets better at the task, the number of regions involved increases, suggesting that mechanisms of interconnection are at play. "Our work entails modelling the connections in the brain and how they change during the learning process. To do this, we use mathematical tools derived from complex networks theory," explained Fabrizio De Vico Fallani. "We think this information may be used as learning biomarkers."  The researchers could then develop mathematical models that can be used to predict the learning trajectory when a person uses a brain-computer interface, and, eventually, make them more effective.

 

#50yearsofInria

What do you imagine your field of research will be like in 2067?

It is highly likely that brain-computer interfaces will be an integral part of our daily lives in fifty years' time. If that is the case, we must have answers to the ethical questions that such interfaces raise: particularly, what influence will these devices have on our ability to interact with the outside world?

What major advances do you hope to see?

In terms of methodology, complex network theory is now in its teenage years, with all the little problems that entails. It needs to reach maturity before we will see the impact on our understanding of the intrinsic mechanisms of complex networks such as the brain. In practical terms, current technology can only give us access to certain parts of the nervous system. The greatest advance will therefore be technological: will it, one day, be possible to access all the information contained in our brains?

Keywords: EPI Aramis Semaine du cerveau Inria de Paris Cerveau-machine Interface

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