Variability of task in Brain computer interface for a better experience

Research internship position (6 months)

Potioc team, Inria Bordeaux Sud-Ouest (TALENCE)

Context: Brain-computer interfaces for motor rehabilitation

Brain Computer Interfaces (BCI) systems [1] allow their users to interact with a computer solely through their brain activity, which is  usually measured by electroencephalography (EEG)  BCI-guided motor-imagery training is promising for post-stroke rehabilitation  following an upper limb motor impairment [2].  In this type of protocol patients imagine movement of their arm, even if they are not  able to move it, then the machine extracts their movement intention and provides feedback about their ability to solicit specific  brain networks. Though promising, it takes training for the human-system pair to perform well: the user needs to send clear and  distinct commands and the system needs to properly analyze and translate them. However, standard user training approaches are  sub-optimal. Notably, they are very long, very repetitive, and usually reported as boring for the user. At present, it is mainly up to the  user to adapt during training: to anticipate the action of the system (usually external pace), to accept the proposed perceptual  modalities (content of the interface, feedback, cues), and to respond according to the expected formats (commands to be sent are  usually guided, as in a dictation, with little to no variabilities). These interactions need further improvements, notably minimizing the  time for skill acquisition, maximizing the efficiency of the system (e g  feedback reliability), hedonic outcomes (e.g.  user experience)  and medical outcomes (e.g.  motor rehabilitation).

In the Potioc team, we seek to understand, model and optimize the learning process to control a BCI (team inria fr/potioc/ brainconquest/). This will help to move towards adaptive and personalized Brain-Computer Interfaces for multiple applications and  notably post-stroke motor rehabilitation exercises 

Scope of the internship : introducing variability into the instructed imagined tasksk

The goal of the internship is to study the influence of variability on motor imagery-BCI training outcomes with healthy participants, typically by introducing a range of various exercises that would involve similar interaction (imaging right vs left movement) but in different contexts (reaching an object, shaking hands, ect.).   The different tasks will need to be refined during the internship 

Tasks / internship schedule

• Study the literature on this topic (motor imagery, BCI for rehabilitation, motivation, UX for BCI, etc.)
• With the help of the team, design a protocol that will experimentally compare different conditions and observe the effects of task  variability in Motor imagery-BCI training performances, learning, motivation, perceived load or judgment of control (for example)  Use  the literature and possibly other methods (e g  surveys, interviews, pre-tests) to design the protocol 
• Justify your choices regarding the protocol, the instructions given to the subjects or the questionnaires we will use. Then, the  protocol will undergo validation with the ethical committee
• Implement the protocol in Unity by re-using an already existing protocol experiment and changing the animations.
• With the help of our EEG technician: recruit participants and run the experiment (on healthy subjects).
• If enough time is available, you might possibly start data analysis and maybe write a paper about the findings

Desired profile / required skills

• Master level (e.g. last year engineering school or 2nd year  Master student)
• Already implemented a project in Unity/C#
• Knowledge to design and carry out scientific experiments
• Extra skills (it is a plus but not mandatory!):  knowledge in  cognitive science, human-centered approaches,  neuroscience, statistical analysis or EEG
• Motivation to work in an international, english-speaking  environment

General informations

• Inria intern position for 6 months (~600€/month)
• Location: Talence (33)
• On-site presence (teleworking possibilities depending on the  covid situation)
• Start of the internship: beginning of 2022 (to be defined  according to the student s academic schedule)
• Supervision: Fabien Lotte (Research Director), Aline Roc (PhD  Student) and David Trocellier (PhD Student)
• Join a friendly research team! 🙂

Application

Send CV and cover letter to 

Aline Roc aline.roc@inria.fr

David Trocellier david.trocellier@inria.fr 

& Fabien Lotte fabien.lotte@inria.fr

[1] Graimann, B., Allison, B., & Pfurtscheller, G. (2009). Brain computer interfaces: A  gentle introduction  In Brain-computer interfaces (pp  t-2e). Springer, Berlin,  Heidelberg. https://link.springer.com/chapter/10.1007/978-3-642-02091-9_1

[2] Cervera, M. A., Soekadar, S. R., Ushiba, J., Millán, J. D. R., Liu, M., Birbaumer, N., &  Garipelli, G. (2018). Brain computer interfaces for post stroke motor rehabilitation: a  meta analysis  Annals of clinical and translational neurology, 5(5), 651-663. https://onlinelibrary.wiley.com/doi/full/10.1002/acn3.544

Tagged as: BCI, Neuroscience