Feature Paper – Communicating with completely locked-in people using a fNIRS-based brain-computer interface

fNIRS big in the news:  Communicating with completely locked-in people using a fNIRS-based brain-computer interface

By Felix Scholkmann

A fNIRS paper published in January this year in PLOS Biology got a big new coverage (BBC, CNN, NBC New, The Guardian, Zeit, Nature, Der Spiegel). The paper reported of successfully implementing a brain-computer interface (BCI) that allowed amyotrophic lateral sclerosis (ALS) patients being in a locked-in state to communicate by answering “yes” and “no” questions with their thought. Four patients were measured for the study. The research team, led by Professor Niels Birbaumer (Wyss Center for Bio and Neuroengineering, Geneva, Switzerland; University of Tübingen, Germany; Ospedale San Camillo, IRCCS, Venice, Italy), could show that a BCI based on fNIRS had a better above-chance-level correct response rate than one based on electroencephalogray or invasive electrocorticography. For fNIRS, an above-chance-level correct response rate over 70% was obtained (patient 1: 78.6%, patient 2: 78.8%, patient 3: 75.8%, and patient 4: 70.0). A multi-channel continuous wave NIRSport (NIRX) NIRS system was used (8 channels, source-detector separation: 3 cm) covering the frontocentral regions. Data analysis was performed with the [O2Hb] signal since it gave higher cross-validation classification accuracy than the [HHb] signal. The hemodynamic responses to the “yes” and “no” questions obtained had various shapes, in general not resembling the “classical” hemodynamic response function normally observed with fNIRS due to a task or stimulus. The origin of these individual differences might be an interesting question for future research. In conclusion, the study by Chaudhary et al. delivered fascinating results indicating that a fNIRS-based BCI can enable to communicate with patients in the completely locked-in state. I am looking forward to hear more from this research group in the future about their important and captivating research topic.

Journal reference:

Ujwal Chaudhary, Bin Xia, Stefano Silvoni, Leonardo G. Cohen, Niels Birbaumer. Brain–Computer Interface–Based Communication in the Completely Locked-In State. PLOS Biology, 2017; 15 (1): e1002593 DOI: 10.1371/journal.pbio.1002593