Key result
A reanalysis of NIRS data from completely locked-in patients found no significant difference in hemodynamic responses to 'yes' and 'no' questions, with an average classification accuracy of 49.4% (p>0.05).
Why the study?
Does NIRS-based BCI allow communication in patients in a complete locked-in state?
Does NIRS-based BCI allow communication in patients in a complete locked-in state?
Reanalysis of previously published data demonstrates no scientifically sound evidence that NIRS-based BCI enables communication in patients in a complete locked-in state.
May enable communication in CLIS; leaves open whether findings generalize beyond single cases.
When Birbaumer and colleagues [1] showed in 1999 for the first time that a person in a locked-in state can use a brain-computer interface (BCI) to communicate, it also created the hope of BCIs restoring communication in the complete locked-in state (CLIS), in which a patient has no remaining muscle control.Since this pioneering work, multiple electroencephalography (EEG)-based BCI systems have been successfully tested with locked-in patients [2].However, these systems did not work for completely locked-in patients, leading to the conclusion that voluntary brain regulation is not possible in the CLIS [2,3].This changed in 2014 when Gallegos-Ayala and colleagues [4] presented a case study suggesting that near-infrared spectroscopy (NIRS) could be used for communication in the CLIS.It was followed up by Chaudhary and colleagues in 2017 [5], who recorded NIRS in 4 patients in the CLIS.In that work, results from offline and online classification are presented with accuracies significantly above chance level, which led the authors to the conclusion that NIRSbased BCI communication is working in CLIS.For this commentary, I performed a reanalysis of the data from Chaudhary and colleagues [5].As the results are substantially different from the results reported in the original paper, I question the claim of NIRS-based BCI communication in the CLIS.
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Martin Spüler (2019) conducted an editorial in Complete locked-in state (CLIS) (n=4). NIRS-based brain-computer interface (BCI) vs. Chance level was evaluated on Offline classification accuracy of NIRS data for 'yes' and 'no' questions (p=>0.05). A reanalysis of NIRS data from completely locked-in patients found no significant difference in hemodynamic responses to 'yes' and 'no' questions, with an average classification accuracy of 49.4% (p>0.05).
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