False-Positive Calls of Reimplemented Published Analyses for Covert Command-Following on Electroencephalograms Recorded Without Study Commands
- 1BRIDGE GenAI Lab, Beth Israel Deaconess Medical Center, Boston, MA, USA
Abstract
Objective: To measure how often published electroencephalographic analyses for covert command-following call patients positive without commands, and their detection of genuine responses. Methods: This cross-sectional study applied 11 reimplemented published analyses to electroencephalograms without commands: 974 clinical electroencephalography patients and, with rules fixed, 730 new patients; 38 with prolonged disorders of consciousness; and 544 comatose patients after cardiac arrest. Outcomes: false calls (share called positive) against a 5% benchmark, and genuine-response detection. Results: Three of 10 command-following analyses called significantly more than 5% of clinical electroencephalography patients positive, replicated in new patients: Goldfine 2011, a spectral test, 23.3% (95% CI, 20.2%-26.6%), above its stated 5%; du Bois 2026, a criterion for entry to brain-computer interface training, 22.2% (95% CI, 19.2%-25.5%); and Guger 2018, a P300 accuracy threshold, 13.8% (95% CI, 11.5%-16.3%), near its approximate 12% chance rate (24.5% over 2 runs). The other 7 called 0.0% to 6.9%. After cardiac arrest: 11.5% to 27.3%. All 3 detected genuine responses. Identified contributors: a variance ignoring within-command dependence (Goldfine 2011), selection over configurations and times (du Bois 2026) and a permissive threshold (Guger 2018). Goldfine 2011's command-level correction, fixed before testing, called 0.8% of new patients and 2.4% after arrest, detecting 93.4% of stroke imagery-versus-rest sessions but few between imagery types. Interpretation: Reimplemented published analyses called up to 27% of patients positive without commands, more with repeated runs. A positive result needs its complete call rule's false-call rate and detection at that rate; imagery-versus-rest detection may reflect task engagement, not imagery. Funding: A.G. and E.K. were supported by the Clinical and Translational Science Awards (CTSA) Grant UL1TR002541 from the National Center for Advancing Translational Sciences, through the Harvard Catalyst - The Harvard Clinical and Translational Science Center Pilot Award Program. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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BibTeX
@misc{gorenshtein2026falsepositive,
title = {{False-Positive Calls of Reimplemented Published Analyses for Covert Command-Following on Electroencephalograms Recorded Without Study Commands}},
author = {A. Gorenshtein and Y. Adiniaev and Y. Barash and E. Klang and O. Daniel},
howpublished = {medRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.03.26367200},
url = {https://www.medrxiv.org/content/10.64898/2026.11.03.26367200v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - False-Positive Calls of Reimplemented Published Analyses for Covert Command-Following on Electroencephalograms Recorded Without Study Commands
AU - A. Gorenshtein
AU - Y. Adiniaev
AU - Y. Barash
AU - E. Klang
AU - O. Daniel
PY - 2026
DA - 2026/11/03
PB - medRxiv
DO - 10.64898/2026.11.03.26367200
UR - https://www.medrxiv.org/content/10.64898/2026.11.03.26367200v1
AB - Objective: To measure how often published electroencephalographic analyses for covert command-following call patients positive without commands, and their detection of genuine responses. Methods: This cross-sectional study applied 11 reimplemented published analyses to electroencephalograms without commands: 974 clinical electroencephalography patients and, with rules fixed, 730 new patients; 38 with prolonged disorders of consciousness; and 544 comatose patients after cardiac arrest. Outcomes: false calls (share called positive) against a 5% benchmark, and genuine-response detection. Results: Three of 10 command-following analyses called significantly more than 5% of clinical electroencephalography patients positive, replicated in new patients: Goldfine 2011, a spectral test, 23.3% (95% CI, 20.2%-26.6%), above its stated 5%; du Bois 2026, a criterion for entry to brain-computer interface training, 22.2% (95% CI, 19.2%-25.5%); and Guger 2018, a P300 accuracy threshold, 13.8% (95% CI, 11.5%-16.3%), near its approximate 12% chance rate (24.5% over 2 runs). The other 7 called 0.0% to 6.9%. After cardiac arrest: 11.5% to 27.3%. All 3 detected genuine responses. Identified contributors: a variance ignoring within-command dependence (Goldfine 2011), selection over configurations and times (du Bois 2026) and a permissive threshold (Guger 2018). Goldfine 2011's command-level correction, fixed before testing, called 0.8% of new patients and 2.4% after arrest, detecting 93.4% of stroke imagery-versus-rest sessions but few between imagery types. Interpretation: Reimplemented published analyses called up to 27% of patients positive without commands, more with repeated runs. A positive result needs its complete call rule's false-call rate and detection at that rate; imagery-versus-rest detection may reflect task engagement, not imagery. Funding: A.G. and E.K. were supported by the Clinical and Translational Science Awards (CTSA) Grant UL1TR002541 from the National Center for Advancing Translational Sciences, through the Harvard Catalyst - The Harvard Clinical and Translational Science Center Pilot Award Program. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
ER -