{"id":"doi:10.1088/1741-2552/aead26","kind":"article","title":"From confidence to caution: conformal gating for cross-session motor imagery brain-computer interfaces","authors":["Xing S","Nagarajan A"],"author_count":2,"year":2026,"published":"2026-10-23","venue":"Journal of neural engineering","cited_by":0,"doi":"10.1088/1741-2552/aead26","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1088/1741-2552/aead26","archive_url":"https://space-kitty.com/papers/doi:10.1088/1741-2552/aead26","updated":null,"pmid":"42805221","pmcid":null,"openalex_id":null,"pdf_url":null,"abstract":"Objective. Erroneous motor imagery brain-computer interface (MI-BCI) commands can cause unintended device actions, yet standard classifiers provide no mechanism to withhold uncertain predictions. We evaluate whether conformal prediction (CP) can serve as a command gate under cross-session EEG shift, where exchangeability cannot be assumed, and how gating-policy choice should vary with application-specific risk tolerance. Approach. We compare threshold-based CP (THR), regularised adaptive prediction sets (RAPS/RAPS-Opt), and Chow's selective prediction. Experiments use DeepConvNet as the base classifier on OpenBMI (54 subjects, 2-class) and BCI Competition IV Dataset 2a (BCIC IV-2a: 9 subjects, 4-class). Five chronological split conditions evaluate calibration sources with increasing match to the target session. Performance is assessed using decision rate, wrong-decisive rate, empirical coverage,, and a risk-weighted utility. Main results. Ungated cross-session classifiers produced wrong-decisive rates of 37.5% on OpenBMI and 35.5% on BCIC IV-2a. Across THR and RAPS, these rates were reduced to 9%-16% on OpenBMI and 6%-8% on BCIC IV-2a (OpenBMI: all, BCIC IV-2a:). On OpenBMI, increasing calibration-test match made conformal gates more conservative: for THR, decision rate fell from 0.55 to 0.41 and wrong-decisive rate from 0.16 to 0.11 ()., requiring no labelled target-session data, achieved the highest THRamong cross-session strategies (0.53). Chow issued more commands but incurred higher wrong-decisive rates. Under, the preferred policy shifted from Chow atto THR for; a sensitivity analysis re-optimising Chow's threshold directly fordid not alter this qualitative ordering (THR above Chow-for all,-). Significance. This study reframes cross-session MI-BCI reliability as an application-dependent safety-decisiveness trade-off, providing a framework for selecting calibration sources and uncertainty-aware gating policies according to wrong-command tolerance under session shift.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"From confidence to caution: conformal gating for cross-session motor imagery brain-computer interfaces\" by Xing S, Nagarajan A, https://doi.org/10.1088/1741-2552/aead26, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"brain-computer-interfaces","name":"Brain-Computer Interfaces","domain_slug":"neuroscience"}],"cited_in_dossiers":[]}