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Leakage-audited benchmarking reveals limited evidence for cross-subject auditory-evoked EEG vowel perception decoding
1Northeastern University, Shenyang, Shenyang, 110819, China.
Objective:
We evaluated cross-subject five-vowel perception decoding from auditory-evoked EEG with explicit trial definitions, participant-grouped validation, complete prediction coverage, and participant-level inference. Approach. We parsed all Study 2 event tables from OpenNeuro ds006104 version 1.0.1 and analysed the consonant-vowel (CV) pair task. Marker-stimulus pairing converted 7,680 event rows into 3,840 independent CV trials. Excluding active-condition trials left 1,280 eligible control trials. A 400 μV maximum across-channel peak-to-peak criterion rejected 186 epochs,retaining 1,094 epochs from 16 participants and 61 EEG channels. Thirteen unique implementations underwent leave-one-subject-out (LOSO) testing. Participant metrics came from 36,102 trial predictions across 33 complete replicas. Descriptive analyses assessed deep-model stability across five seeds, class-resolved errors, and retention sensitivity. An exploratory MDM analysis comprised 9,616 genuine model refits across training cohorts of 3-15 participants. Main results. Two independent cohort-construction implementations preserved the same ordered 1,094 trials and labels (maximum tensor difference, 4 × 10-12 V). Thus, corrected accounting changed the reported exclusion decomposition but not the analysed cohort or model inputs. Random Forest achieved the highest mean balanced accuracy: 21.474% (95% participant-bootstrap interval, 19.526-23.482%; five-class chance, 20%). The one-sided Wilcoxon, Bonferroni-adjusted, and sign-flip p values were 0.090897, 1.000000, and 0.092791, respectively. All 13 implementations remained non-significant after multiplicity correction.Deep-architecture means were near chance, with substantial within-participant seed ranges and low trial-label agreement for several architectures. Across 3-15 training participants, refitted MDM means ranged from 20.553% to 20.922%, without a monotonic increase. Significance. This dataset and protocol provide limited evidence for cross-subject five-vowel decoding. Explicit trial units, participant-grouped validation, complete seed reporting, prediction-level traceability, and multiplicity-adjusted inference sharpen the interpretation of small-cohort EEG benchmarks.