Objective. We tested whether frozen representations from five EEG foundation models support decoding of long-range temporal correlations, measured as the detrended-fluctuation-analysis (DFA) exponent of the alpha-band amplitude envelope. Approach. REVE, LaBraM, BENDR, CBraMod, and BIOT were evaluated in CAUEEG and BrainLat. A common 240 s estimator used 8-13 Hz filtering, DFA over 2-23.8 s, artifact masking, and quality control. One fixed nested-cross-validation readout predicted DFA and a fixed-mode aperiodic exponent. Controls tested pre-pool order sensitivity and aperiodic residualization. Results. CAUEEG included 764 recordings and BrainLat 79. BIOT decoded DFA in CAUEEG (R-squared = 0.232; conditional subject-bootstrap 95 percent interval, 0.121-0.310), and CBraMod was positive but imprecise (R-squared = 0.121; 0.003-0.214). Neither replicated in BrainLat, where all five point estimates were negative. In contrast, CBraMod and BIOT decoded the aperiodic exponent in both cohorts (R-squared = 0.459-0.757). BIOT remained positive after removal of the measured linear aperiodic association in matched CAUEEG data (R-squared = 0.240). The post-hoc order control was batch- and configuration-sensitive. Because chronological EEG epochs are not exchangeable, it was descriptive, not an LRTC-specific test. No revised DFA transfer direction passed source-label permutation testing. Cohort membership was near-ceiling decodable from all five embeddings, but this is not a pure site effect. Significance. CBraMod and BIOT show a replicated, model-specific spectral-temporal dissociation: aperiodic decoding is present in both cohorts, whereas alpha-envelope DFA decoding is cohort-dependent. These findings bound the evaluated readouts; they do not establish representational absence or an architectural cause. Transfer and clinical associations remain exploratory.
Brain-computer interfaces (BCIs) have long sought calibration-free operation, but classifiers are typically benchmarked by discrimination alone, blind to whether predicted probabilities are well calibrated - a meaningful gap given nonstationary electroencephalogram (EEG) signals and the risk of overconfident point-esti...
Reliability showed no detectable association with discrimination, pretraining paradigm, or domain, and had to be measured directly, so it is recommended to become a standard evaluation axis for EEG-FM representations intended for longitudinal or biomarker use, and release a reproducible pipeline.
B. Gebregergis, Haben Yhdego, Tewolde Teklu· bioRxiv· 0 citations
Electroencephalography (EEG) offers millisecond-scale temporal resolution for studying brain activity, yet its practical value is persistently compromised by ocular artifacts—unwanted electrical potentials from eye blinks and saccadic movements that can exceed genuine cortical signals by an order of magnitude. Because...
A. Mishra, M. Choudhry· 2026 4th International Confe...· 0 citations
This study investigated whether five frontal dry-electrode electroencephalography (EEG) channels can support recognition of mental fatigue-related states after individual calibration. Thirteen healthy adult men completed pre- and post-rest recordings, N-back, Stroop, and a 15-min sustained attention to response task (S...
Quantitative EEG (qEEG) provides objective, millisecond-resolution measures of brain dynamics. Despite decades of methodological advances, clinically relevant derived indices—spectral power ratios, cognitive-emotional state markers, and physiological parameters—are typically reported as raw values without the normative...
J. Bosch-Bayard, J. Guerrero-Sauzameda, R. I. Bosch-Bayard et al.· Brain Topography· 0 citations
A large-scale, standardized within-session benchmark of decoding pipelines across three public datasets is presented, using the benchmark as an empirical performance landscape for building compact portfolios of pipelines of size K.
Paul Barbaste, Olivier Oullier, Xavier Vasques· arXiv.org· 0 citations
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