Overall Performance

RQ1. In a broad and shared task space, where are EEG FMs competitive with or stronger than task-specific supervised models?

Score Matrices Performance Rankings Overall Gain (Δ)

Score Matrices

EEG foundation models and supervised baseline models are compared across benchmark datasets and tasks, with color intensity showing relative performance within each task.

Unsupported

Balanced Accuracy

Dataset · task · split	Baseline Models																									Foundation Models
Dataset · task · split	ADFCNN	ATCNet	BiDANN	CTNet	DBConformer	DeepConvNet	DeepSleepNet	EEGConformer	EEGInceptionERP	EEGNet	EEGNeX	EEGWaveNet	FBCNet	HSLT	IFNet	MSCFormer	MSVTNet	ShallowConvNet	SleepEEGNet	SleepTransformer	SlimSeiz	TMSA-Net	TSception	U-Sleep	YASA	BENDR	BIOT · Prest 16ch	BIOT · Shhs Prest 18ch	BIOT · Six Datasets 18ch	CBraMod	CodeBrain	CSBrain	EEGMamba	EEGPT	LaBraM	LEAD	LUNA · Base	LUNA · Large	mdJPT	MIRepNet	NeuroGPT	NeuroRVQ	REVE · Base	REVE · Large
EEGMatMental Arithmetic vs RestWS	0.50	0.61	0.58	0.53	0.50	0.60	0.888	0.8510	0.52	0.51	0.62	0.53	0.54	0.50	0.55	0.50	0.50	0.906	0.933	0.56	0.50	0.57	0.72	0.887	0.48	0.85	-	-	-	0.84	0.914	0.905	0.64	0.74	0.70	0.961	0.78	0.79	0.50	0.50	0.869	0.50	0.952	0.57
EEGMatMental Arithmetic vs RestCS	0.50	0.51	0.55	0.51	0.50	0.50	0.61	0.66	0.47	0.50	0.53	0.49	0.50	0.50	0.50	0.50	0.50	0.707	0.6810	0.51	0.68	0.51	0.65	0.698	0.50	0.725	-	-	-	0.821	0.763	0.726	0.65	0.734	0.63	0.792	0.699	0.65	0.50	0.50	0.67	0.50	0.67	0.56
TUEVEpileptiform EventsWS	0.49	0.62	0.7410	0.63	0.62	0.29	0.61	0.65	0.65	0.52	0.69	0.52	0.63	0.25	0.64	0.60	0.52	0.73	0.72	0.59	0.71	0.66	0.67	0.808	0.45	0.69	-	-	-	0.881	0.853	0.835	0.72	0.809	0.70	0.844	0.852	0.807	0.25	0.25	0.66	0.25	0.816	0.64
TUEVEpileptiform EventsCS	0.39	0.705	0.26	0.697	0.649	0.25	0.27	0.57	0.62	0.46	0.678	0.34	0.704	0.25	0.713	0.6410	0.35	0.706	0.52	0.42	0.50	0.721	0.62	0.38	0.45	0.28	-	-	-	0.43	0.26	0.25	0.44	0.39	0.53	0.44	0.37	0.48	0.25	0.25	0.54	0.25	0.38	0.722
TUEVEpileptiform Event DetectionWS	0.64	0.90	0.94	0.90	0.90	0.50	0.88	0.91	0.91	0.82	0.92	0.88	0.91	-	0.91	0.89	0.85	0.977	0.95	0.87	0.95	0.91	0.92	0.975	0.79	0.92	-	-	-	0.976	0.973	0.981	0.95	0.972	0.95	0.974	0.969	0.9510	0.50	0.50	0.93	0.50	0.968	0.86
TUEVEpileptiform Event DetectionCS	0.56	0.9210	0.929	0.90	0.927	0.50	0.69	0.90	0.91	0.69	0.934	0.87	0.86	-	0.928	0.89	0.88	0.89	0.90	0.86	0.926	0.89	0.943	0.941	0.84	0.82	-	-	-	0.88	0.88	0.84	0.90	0.935	0.90	0.942	0.91	0.92	0.50	0.50	0.88	0.50	0.79	0.86
SHU-MILeft/Right Hand MIWS	0.60	0.65	0.75	0.64	0.63	0.64	0.81	0.65	0.68	0.62	0.70	0.68	0.64	0.50	0.64	0.63	0.58	0.76	0.82	0.84	0.72	0.66	0.70	0.858	0.51	0.53	-	-	-	0.865	0.856	0.857	0.8410	0.50	0.50	0.881	0.864	0.863	0.50	0.50	0.60	0.50	0.882	0.849
SHU-MILeft/Right Hand MICS	0.58	0.65	0.694	0.63	0.678	0.64	0.65	0.64	0.65	0.63	0.677	0.66	0.679	0.52	0.64	0.65	0.59	0.63	0.65	0.65	0.64	0.65	0.703	0.6610	0.53	0.50	-	-	-	0.65	0.65	0.63	0.64	0.56	0.50	0.721	0.695	0.686	0.50	0.50	0.58	0.50	0.722	0.65
TUSLBackground Slowing DetectionWS	0.50	0.54	0.77	0.62	0.66	0.63	0.61	0.66	0.51	0.46	0.49	0.50	0.44	0.50	0.63	0.55	0.49	0.73	0.60	0.43	0.73	0.64	0.49	0.876	0.65	0.63	-	-	-	0.8010	0.884	0.857	0.838	0.79	0.78	0.875	0.902	0.893	0.50	0.50	0.819	0.50	0.921	0.60
TUSLBackground Slowing DetectionCS	0.50	0.52	0.63	0.50	0.50	0.63	0.57	0.55	0.51	0.49	0.51	0.50	0.50	0.50	0.53	0.52	0.49	0.50	0.50	0.53	0.57	0.56	0.50	0.688	0.56	0.42	-	-	-	0.773	0.754	0.669	0.6510	0.58	0.735	0.781	0.65	0.60	0.50	0.50	0.726	0.50	0.772	0.697
TUSLSlowing + SeizureWS	0.42	0.44	0.67	0.35	0.36	0.40	0.61	0.41	0.40	0.37	0.54	0.33	0.44	0.33	0.48	0.42	0.48	0.66	0.62	0.42	0.52	0.56	0.43	0.779	0.35	0.48	-	-	-	0.806	0.852	0.844	0.7110	0.69	0.778	0.843	0.825	0.797	0.33	0.33	0.51	0.33	0.891	0.43
TUSLSlowing + SeizureCS	0.448	0.37	0.23	0.36	0.33	0.35	0.23	0.32	0.32	0.34	0.31	0.33	0.36	0.33	0.36	0.34	0.25	0.34	0.40	0.33	0.4110	0.36	0.33	0.32	0.476	0.36	-	-	-	0.622	0.701	0.583	0.37	0.457	0.564	0.525	0.38	0.30	0.33	0.33	0.35	0.33	0.449	0.33
Kaggle-INRIAP300 Feedback CorrectnessWS	0.52	-	0.628	0.60	0.50	0.56	0.61	0.61	0.61	0.56	0.636	0.50	0.57	0.51	0.54	0.50	0.53	0.59	0.629	0.635	0.53	0.52	0.59	0.59	0.50	0.50	-	-	-	0.57	0.50	0.637	0.56	0.54	0.57	0.6210	0.60	0.61	0.57	0.52	0.672	0.654	0.701	0.673
Kaggle-INRIAP300 Feedback CorrectnessCS	0.48	-	0.637	0.57	0.50	0.6010	0.59	0.58	0.619	0.663	0.618	0.50	0.59	0.50	0.51	0.50	0.52	0.49	0.57	0.655	0.50	0.51	0.52	0.60	0.50	0.60	-	-	-	0.48	0.50	0.51	0.59	0.50	0.656	0.56	0.54	0.56	0.50	0.52	0.59	0.682	0.664	0.691
ERP-BCIP300 Target DetectionWS	0.51	-	0.59	0.60	0.50	0.50	0.61	0.50	0.648	0.41	0.6210	0.50	0.56	0.50	0.50	0.50	0.50	0.47	0.54	0.715	0.50	0.50	0.44	0.724	0.50	0.60	-	-	-	0.761	0.723	0.742	-	0.667	0.686	0.62	0.639	0.50	0.50	0.50	0.50	0.50	-	-
ERP-BCIP300 Target DetectionCS	0.50	-	0.59	0.61	0.50	0.50	0.62	0.50	0.6410	0.49	0.63	0.50	0.56	0.50	0.50	0.50	0.50	0.46	0.57	0.705	0.50	0.50	0.45	0.713	0.50	0.50	-	-	-	0.781	0.714	0.742	0.706	0.50	0.678	0.64	0.687	0.659	0.50	0.50	0.50	0.50	-	-
SEEDEmotion RecognitionWS	0.43	0.65	0.748	0.66	0.66	0.60	0.64	0.68	0.66	0.59	0.719	0.66	0.68	0.37	0.67	0.63	0.62	0.804	0.69	0.50	0.68	0.7110	0.795	0.69	0.47	0.35	-	-	-	0.36	0.64	0.60	0.872	0.52	0.69	0.786	0.787	0.833	0.65	0.56	0.62	-	0.891	0.61
SEEDEmotion RecognitionCS	0.45	0.51	0.50	0.51	0.53	0.47	0.51	0.539	0.49	0.47	0.50	0.49	0.52	0.35	0.50	0.553	0.51	0.545	0.572	0.42	0.5310	0.544	0.49	0.537	0.44	0.33	-	-	-	0.49	0.47	0.49	0.52	0.49	0.48	0.48	0.546	0.50	0.538	0.43	0.48	-	0.581	0.33
FACEDEmotion RecognitionWS	0.12	0.3110	0.30	0.348	0.16	0.394	0.22	0.501	0.357	0.375	0.422	0.13	0.19	0.11	0.319	0.16	0.12	0.393	0.28	0.27	0.21	0.17	0.17	0.16	0.12	0.12	-	-	-	0.13	0.11	0.12	0.366	0.14	0.15	0.26	0.26	0.20	-	0.16	0.16	-	0.28	0.22
FACEDEmotion RecognitionCS	0.11	0.279	0.23	0.316	0.13	0.353	0.19	0.461	0.317	0.325	0.372	0.14	0.18	0.11	0.26	0.14	0.12	0.324	0.22	0.24	0.18	0.16	0.16	0.15	0.13	0.13	-	-	-	0.12	0.11	0.12	0.298	0.14	0.14	0.23	0.25	0.2710	-	0.15	0.19	-	0.25	0.20
DTU-AADGender Attention DecodingWS	0.54	0.56	0.6910	0.56	0.60	0.63	0.59	0.59	0.60	0.53	0.59	0.64	0.59	0.50	0.57	0.55	0.52	0.743	0.734	0.60	0.709	0.68	0.707	0.63	0.50	0.50	-	-	-	0.03	0.57	0.51	0.708	0.901	0.54	0.725	0.67	0.716	-	0.57	0.58	-	0.782	0.56
DTU-AADGender Attention DecodingCS	0.51	0.50	0.51	0.51	0.50	0.50	0.48	0.50	0.00	0.50	0.518	0.51	0.51	0.50	0.519	0.525	0.50	0.542	0.50	0.50	0.543	0.5110	0.50	0.527	0.50	0.34	-	-	-	0.50	0.50	0.45	0.534	0.50	0.50	0.526	0.551	0.51	-	0.50	0.49	-	0.48	0.47
DTU-AADGender x Left/Right Attention DecodingWS	0.27	0.26	0.408	0.28	0.30	0.26	0.33	0.30	0.29	0.25	0.33	0.33	0.29	0.25	0.28	0.27	0.25	0.483	0.464	0.32	0.3910	0.417	0.409	0.36	0.25	0.25	-	-	-	0.25	0.26	0.28	0.426	0.512	-	0.445	0.35	0.37	-	0.31	0.33	-	0.531	0.30
DTU-AADGender x Left/Right Attention DecodingCS	0.25	0.25	0.25	0.25	0.25	0.26	0.26	0.25	0.274	0.2610	0.25	0.25	0.25	0.26	0.268	0.26	0.25	0.25	0.25	0.26	0.26	0.282	0.26	0.276	0.267	0.25	-	-	-	0.25	0.25	0.281	0.26	0.23	0.26	0.275	0.26	0.273	-	0.269	0.22	-	0.25	0.25
DTU-AADLeft/Right Attention DecodingWS	0.51	0.23	0.597	0.51	0.50	0.51	0.57	0.54	0.52	0.50	0.54	0.52	0.51	0.51	0.51	0.50	0.51	0.681	0.662	0.53	0.633	0.615	0.606	0.5810	0.50	0.50	-	-	-	0.50	0.51	0.52	0.589	0.634	0.50	0.57	0.56	0.50	-	0.54	0.56	-	0.588	0.51
DTU-AADLeft/Right Attention DecodingCS	0.48	0.28	0.50	0.50	0.49	0.50	0.49	0.51	0.519	0.50	0.50	0.49	0.50	0.523	0.516	0.50	0.50	0.49	0.50	0.49	0.518	0.50	0.49	0.49	0.50	0.50	-	-	-	0.47	0.517	0.35	0.521	0.47	-	0.515	0.48	0.50	-	0.49	0.524	-	0.522	0.5110
BCIC-IV-2BLeft/Right Hand MIWS	0.51	0.70	0.65	0.72	0.60	0.68	0.743	0.71	0.7210	0.71	0.742	0.62	0.63	0.50	0.70	0.738	0.52	0.66	0.63	0.737	0.52	0.60	-	0.70	0.50	0.50	-	-	-	0.745	0.736	0.739	0.72	0.50	0.72	-	0.71	-	-	-	0.57	0.50	0.761	0.744
BCIC-IV-2BLeft/Right Hand MICS	0.51	0.706	0.61	0.708	0.63	0.69	0.68	0.69	0.709	0.68	0.712	0.60	0.61	0.51	0.69	0.711	0.49	0.64	0.57	0.704	0.53	0.55	-	0.68	0.51	0.52	-	-	-	0.69	0.69	0.67	0.67	0.50	0.705	0.58	0.6910	-	0.50	0.50	-	0.50	0.703	0.707
Large-MILeft/Right/Hand/LegWS	0.39	0.68	0.68	0.67	0.49	0.64	0.717	0.65	0.67	0.60	0.6910	0.46	0.60	0.25	0.63	0.62	0.37	0.733	0.715	0.734	0.58	0.54	0.52	0.716	0.29	0.39	-	-	-	0.25	0.42	0.63	0.64	0.48	0.64	-	0.68	0.708	-	0.49	0.52	0.762	0.831	0.699
Large-MILeft/Right/Hand/LegCS	0.38	0.53	0.53	0.58	0.48	0.60	0.61	0.54	0.668	0.59	0.60	0.42	0.53	0.25	0.649	0.55	0.35	0.713	0.667	0.704	0.54	0.58	0.50	0.58	0.30	0.25	-	-	-	0.25	0.39	0.6210	0.61	0.44	0.686	-	0.61	-	0.705	-	-	0.791	0.742	0.59
Large-MILeft/Right + PassiveWS	0.30	0.70	0.67	0.70	0.60	0.57	0.70	0.69	0.70	0.60	0.729	0.36	0.64	0.34	0.65	0.65	0.41	0.754	0.753	0.7110	0.61	0.65	0.54	0.746	0.36	0.33	-	-	-	0.33	0.40	0.63	0.66	0.55	0.60	-	0.745	0.728	-	0.60	0.62	0.772	0.831	0.727
Large-MILeft/Right + PassiveCS	0.39	0.64	0.56	0.62	0.64	0.63	0.676	0.63	0.63	0.61	0.62	0.34	0.6510	0.39	0.63	0.63	0.44	0.677	0.65	0.732	0.57	0.63	0.51	0.668	0.41	0.55	-	-	-	0.33	0.39	0.64	0.703	0.669	0.684	-	0.675	-	-	-	-	0.791	0.63	0.64
Large-MILeft/Right Hand MIWS	0.37	0.80	0.75	0.8110	0.72	0.78	0.826	0.78	0.819	0.78	0.827	0.00	0.73	0.50	0.75	0.79	0.55	0.828	0.824	0.833	0.77	0.80	0.68	0.825	0.51	0.79	-	-	-	0.50	0.50	0.54	0.69	0.72	0.75	-	0.78	0.80	0.73	0.72	-	0.842	0.861	0.80
Large-MILeft/Right Hand MICS	0.27	0.845	0.68	0.82	0.73	0.854	0.77	0.75	0.847	0.848	0.8410	0.62	0.77	-	0.852	0.81	0.62	0.871	0.80	0.81	0.76	0.853	0.75	0.77	0.50	0.50	-	-	-	0.50	0.50	0.73	0.74	0.80	0.849	-	0.81	-	-	-	0.72	0.846	0.78	0.77
Large-MIHand vs Leg MIWS	0.50	0.77	0.7810	0.76	0.69	0.72	0.77	0.74	0.76	0.69	0.805	0.53	0.72	0.54	0.74	0.72	0.57	0.813	0.806	0.804	0.73	0.69	0.71	0.797	0.53	0.50	-	-	-	0.50	0.58	0.76	0.788	0.66	0.76	-	0.77	-	-	-	-	0.842	0.871	0.789
Large-MIHand vs Leg MICS	0.31	0.754	0.67	0.70	0.66	0.65	0.739	0.68	0.747	0.65	0.68	0.51	0.65	0.53	0.69	0.67	0.54	0.745	0.70	0.746	0.69	0.68	0.67	0.72	0.53	0.70	-	-	-	0.50	0.62	0.63	0.70	0.64	0.763	-	0.7210	0.738	-	-	-	0.861	0.782	0.67
Large-MIIndividual FingersWS	0.21	0.4010	0.39	0.39	0.31	0.37	0.417	0.38	0.37	0.37	0.425	0.24	0.32	0.20	0.35	0.36	0.21	0.426	0.418	0.462	0.32	0.29	0.28	0.36	0.22	0.20	-	-	-	0.20	0.21	0.32	0.34	0.22	0.38	-	0.409	0.37	-	-	-	0.453	0.521	0.444
Large-MIIndividual FingersCS	0.22	0.31	0.27	0.30	0.27	0.339	0.31	0.31	0.3210	0.336	0.338	0.23	0.28	0.20	0.29	0.337	0.21	0.27	0.30	0.363	0.26	0.25	0.23	0.30	0.21	0.20	-	-	-	0.20	0.20	0.24	0.25	0.24	0.371	-	-	-	-	-	-	0.364	0.372	0.335
Large-MILeft/Right/Hand/Leg/TongueWS	0.26	0.63	0.64	0.63	0.45	0.58	0.6510	0.59	0.62	0.54	0.668	0.43	0.55	0.20	0.57	0.59	0.31	0.693	0.667	0.674	0.54	0.46	0.47	0.676	0.23	0.32	-	-	-	0.20	0.31	0.57	0.60	0.37	0.61	-	0.669	-	-	-	-	0.712	0.801	0.675
Large-MILeft/Right/Hand/Leg/TongueCS	0.27	0.52	0.53	0.55	0.50	0.56	0.5710	0.50	0.598	0.51	0.626	0.43	0.47	0.20	0.51	0.50	0.32	0.662	0.617	0.663	0.50	0.45	0.44	0.55	0.24	0.30	-	-	-	0.20	0.28	0.589	0.56	0.42	0.635	-	0.56	-	-	-	-	0.721	0.644	0.52
Large-MIWith RestWS	0.18	-	0.534	0.42	0.32	0.36	0.4510	0.39	0.40	0.29	0.41	0.32	0.42	0.09	0.35	0.38	0.28	0.41	0.506	0.478	0.44	0.38	0.40	0.487	0.11	0.14	-	-	-	0.09	0.15	0.09	0.44	0.34	0.515	-	0.543	0.562	0.459	-	-	0.591	-	-
Large-MIWith RestCS	0.34	-	0.42	0.41	0.41	0.38	0.439	0.39	0.438	0.33	0.42	0.40	0.467	0.17	0.41	0.40	0.36	0.38	0.4310	0.523	0.36	0.38	0.39	0.485	0.21	0.16	-	-	-	0.17	0.19	0.17	0.494	0.36	0.591	-	0.476	-	-	-	-	0.582	-	-
PhysioNet-MILeft/Right/Both Hands/FeetWS	0.29	0.587	0.51	0.579	0.46	0.52	0.55	0.56	0.54	0.54	0.604	0.36	0.50	0.25	0.51	0.54	0.29	0.51	0.54	0.5710	0.50	0.47	0.44	0.588	0.28	0.47	-	-	-	0.613	0.612	0.621	0.56	0.46	0.25	0.595	0.56	-	0.25	0.25	0.47	0.25	0.596	0.57
PhysioNet-MILeft/Right/Both Hands/FeetCS	0.29	0.519	0.47	0.50	0.43	0.47	0.50	0.50	0.49	0.50	0.535	0.35	0.46	0.25	0.48	0.49	0.33	0.47	0.49	0.527	0.44	0.43	0.41	0.543	0.27	0.42	-	-	-	0.561	0.544	0.552	0.518	0.46	0.50	-	0.49	0.5110	-	-	0.46	0.25	0.45	0.526
PhysioNet-MILeft/Right Hand MIWS	0.51	0.79	0.74	0.819	0.70	0.76	0.74	0.77	0.79	0.78	0.8010	0.63	0.73	0.51	0.74	0.77	0.54	0.75	0.75	0.76	0.73	0.70	0.68	0.831	0.52	0.75	-	-	-	0.832	0.834	0.825	0.79	0.74	0.76	0.833	0.818	-	0.50	0.50	0.77	0.50	0.826	0.817
PhysioNet-MILeft/Right Hand MICS	0.53	0.7510	0.72	0.75	0.71	0.74	0.71	0.75	0.75	0.774	0.777	0.61	0.72	0.50	0.72	0.75	0.57	0.72	0.74	0.74	0.71	0.69	0.66	0.782	0.49	0.73	-	-	-	0.811	0.775	0.776	-	0.63	-	-	0.71	-	-	-	0.768	0.50	0.783	0.769
PhysioNet-MIHand vs Feet MIWS	0.50	0.63	0.64	0.57	0.50	0.669	0.678	0.685	0.60	0.56	0.64	0.52	0.55	-	0.52	0.50	0.50	0.65	0.6610	0.63	0.60	0.54	0.58	0.686	0.50	0.677	-	-	-	0.721	0.684	0.712	0.64	0.59	0.64	-	0.65	-	-	0.50	0.61	0.50	0.64	0.703
PhysioNet-MIHand vs Feet MICS	0.50	0.63	0.62	0.56	0.50	0.63	0.648	0.649	0.62	0.54	0.6410	0.49	0.54	-	0.54	0.50	0.50	0.657	0.63	0.61	0.58	0.50	0.56	0.656	0.50	0.61	-	-	-	0.692	0.685	0.684	0.63	0.55	0.63	-	0.62	-	0.50	-	0.61	0.50	0.721	0.693
Stroke-MILeft/Right Hand MIWS	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.507	-	-	-	0.582	0.536	0.554	0.573	0.555	0.50	-	0.508	-	0.509	-	-	0.5010	0.601	0.50
Stroke-MILeft/Right Hand MICS	0.508	0.509	0.5010	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.50	0.506	-	-	-	0.551	0.47	0.50	0.515	0.542	0.49	-	-	-	-	-	-	0.507	0.523	0.514
BCIC-IV-2ALeft/Right Hand MIWS	0.53	0.52	0.59	0.639	0.57	0.55	0.56	0.673	0.50	0.50	0.655	0.50	0.59	0.50	0.51	0.59	0.57	0.54	0.731	0.62	0.58	0.61	0.54	0.674	0.51	0.50	-	-	-	0.6210	0.648	0.656	-	0.657	0.49	-	0.61	0.59	-	-	-	0.50	0.722	0.50
BCIC-IV-2ALeft/Right Hand MICS	0.55	0.665	0.53	0.723	0.6410	0.60	0.54	0.762	0.50	0.50	0.649	0.50	0.50	0.50	0.53	0.656	0.52	0.52	0.801	0.724	0.51	0.52	0.52	0.62	0.49	0.50	-	-	-	0.52	0.50	0.59	-	0.50	0.53	0.648	0.55	-	0.50	0.50	-	0.50	0.657	0.47
BCIC-IV-2ALeft/Right/Hand/Foot/TongueWS	0.26	0.469	0.42	0.475	0.26	0.31	0.41	0.477	0.41	0.40	0.513	0.25	0.38	0.25	0.40	0.26	0.30	0.40	0.571	0.40	0.39	0.37	0.38	0.40	0.26	0.25	-	-	-	0.494	0.4510	0.468	-	0.37	0.33	0.476	0.43	-	-	-	-	0.25	0.562	0.41
BCIC-IV-2ALeft/Right/Hand/Foot/TongueCS	0.25	0.25	0.30	0.447	0.26	0.4010	0.39	0.445	0.40	0.418	0.501	0.25	0.29	0.25	0.25	0.26	0.28	0.26	0.492	0.419	0.26	0.26	0.37	0.32	0.25	0.25	-	-	-	0.463	0.40	0.40	-	0.25	0.31	-	0.39	0.39	-	-	0.446	0.25	0.454	0.37
BCIC-IV-2AHand vs Feet MIWS	0.50	0.61	0.60	0.677	0.50	0.51	0.58	0.60	0.46	0.04	0.48	0.50	0.59	-	0.62	0.48	0.50	0.56	0.50	0.63	0.55	0.50	0.32	0.702	0.50	0.50	-	-	-	0.703	0.685	0.676	0.6410	0.56	0.60	-	0.684	0.669	-	-	-	0.50	0.731	0.668
BCIC-IV-2AHand vs Feet MICS	0.53	0.56	0.56	0.5910	0.50	0.58	0.52	0.51	0.47	-	0.53	0.50	0.51	-	0.691	0.50	0.50	0.55	0.51	0.56	0.51	0.50	0.52	0.666	0.50	0.50	-	-	-	0.692	0.675	0.684	0.609	0.53	0.57	-	0.628	-	-	-	-	0.50	0.683	0.647
OpenBMILeft/Right Hand MIWS	0.64	0.74	0.71	0.75	0.68	0.73	0.72	0.73	0.767	0.72	0.784	0.69	0.68	0.51	0.72	0.71	0.68	0.766	0.67	0.759	0.67	0.72	0.72	0.768	0.50	0.66	-	-	-	0.50	0.51	0.63	0.69	0.70	0.7510	0.822	0.72	0.73	-	-	0.75	0.823	0.871	0.775
OpenBMILeft/Right Hand MICS	0.64	0.7310	0.67	0.737	0.66	0.71	0.71	0.71	0.736	0.72	0.763	0.66	0.69	0.49	0.71	0.70	0.66	0.738	0.66	0.745	0.65	0.67	0.67	0.764	0.50	0.50	-	-	-	0.50	0.52	0.64	0.67	0.69	0.72	-	-	-	-	-	-	0.822	0.851	0.739
HGDLeft/Right/Hand/Foot/TongueWS	0.45	0.74	0.72	0.7710	0.65	0.74	0.73	0.778	0.73	0.68	0.825	0.55	0.68	0.33	0.73	0.66	0.54	0.842	0.779	0.73	0.65	0.69	0.71	0.72	0.38	0.52	-	-	-	0.843	0.834	0.807	0.71	0.63	0.60	0.816	0.75	-	0.33	-	0.74	0.33	0.891	0.71
HGDLeft/Right/Hand/Foot/TongueCS	0.46	0.755	0.64	0.756	0.68	0.70	0.66	0.802	0.67	0.738	0.747	0.45	0.63	0.35	0.71	0.70	0.51	0.68	0.62	0.71	0.55	0.65	0.48	0.64	0.38	0.55	-	-	-	0.729	0.764	0.763	0.69	0.55	0.60	-	-	0.7110	-	-	-	0.33	0.801	0.67
HGDLeft/Right Hand MIWS	0.50	0.775	0.67	0.768	0.60	0.759	0.75	0.776	0.74	0.74	0.822	0.61	0.63	0.50	0.69	0.59	0.54	0.794	0.73	0.72	0.67	0.71	0.66	0.63	0.49	0.50	-	-	-	0.813	0.767	0.7510	0.71	0.61	0.57	-	0.70	-	-	0.50	-	0.50	0.881	0.70
HGDLeft/Right Hand MICS	0.50	0.776	0.55	0.759	0.59	0.784	0.68	0.802	0.793	0.767	0.73	0.57	0.59	0.50	0.68	0.61	0.57	0.67	0.63	0.768	0.59	0.59	0.55	0.63	0.52	0.50	-	-	-	0.775	0.74	0.7410	0.68	0.54	0.50	-	-	0.66	-	-	-	0.50	0.801	0.67
HGDHand vs Feet MIWS	0.74	0.92	0.947	0.92	0.89	0.89	0.90	0.89	0.929	0.85	0.954	0.80	0.89	-	0.938	0.90	0.77	0.962	0.92	0.87	0.86	0.89	0.9210	0.90	0.50	0.80	-	-	-	0.963	0.955	0.89	0.88	0.86	0.91	-	-	0.946	-	-	0.87	0.50	0.971	0.87
HGDHand vs Feet MICS	0.66	0.902	0.85	0.888	0.73	0.74	0.84	0.8810	0.81	0.904	0.889	0.73	0.81	-	0.88	0.72	0.66	0.79	0.74	0.87	0.71	0.77	0.68	0.78	0.50	0.75	-	-	-	0.905	0.903	0.887	0.87	0.71	0.84	-	0.896	-	-	-	-	0.50	0.961	0.85
Meng2019Cursor Movement DetectionWS	0.75	0.84	0.864	0.83	0.81	0.58	0.848	0.82	0.849	0.80	0.863	0.80	0.81	0.68	0.82	0.82	0.76	0.865	0.83	0.82	0.80	0.81	0.83	0.8410	0.67	0.64	-	-	-	0.79	0.66	0.68	0.82	0.76	0.79	0.857	0.856	-	-	-	-	0.891	0.872	0.81
Meng2019Cursor Movement DetectionCS	0.69	0.73	0.72	0.739	0.71	0.58	0.71	0.70	0.72	0.72	0.755	0.71	0.73	0.65	0.72	0.7310	0.70	0.746	0.71	0.748	0.70	0.70	0.71	0.747	0.62	0.65	-	-	-	0.71	0.60	0.63	0.70	0.73	0.73	-	-	0.763	-	-	0.71	0.801	0.792	0.764
Meng2019Cursor ControlWS	0.64	0.71	0.73	0.70	0.69	0.69	0.72	0.73	0.70	0.67	0.7310	0.70	0.68	0.49	0.71	0.68	0.67	0.747	0.754	0.70	0.72	0.748	0.72	0.746	0.51	0.61	-	-	-	0.52	0.56	0.61	0.66	0.68	0.70	-	0.745	-	-	-	0.753	0.762	0.811	0.749
Meng2019Cursor ControlCS	0.48	0.53	0.51	0.52	0.46	0.49	0.55	0.48	0.54	0.51	0.597	0.48	0.56	0.50	0.54	0.47	0.49	0.614	0.55	0.54	0.55	0.55	0.56	0.615	0.50	0.596	-	-	-	0.52	0.5910	0.56	0.598	0.599	0.51	-	-	0.58	-	-	-	0.682	0.701	0.643
Meng2019Cursor Control + RestWS	0.47	0.66	0.714	0.66	0.63	0.54	0.715	0.66	0.66	0.62	0.697	0.64	0.64	0.44	0.64	0.64	0.60	0.723	0.698	0.66	0.64	0.66	0.66	0.689	0.41	0.41	-	-	-	0.34	0.46	0.52	0.64	0.55	0.60	-	0.706	-	-	-	0.67	0.762	0.791	0.6710
Meng2019Cursor Control + RestCS	0.42	0.50	0.49	0.48	0.49	0.42	0.535	0.48	0.48	0.47	0.5010	0.49	0.519	0.41	0.49	0.49	0.45	0.544	0.45	0.527	0.46	0.44	0.48	0.518	0.40	0.39	-	-	-	0.33	0.41	0.46	0.49	0.47	0.48	-	0.536	-	-	-	-	0.602	0.671	0.583
UCDDB-SleepSleep Staging 30s 5-classWS	0.45	0.69	0.57	0.65	0.65	0.33	0.752	0.62	0.66	0.63	0.737	0.57	0.62	0.20	0.69	0.63	0.64	0.69	0.761	0.46	0.70	0.61	0.64	0.7310	0.51	-	-	0.754	0.753	0.739	0.69	0.72	0.72	-	-	-	0.738	0.735	-	-	-	-	0.736	0.61
UCDDB-SleepSleep Staging 30s 5-classCS	0.51	0.7010	0.52	0.64	0.63	0.27	0.735	0.58	0.64	0.62	0.69	0.56	0.62	0.20	0.67	0.62	0.65	0.64	0.719	0.45	0.70	0.61	0.63	0.751	0.48	-	-	0.736	0.734	0.70	0.62	0.64	0.743	-	-	-	0.742	0.737	-	-	-	-	0.728	0.58
UCDDB-SleepSleep Staging 30s 6-classWS	0.34	0.58	0.48	0.55	0.55	0.28	0.644	0.51	0.56	0.53	0.6210	0.49	0.53	0.17	0.59	0.54	0.55	0.59	0.642	0.42	0.59	0.53	0.53	0.629	0.46	-	-	0.635	0.636	0.638	0.59	0.61	0.61	-	-	-	0.641	0.637	-	-	-	-	0.643	0.53
UCDDB-SleepSleep Staging 30s 6-classCS	0.40	0.59	0.44	0.54	0.55	0.23	0.609	0.49	0.54	0.51	0.59	0.48	0.52	0.17	0.56	0.54	0.55	0.53	0.618	0.34	0.6010	0.52	0.52	0.627	0.43	-	-	0.632	0.631	0.59	0.53	0.17	0.634	-	-	-	0.633	0.625	-	-	-	-	0.626	0.51
UCDDB-SleepSleep/Wake 30sWS	0.70	0.85	0.69	0.87	0.87	0.71	0.78	0.80	0.83	0.84	0.888	0.55	0.86	-	0.86	0.85	0.894	0.88	0.892	0.70	0.87	0.886	0.889	0.893	0.60	-	-	0.88	0.88	0.895	0.8810	0.88	0.87	-	-	-	0.88	0.887	-	-	-	-	0.901	0.82
UCDDB-SleepSleep/Wake 30sCS	0.63	0.85	0.65	0.893	0.86	0.63	0.67	0.74	0.75	0.82	0.87	0.60	0.85	-	0.87	0.86	0.894	0.88	0.901	0.74	0.889	0.887	0.88	0.88	0.60	-	-	0.888	0.88	0.8810	0.88	0.87	0.896	-	-	-	0.86	0.895	-	-	-	-	0.892	0.84
UCDDB-SleepWake/NREM/REM 30sWS	0.59	0.83	0.71	0.84	0.84	0.41	0.859	0.80	0.8410	0.81	0.863	0.09	0.76	-	0.82	0.82	0.864	0.81	0.872	0.76	0.81	0.84	0.858	0.81	0.59	-	-	0.857	0.865	0.84	0.84	0.84	0.82	-	-	-	0.856	0.83	-	-	-	-	0.871	0.79
UCDDB-SleepWake/NREM/REM 30sCS	0.59	0.81	0.70	0.856	0.82	0.39	0.79	0.72	0.82	0.79	0.854	0.57	0.80	-	0.82	0.81	0.871	0.81	0.862	0.78	0.8410	0.849	0.857	0.83	0.60	-	-	0.858	0.855	0.81	0.81	0.82	0.83	-	-	-	0.81	0.82	-	-	-	-	0.863	0.82
HMC-SleepSleep/Wake 30sWS	0.64	0.91	0.76	0.936	0.90	0.92	0.80	0.86	0.92	0.86	0.91	0.92	0.89	0.50	0.91	0.87	0.935	0.91	0.928	0.82	0.91	0.929	0.90	0.933	0.76	-	-	-	-	0.934	0.942	0.91	0.89	-	-	-	0.9210	0.937	-	-	-	-	0.941	0.87
HMC-SleepSleep/Wake 30sCS	0.57	0.83	0.71	0.82	0.83	0.82	0.68	0.79	0.849	0.82	0.874	0.82	0.84	0.50	0.83	0.81	0.84	0.8410	0.83	0.79	0.848	0.83	0.83	0.83	0.77	-	-	-	-	0.883	0.881	0.875	0.882	-	-	-	0.84	0.857	-	-	-	-	0.876	0.82
HMC-SleepWake/NREM/REM 30sWS	0.44	0.866	0.64	0.869	0.83	0.892	0.82	0.82	0.81	0.66	0.84	0.78	0.76	0.33	0.85	0.78	0.85	0.8510	0.893	0.73	0.867	0.81	0.79	0.884	0.54	-	-	-	-	0.901	0.885	0.85	0.77	-	-	-	0.85	0.84	-	-	-	-	0.868	0.77
HMC-SleepWake/NREM/REM 30sCS	0.47	0.793	0.56	0.75	0.73	0.786	0.75	0.70	0.72	0.67	0.787	0.68	0.769	0.35	0.785	0.70	0.74	0.75	0.76	0.68	0.792	0.73	0.74	0.784	0.57	-	-	-	-	0.791	0.7610	0.75	0.72	-	-	-	0.76	0.778	-	-	-	-	0.75	0.71
MigraineDBSSAEP Frequency DiscriminationWS	0.49	0.50	0.49	0.527	0.50	0.50	0.51	0.50	0.30	0.50	0.27	0.50	0.50	0.48	0.50	0.5110	0.50	0.48	0.528	0.534	0.529	0.51	0.47	0.51	0.50	0.50	-	-	-	0.641	0.51	0.552	0.535	0.50	0.526	0.51	0.50	-	-	-	-	0.50	0.50	0.553
MigraineDBSSAEP Frequency DiscriminationCS	0.37	0.49	0.49	0.48	0.519	0.50	0.51	0.518	0.49	0.45	0.50	0.50	0.49	0.50	0.527	0.51	0.49	0.49	0.50	0.50	0.5110	0.50	0.17	0.50	0.47	0.50	-	-	-	0.651	0.50	0.642	0.536	0.50	0.555	-	-	-	-	-	0.49	0.50	0.573	0.554
MigraineDBSSVEP Frequency DiscriminationWS	0.46	0.62	0.51	0.66	0.50	0.49	0.798	0.50	0.62	0.51	0.71	0.50	0.55	0.51	0.52	0.50	0.51	0.56	0.50	0.799	0.47	0.52	0.49	0.807	0.49	0.50	-	-	-	0.893	0.835	0.892	0.7610	0.50	0.826	-	0.50	-	-	-	-	0.50	0.901	0.844
MigraineDBSSVEP Frequency DiscriminationCS	0.48	0.63	0.50	0.69	0.51	0.50	0.798	0.47	0.63	0.55	0.70	0.50	0.54	0.50	0.58	0.50	0.50	0.55	0.49	0.817	0.51	0.51	0.52	0.769	0.49	0.50	-	-	-	0.901	0.853	0.892	0.7210	0.50	0.836	-	-	-	0.50	-	-	0.50	0.854	0.835
MigraineDB4-Hz SSVEP Migraine DetectionWS	0.53	0.49	0.958	0.69	0.63	0.52	0.83	0.70	0.48	0.50	0.88	0.60	0.69	0.50	0.72	0.53	0.57	0.9410	0.82	0.73	0.82	0.86	0.959	0.93	0.50	0.50	-	-	-	0.994	0.995	0.986	0.91	1.002	0.77	-	0.977	-	0.52	-	0.85	1.001	1.003	0.73
MigraineDB6-Hz SSVEP Migraine DetectionWS	0.57	0.59	0.93	0.67	0.60	0.65	0.85	0.71	0.52	0.50	0.86	0.56	0.71	0.50	0.70	0.51	0.50	0.948	0.85	0.72	0.82	0.85	0.939	0.90	0.51	0.50	-	-	-	1.004	0.995	0.977	0.88	1.002	0.77	0.996	0.9310	-	-	-	0.86	1.001	1.003	0.75
MigraineDB4-Hz SSAEP Migraine DetectionWS	0.55	0.64	0.919	0.66	0.68	0.67	0.82	0.72	0.60	0.61	0.9110	0.50	0.75	0.50	0.69	0.61	0.60	0.89	0.81	0.73	0.80	0.81	0.928	0.86	0.50	0.50	-	-	-	1.004	0.995	0.947	0.89	1.001	0.87	-	0.966	-	-	0.51	0.83	1.002	1.003	0.78
MigraineDBResting Migraine DetectionWS	0.70	0.85	0.99	0.92	0.94	0.51	0.96	0.86	0.88	0.75	0.98	0.83	0.95	0.50	0.96	0.89	0.76	1.008	0.96	0.85	0.96	0.98	1.004	1.007	0.61	0.50	-	-	-	1.001	0.9910	1.009	0.95	1.002	-	-	1.006	1.005	-	0.50	-	1.003	-	0.70
MigraineDB6-Hz SSAEP Migraine DetectionWS	0.55	0.64	0.918	0.66	0.67	0.68	0.81	0.73	0.62	0.50	0.909	0.57	0.74	0.50	0.71	0.51	0.62	0.89	0.82	0.74	0.82	0.84	0.90	0.88	0.51	0.50	-	-	-	0.995	0.994	0.946	0.9010	1.003	0.85	-	0.947	-	-	-	-	1.001	1.002	0.79
MigraineDBSSVEP Migraine DetectionWS	0.55	0.75	0.999	0.86	0.86	0.94	0.91	0.84	0.85	0.67	0.96	0.73	0.93	-	0.92	0.80	0.75	0.9910	0.89	0.81	0.91	0.96	1.007	0.98	0.51	0.50	-	-	-	1.003	1.006	1.008	0.95	1.001	0.85	1.005	-	-	-	0.51	-	1.004	1.002	0.84
MigraineDBSSAEP Migraine DetectionWS	0.54	0.86	0.96	0.87	0.87	0.79	0.87	0.78	0.78	0.72	0.9610	0.69	0.93	-	0.89	0.81	0.80	0.969	0.87	0.82	0.89	0.93	0.997	0.988	0.54	0.50	-	-	-	1.002	1.005	1.006	0.95	1.004	0.95	-	-	-	0.50	-	-	1.001	1.003	0.86
BCIC-IV-1Left/Right Hand MIWS	0.47	0.49	0.49	0.50	0.51	0.49	0.50	0.533	0.50	0.529	0.49	0.50	0.50	0.50	0.50	0.50	0.526	0.50	0.49	0.542	0.525	0.50	0.50	0.51	0.49	0.51	-	-	-	0.551	0.49	0.49	-	0.49	0.49	-	0.534	-	0.5210	-	-	0.528	0.49	0.527
BCIC-IV-1Left/Right Hand MICS	0.42	0.529	0.555	0.50	0.47	0.51	0.50	0.536	0.50	0.553	0.50	0.50	0.537	0.50	0.562	0.46	0.49	0.48	0.50	0.5210	0.554	0.50	0.51	0.48	0.51	0.47	-	-	-	0.51	0.47	0.50	0.48	0.47	0.50	-	0.50	-	-	-	-	0.561	0.51	0.528
BCIC-IV-1Left Hand vs Foot MIWS	0.40	0.50	0.594	0.50	0.46	0.50	0.49	0.49	0.50	0.48	0.50	0.50	0.51	0.50	0.51	0.42	0.45	0.50	0.47	0.603	0.549	0.46	0.577	0.50	0.49	0.651	-	-	-	0.50	0.5310	0.575	-	0.52	0.51	0.652	0.576	-	-	0.568	-	0.51	0.53	0.51

Cohen's Kappa

Dataset · task · split	Baseline Models																									Foundation Models
Dataset · task · split	ADFCNN	ATCNet	BiDANN	CTNet	DBConformer	DeepConvNet	DeepSleepNet	EEGConformer	EEGInceptionERP	EEGNet	EEGNeX	EEGWaveNet	FBCNet	HSLT	IFNet	MSCFormer	MSVTNet	ShallowConvNet	SleepEEGNet	SleepTransformer	SlimSeiz	TMSA-Net	TSception	U-Sleep	YASA	BENDR	BIOT · Prest 16ch	BIOT · Shhs Prest 18ch	BIOT · Six Datasets 18ch	CBraMod	CodeBrain	CSBrain	EEGMamba	EEGPT	LaBraM	LEAD	LUNA · Base	LUNA · Large	mdJPT	MIRepNet	NeuroGPT	NeuroRVQ	REVE · Base	REVE · Large
EEGMatMental Arithmetic vs RestWS	0.01	0.27	0.19	0.09	0.00	0.18	0.739	0.64	0.06	0.03	0.26	0.03	0.10	0.00	0.14	0.00	0.00	0.824	0.843	0.14	0.00	0.15	0.37	0.737	-0.04	0.738	-	-	-	0.7110	0.796	0.805	0.28	0.42	0.39	0.911	0.50	0.53	0.00	0.00	0.68	0.00	0.862	0.12
EEGMatMental Arithmetic vs RestCS	-0.00	0.03	0.11	0.03	0.00	-0.00	0.26	0.27	-0.06	0.01	0.08	-0.01	0.01	0.00	0.01	0.00	0.00	0.454	0.33	0.04	0.415	0.04	0.26	0.378	0.00	0.397	-	-	-	0.522	0.453	0.3410	0.32	0.359	0.24	0.621	0.33	0.25	0.00	0.00	0.406	0.00	0.29	0.10
TUEVEpileptiform EventsWS	0.46	0.73	0.89	0.75	0.73	0.10	0.72	0.79	0.78	0.56	0.82	0.57	0.75	0.00	0.77	0.71	0.56	0.919	0.90	0.68	0.89	0.80	0.81	0.918	0.44	0.86	-	-	-	0.934	0.942	0.925	0.85	0.926	0.87	0.951	0.927	0.9110	0.00	0.00	0.81	0.00	0.943	0.70
TUEVEpileptiform EventsCS	0.16	0.591	0.31	0.555	0.39	0.00	0.13	0.28	0.468	0.05	0.536	0.02	0.40	0.00	0.573	0.459	0.4510	0.564	0.30	0.21	0.38	0.582	0.41	0.44	0.10	0.14	-	-	-	0.26	0.25	0.33	0.31	0.36	0.32	0.467	0.31	0.30	0.00	0.00	0.18	0.00	0.31	0.36
TUEVEpileptiform Event DetectionWS	0.31	0.79	0.88	0.80	0.79	0.00	0.72	0.83	0.81	0.63	0.84	0.75	0.82	-	0.83	0.78	0.69	0.946	0.9110	0.75	0.91	0.82	0.85	0.945	0.59	0.84	-	-	-	0.947	0.943	0.951	0.90	0.942	0.91	0.944	0.929	0.91	0.00	0.00	0.87	0.00	0.928	0.73
TUEVEpileptiform Event DetectionCS	0.02	0.681	0.40	0.577	0.53	0.00	0.50	0.34	0.49	0.08	0.5310	0.47	0.32	-	0.605	0.45	0.568	0.51	0.43	0.24	0.559	0.662	0.596	0.643	0.17	0.32	-	-	-	0.38	0.43	0.614	0.30	0.49	0.51	0.47	0.52	0.49	0.00	0.00	0.37	0.00	0.51	0.31
SHU-MILeft/Right Hand MIWS	0.19	0.31	0.49	0.28	0.26	0.28	0.62	0.30	0.35	0.25	0.39	0.36	0.28	0.01	0.27	0.26	0.15	0.52	0.64	0.68	0.44	0.33	0.39	0.698	0.01	0.06	-	-	-	0.715	0.716	0.717	0.6810	0.00	0.00	0.761	0.734	0.733	0.00	0.00	0.20	0.00	0.752	0.699
SHU-MILeft/Right Hand MICS	0.17	0.29	0.384	0.27	0.348	0.28	0.30	0.28	0.30	0.26	0.357	0.31	0.349	0.04	0.28	0.30	0.19	0.25	0.29	0.30	0.29	0.29	0.393	0.3110	0.06	0.00	-	-	-	0.30	0.31	0.26	0.28	0.12	0.00	0.441	0.375	0.356	0.00	0.00	0.15	0.00	0.442	0.29
TUSLBackground Slowing DetectionWS	0.00	0.07	0.53	0.24	0.31	0.26	0.22	0.31	0.02	-0.09	-0.01	0.00	-0.11	0.00	0.26	0.10	-0.01	0.46	0.21	-0.14	0.45	0.27	-0.02	0.756	0.29	0.26	-	-	-	0.6010	0.754	0.707	0.678	0.58	0.55	0.755	0.802	0.783	0.00	0.00	0.639	0.00	0.851	0.20
TUSLBackground Slowing DetectionCS	0.00	0.04	0.26	-0.00	0.00	0.27	0.13	0.09	0.01	-0.03	0.02	0.00	0.00	0.00	0.05	0.03	-0.03	0.00	0.00	0.05	0.15	0.12	0.00	0.368	0.13	-0.16	-	-	-	0.533	0.504	0.319	0.3110	0.16	0.475	0.561	0.31	0.21	0.00	0.00	0.436	0.00	0.542	0.397
TUSLSlowing + SeizureWS	0.12	0.15	0.51	0.02	0.04	0.11	0.42	0.11	0.10	0.05	0.31	0.00	0.16	0.00	0.21	0.12	0.22	0.48	0.43	0.12	0.27	0.33	0.16	0.649	0.03	0.24	-	-	-	0.696	0.772	0.764	0.5610	0.53	0.668	0.763	0.735	0.687	0.00	0.00	0.25	0.00	0.841	0.15
TUSLSlowing + SeizureCS	0.148	0.04	-0.10	0.02	0.00	0.04	-0.09	-0.01	-0.01	0.00	-0.00	0.00	0.01	0.00	0.02	0.01	-0.09	0.01	0.1110	0.00	0.10	0.04	0.00	0.00	0.186	-0.01	-	-	-	0.392	0.521	0.335	0.07	0.139	0.333	0.334	0.10	-0.01	0.00	0.00	0.01	0.00	0.187	0.01
Kaggle-INRIAP300 Feedback CorrectnessWS	0.04	-	0.268	0.2410	0.00	0.12	0.23	0.23	0.277	0.11	0.304	0.00	0.16	0.01	0.10	0.00	0.08	0.21	0.269	0.286	0.08	0.04	0.19	0.19	0.00	0.00	-	-	-	0.10	0.00	0.22	0.11	0.08	0.15	0.22	0.19	0.20	0.17	0.06	0.352	0.295	0.381	0.323
Kaggle-INRIAP300 Feedback CorrectnessCS	-0.02	-	0.219	0.16	0.00	0.16	0.16	0.19	0.265	0.218	0.256	0.00	0.19	0.00	0.04	0.00	0.05	-0.02	0.15	0.273	0.01	0.03	0.04	0.19	0.00	0.2010	-	-	-	-0.01	0.00	0.02	0.16	-0.01	0.237	0.11	0.07	0.10	0.00	0.06	0.20	0.321	0.282	0.274
ERP-BCIP300 Target DetectionWS	0.03	-	0.23	0.27	0.00	0.00	0.30	0.00	0.377	0.01	0.339	0.00	0.17	0.00	0.01	0.00	0.00	0.02	0.09	0.455	-0.00	-0.00	0.05	0.484	0.00	0.13	-	-	-	0.561	0.483	0.542	-	0.348	0.406	0.28	0.3110	0.00	0.00	0.00	0.00	0.00	-	-
ERP-BCIP300 Target DetectionCS	-0.00	-	0.23	0.30	0.00	0.00	0.31	0.00	0.379	0.01	0.3610	0.00	0.18	0.00	-0.00	0.00	0.00	0.01	0.14	0.454	0.01	0.00	0.03	0.456	0.00	0.00	-	-	-	0.571	0.455	0.522	0.463	0.00	0.407	0.32	0.378	0.34	0.00	0.00	0.00	0.00	-	-
SEEDEmotion RecognitionWS	0.15	0.47	0.628	0.49	0.49	0.40	0.46	0.52	0.49	0.40	0.579	0.50	0.53	0.06	0.51	0.45	0.43	0.704	0.53	0.25	0.52	0.5610	0.685	0.53	0.20	0.02	-	-	-	0.04	0.47	0.40	0.802	0.28	0.53	0.676	0.677	0.753	0.47	0.34	0.43	-	0.841	0.42
SEEDEmotion RecognitionCS	0.17	0.27	0.25	0.27	0.30	0.21	0.27	0.3010	0.24	0.21	0.26	0.23	0.28	0.03	0.26	0.323	0.26	0.315	0.362	0.14	0.309	0.314	0.24	0.316	0.16	0.00	-	-	-	0.24	0.21	0.23	0.29	0.24	0.23	0.23	0.317	0.25	0.308	0.15	0.22	-	0.381	-0.00
FACEDEmotion RecognitionWS	0.01	0.2210	0.21	0.268	0.05	0.314	0.12	0.441	0.277	0.305	0.352	0.02	0.09	0.00	0.239	0.05	0.01	0.323	0.19	0.18	0.12	0.07	0.06	0.06	0.01	0.00	-	-	-	0.02	0.00	0.01	0.296	0.04	0.05	0.17	0.16	0.09	-	0.06	0.06	-	0.20	0.11
FACEDEmotion RecognitionCS	0.00	0.189	0.13	0.236	0.03	0.263	0.09	0.391	0.227	0.244	0.292	0.04	0.08	0.00	0.17	0.04	0.01	0.235	0.13	0.14	0.07	0.05	0.05	0.04	0.02	0.03	-	-	-	0.01	-0.00	0.01	0.208	0.04	0.04	0.13	0.16	0.1810	-	0.05	0.08	-	0.16	0.10
DTU-AADGender Attention DecodingWS	0.08	0.11	0.3710	0.12	0.21	0.26	0.18	0.19	0.20	0.06	0.19	0.28	0.19	0.00	0.15	0.11	0.04	0.483	0.454	0.20	0.409	0.36	0.416	0.26	0.01	0.00	-	-	-	0.00	0.13	0.06	0.408	0.801	0.09	0.435	0.35	0.417	-	0.15	0.17	-	0.572	0.12
DTU-AADGender Attention DecodingCS	0.01	0.00	0.01	0.02	-0.00	-0.00	-0.04	0.00	0.00	-0.00	0.056	0.02	0.02	0.00	0.038	0.065	0.01	0.092	0.01	0.00	0.091	0.0310	-0.00	0.039	-0.00	-0.31	-	-	-	-0.00	-0.00	-0.03	0.064	0.00	0.00	0.047	0.083	0.02	-	0.00	-0.02	-	-0.04	-0.06
DTU-AADGender x Left/Right Attention DecodingWS	0.03	0.01	0.208	0.04	0.07	0.01	0.10	0.07	0.05	0.00	0.11	0.11	0.05	0.00	0.04	0.02	-0.01	0.313	0.294	0.09	0.1810	0.217	0.209	0.14	0.01	0.00	-	-	-	0.00	0.01	0.04	0.236	0.352	-	0.245	0.13	0.16	-	0.09	0.11	-	0.371	0.06
DTU-AADGender x Left/Right Attention DecodingCS	-0.01	-0.00	-0.01	-0.00	0.00	0.02	0.01	-0.00	0.034	0.0210	0.00	-0.00	0.01	0.01	0.026	0.01	-0.00	0.01	0.00	0.02	0.02	0.042	0.01	0.025	0.028	0.00	-	-	-	-0.00	0.00	0.041	0.01	-0.02	0.01	0.027	0.01	0.033	-	0.029	-0.03	-	0.00	0.00
DTU-AADLeft/Right Attention DecodingWS	0.01	0.00	0.187	0.01	0.01	0.01	0.13	0.08	0.03	0.00	0.08	0.04	0.02	0.01	0.02	-0.00	0.01	0.351	0.332	0.06	0.263	0.225	0.216	0.1610	0.01	0.00	-	-	-	0.00	0.02	0.05	0.169	0.254	0.00	0.14	0.12	0.00	-	0.08	0.11	-	0.178	0.01
DTU-AADLeft/Right Attention DecodingCS	-0.04	0.00	0.00	0.01	-0.01	-0.01	-0.02	0.01	0.029	-0.00	-0.00	-0.02	0.01	0.043	0.026	0.00	0.01	-0.02	0.00	-0.02	0.028	-0.01	-0.02	-0.02	-0.00	0.00	-	-	-	-0.01	0.027	-0.00	0.051	-0.06	-	0.025	-0.03	0.00	-	-0.01	0.034	-	0.042	0.0110
BCIC-IV-2BLeft/Right Hand MIWS	0.02	0.41	0.29	0.44	0.19	0.36	0.473	0.42	0.4410	0.42	0.482	0.25	0.26	0.00	0.40	0.458	0.04	0.33	0.26	0.457	0.05	0.21	-	0.40	-0.00	0.00	-	-	-	0.474	0.466	0.459	0.44	0.00	0.43	-	0.41	-	-	-	0.14	0.00	0.521	0.475
BCIC-IV-2BLeft/Right Hand MICS	0.01	0.406	0.22	0.408	0.27	0.37	0.36	0.38	0.399	0.37	0.422	0.20	0.23	0.03	0.37	0.431	-0.02	0.29	0.15	0.404	0.06	0.10	-	0.35	0.03	0.05	-	-	-	0.38	0.38	0.33	0.35	0.00	0.405	0.16	0.3810	-	0.00	0.00	-	0.00	0.413	0.407
Large-MILeft/Right/Hand/LegWS	0.18	0.57	0.57	0.56	0.32	0.52	0.617	0.54	0.57	0.46	0.5910	0.27	0.46	0.00	0.50	0.49	0.16	0.643	0.625	0.634	0.44	0.38	0.36	0.616	0.05	0.19	-	-	-	0.00	0.22	0.50	0.52	0.31	0.52	-	0.58	0.608	-	0.33	0.37	0.672	0.771	0.599
Large-MILeft/Right/Hand/LegCS	0.18	0.37	0.38	0.45	0.31	0.46	0.48	0.38	0.558	0.46	0.46	0.22	0.37	0.00	0.539	0.39	0.13	0.613	0.557	0.604	0.38	0.44	0.33	0.44	0.07	0.00	-	-	-	0.00	0.19	0.4910	0.48	0.25	0.576	-	0.48	-	0.605	-	-	0.721	0.652	0.46
Large-MILeft/Right + PassiveWS	0.04	0.55	0.50	0.55	0.39	0.35	0.54	0.53	0.55	0.41	0.588	0.04	0.46	0.01	0.48	0.48	0.11	0.624	0.633	0.5610	0.43	0.48	0.31	0.616	0.04	-0.00	-	-	-	0.00	0.10	0.44	0.47	0.33	0.40	-	0.615	0.589	-	0.39	0.43	0.652	0.741	0.587
Large-MILeft/Right + PassiveCS	0.09	0.45	0.34	0.43	0.45	0.44	0.506	0.45	0.45	0.42	0.43	0.02	0.4810	0.08	0.45	0.45	0.15	0.507	0.47	0.592	0.36	0.44	0.26	0.498	0.11	0.32	-	-	-	0.00	0.09	0.46	0.543	0.499	0.524	-	0.515	-	-	-	-	0.681	0.45	0.45
Large-MILeft/Right Hand MIWS	0.03	0.60	0.49	0.6110	0.43	0.55	0.646	0.56	0.639	0.56	0.647	0.00	0.47	-0.00	0.50	0.58	0.10	0.638	0.644	0.663	0.53	0.59	0.35	0.645	0.01	0.59	-	-	-	0.00	0.00	0.13	0.38	0.44	0.49	-	0.56	0.60	0.45	0.43	-	0.692	0.721	0.60
Large-MILeft/Right Hand MICS	0.06	0.695	0.36	0.65	0.46	0.694	0.55	0.50	0.687	0.678	0.6710	0.24	0.54	-	0.712	0.62	0.24	0.731	0.61	0.62	0.52	0.703	0.51	0.54	-0.01	0.00	-	-	-	0.00	0.00	0.46	0.47	0.59	0.679	-	0.62	-	-	-	0.44	0.686	0.55	0.53
Large-MIHand vs Leg MIWS	0.04	0.54	0.5610	0.51	0.38	0.45	0.55	0.49	0.52	0.38	0.605	0.06	0.43	0.07	0.47	0.45	0.14	0.633	0.606	0.604	0.45	0.39	0.42	0.597	0.06	0.00	-	-	-	0.00	0.16	0.51	0.578	0.31	0.51	-	0.54	-	-	-	-	0.682	0.741	0.569
Large-MIHand vs Leg MICS	0.00	0.514	0.35	0.40	0.33	0.31	0.459	0.36	0.477	0.30	0.37	0.03	0.30	0.06	0.38	0.35	0.09	0.485	0.41	0.476	0.37	0.36	0.33	0.44	0.07	0.40	-	-	-	0.00	0.25	0.26	0.39	0.28	0.533	-	0.4410	0.478	-	-	-	0.711	0.562	0.34
Large-MIIndividual FingersWS	0.01	0.2510	0.25	0.24	0.14	0.22	0.277	0.23	0.22	0.22	0.295	0.05	0.16	0.00	0.19	0.21	0.01	0.286	0.278	0.332	0.16	0.12	0.11	0.21	0.02	0.00	-	-	-	0.00	0.01	0.15	0.18	0.02	0.22	-	0.269	0.22	-	-	-	0.313	0.401	0.314
Large-MIIndividual FingersCS	0.03	0.15	0.09	0.14	0.09	0.169	0.15	0.14	0.1510	0.175	0.168	0.04	0.10	-0.00	0.12	0.177	0.01	0.09	0.12	0.214	0.08	0.06	0.04	0.13	0.02	-0.01	-	-	-	0.00	0.00	0.05	0.07	0.06	0.212	-	-	-	-	-	-	0.213	0.211	0.176
Large-MILeft/Right/Hand/Leg/TongueWS	0.08	0.54	0.55	0.53	0.31	0.48	0.5610	0.49	0.52	0.42	0.578	0.28	0.43	0.00	0.46	0.48	0.13	0.613	0.587	0.594	0.42	0.32	0.34	0.586	0.03	0.15	-	-	-	0.00	0.14	0.46	0.50	0.21	0.51	-	0.579	-	-	-	-	0.642	0.751	0.595
Large-MILeft/Right/Hand/Leg/TongueCS	0.09	0.40	0.41	0.44	0.38	0.45	0.4610	0.38	0.498	0.38	0.536	0.29	0.33	0.00	0.38	0.37	0.15	0.582	0.517	0.573	0.37	0.31	0.29	0.44	0.04	0.13	-	-	-	0.00	0.09	0.479	0.45	0.28	0.545	-	0.45	-	-	-	-	0.651	0.554	0.40
Large-MIWith RestWS	0.13	-	0.514	0.41	0.28	0.32	0.439	0.35	0.37	0.27	0.40	0.29	0.39	0.01	0.30	0.35	0.23	0.39	0.486	0.448	0.40	0.35	0.38	0.467	0.03	0.06	-	-	-	0.00	0.07	0.00	0.40	0.28	0.495	-	0.523	0.542	0.4310	-	-	0.571	-	-
Large-MIWith RestCS	0.22	-	0.31	0.29	0.29	0.28	0.329	0.27	0.328	0.20	0.30	0.29	0.357	0.00	0.29	0.28	0.25	0.27	0.3210	0.433	0.23	0.27	0.27	0.375	0.06	0.02	-	-	-	0.00	0.05	0.00	0.394	0.23	0.511	-	0.376	-	-	-	-	0.512	-	-
PhysioNet-MILeft/Right/Both Hands/FeetWS	0.05	0.447	0.34	0.439	0.28	0.37	0.40	0.42	0.39	0.38	0.474	0.14	0.33	-0.01	0.35	0.39	0.05	0.34	0.38	0.4210	0.33	0.29	0.26	0.438	0.04	0.28	-	-	-	0.483	0.482	0.491	0.41	0.27	0.00	0.455	0.41	-	0.00	0.00	0.30	0.00	0.456	0.42
PhysioNet-MILeft/Right/Both Hands/FeetCS	0.05	0.359	0.29	0.34	0.24	0.30	0.34	0.33	0.33	0.34	0.375	0.14	0.27	0.00	0.30	0.32	0.10	0.29	0.31	0.367	0.25	0.24	0.21	0.393	0.02	0.22	-	-	-	0.411	0.394	0.402	0.358	0.28	0.33	-	0.32	0.3410	-	-	0.28	0.00	0.27	0.366
PhysioNet-MILeft/Right Hand MIWS	0.03	0.57	0.48	0.619	0.39	0.50	0.48	0.54	0.58	0.55	0.5910	0.26	0.45	0.02	0.48	0.53	0.08	0.49	0.51	0.52	0.46	0.39	0.37	0.661	0.05	0.50	-	-	-	0.652	0.654	0.655	0.59	0.47	0.52	0.653	0.618	-	0.00	0.00	0.53	0.00	0.656	0.627
PhysioNet-MILeft/Right Hand MICS	0.05	0.5110	0.44	0.50	0.41	0.48	0.42	0.50	0.49	0.544	0.537	0.21	0.45	0.00	0.44	0.49	0.13	0.44	0.48	0.49	0.41	0.38	0.32	0.562	-0.03	0.47	-	-	-	0.621	0.535	0.536	-	0.27	-	-	0.42	-	-	-	0.528	0.00	0.553	0.519
PhysioNet-MIHand vs Feet MIWS	0.00	0.30	0.30	0.17	0.00	0.32	0.32	0.356	0.24	0.14	0.347	0.03	0.13	-	0.06	0.00	0.00	0.339	0.32	0.28	0.24	0.11	0.19	0.395	0.00	0.338	-	-	-	0.451	0.413	0.432	0.32	0.18	0.31	-	0.32	-	-	0.00	0.26	0.00	0.3210	0.404
PhysioNet-MIHand vs Feet MICS	0.00	0.28	0.24	0.15	0.00	0.27	0.309	0.27	0.28	0.11	0.337	-0.02	0.12	-	0.12	0.00	0.00	0.318	0.24	0.25	0.17	-0.00	0.12	0.346	0.00	0.25	-	-	-	0.402	0.365	0.374	0.29	0.11	0.2910	-	0.27	-	0.00	-	0.23	0.00	0.451	0.373
Stroke-MILeft/Right Hand MIWS	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.017	-	-	-	0.172	0.056	0.114	0.143	0.095	-0.01	-	0.008	-	0.009	-	-	0.0010	0.201	-0.01
Stroke-MILeft/Right Hand MICS	0.008	0.009	0.0010	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.006	-	-	-	0.111	-0.05	-0.00	0.015	0.072	-0.01	-	-	-	-	-	-	0.007	0.043	0.034
BCIC-IV-2ALeft/Right Hand MIWS	0.07	0.03	0.17	0.269	0.14	0.10	0.11	0.353	0.00	0.00	0.305	0.00	0.17	0.00	0.02	0.18	0.14	0.07	0.451	0.23	0.17	0.22	0.07	0.354	0.02	0.00	-	-	-	0.2410	0.298	0.296	-	0.297	-0.01	-	0.23	0.17	-	-	-	0.00	0.442	0.00
BCIC-IV-2ALeft/Right Hand MICS	0.10	0.315	0.06	0.443	0.2810	0.19	0.07	0.522	0.00	0.00	0.289	0.00	0.00	0.00	0.06	0.316	0.05	0.04	0.601	0.434	0.02	0.04	0.04	0.25	-0.01	0.00	-	-	-	0.03	-0.00	0.19	-	0.00	0.06	0.288	0.11	-	0.00	0.00	-	0.00	0.307	-0.07
BCIC-IV-2ALeft/Right/Hand/Foot/TongueWS	0.01	0.299	0.23	0.306	0.01	0.08	0.21	0.297	0.22	0.21	0.353	0.00	0.18	0.00	0.21	0.01	0.07	0.21	0.431	0.21	0.20	0.17	0.18	0.20	0.01	0.00	-	-	-	0.324	0.2810	0.298	-	0.17	0.11	0.305	0.25	-	-	-	-	0.00	0.412	0.23
BCIC-IV-2ALeft/Right/Hand/Foot/TongueCS	0.00	0.00	0.07	0.257	0.01	0.2010	0.19	0.265	0.20	0.228	0.331	-0.00	0.05	-0.00	0.01	0.01	0.04	0.02	0.322	0.229	0.02	0.02	0.16	0.10	0.00	0.00	-	-	-	0.283	0.20	0.19	-	0.00	0.08	-	0.19	0.18	-	-	0.256	0.00	0.274	0.16
BCIC-IV-2AHand vs Feet MIWS	0.01	0.24	0.18	0.364	0.00	0.02	0.18	0.23	0.03	-0.00	0.04	0.00	0.21	-	0.27	0.01	0.00	0.14	0.00	0.27	0.13	0.01	0.04	0.403	-0.01	0.00	-	-	-	0.402	0.356	0.347	0.3010	0.12	0.21	-	0.355	0.329	-	-	-	0.00	0.451	0.328
BCIC-IV-2AHand vs Feet MICS	0.06	0.13	0.15	0.2010	0.00	0.209	0.05	0.01	0.03	-	0.16	0.00	0.03	-	0.411	0.00	0.00	0.12	0.01	0.15	0.02	0.00	0.06	0.296	0.00	0.00	-	-	-	0.374	0.315	0.373	0.20	0.08	0.16	-	0.278	-	-	-	-	0.00	0.372	0.297
OpenBMILeft/Right Hand MIWS	0.29	0.48	0.41	0.49	0.36	0.47	0.43	0.46	0.527	0.44	0.564	0.37	0.37	0.02	0.43	0.43	0.35	0.526	0.35	0.519	0.35	0.44	0.43	0.518	0.01	0.33	-	-	-	0.01	0.02	0.26	0.37	0.39	0.5010	0.652	0.44	0.45	-	-	0.50	0.643	0.751	0.555
OpenBMILeft/Right Hand MICS	0.28	0.4610	0.33	0.477	0.33	0.42	0.41	0.42	0.476	0.43	0.523	0.33	0.38	-0.02	0.43	0.40	0.32	0.478	0.32	0.485	0.31	0.33	0.34	0.524	0.00	0.00	-	-	-	-0.00	0.03	0.28	0.34	0.38	0.45	-	-	-	-	-	-	0.652	0.711	0.469
HGDLeft/Right/Hand/Foot/TongueWS	0.18	0.61	0.58	0.6510	0.48	0.61	0.60	0.658	0.60	0.52	0.735	0.32	0.51	0.00	0.59	0.49	0.31	0.762	0.659	0.59	0.48	0.54	0.56	0.58	0.06	0.28	-	-	-	0.753	0.744	0.697	0.56	0.44	0.40	0.726	0.62	-	0.00	-	0.60	0.00	0.831	0.56
HGDLeft/Right/Hand/Foot/TongueCS	0.19	0.635	0.45	0.636	0.52	0.56	0.48	0.692	0.51	0.598	0.607	0.17	0.45	0.02	0.56	0.55	0.26	0.52	0.42	0.57	0.32	0.48	0.22	0.47	0.06	0.32	-	-	-	0.589	0.644	0.643	0.53	0.32	0.39	-	-	0.5710	-	-	-	0.00	0.701	0.50
HGDLeft/Right Hand MIWS	0.01	0.545	0.33	0.518	0.21	0.519	0.49	0.546	0.49	0.48	0.642	0.22	0.26	-0.01	0.38	0.17	0.08	0.594	0.46	0.44	0.34	0.42	0.33	0.26	-0.03	0.00	-	-	-	0.613	0.527	0.5010	0.42	0.22	0.15	-	0.40	-	-	0.00	-	0.00	0.751	0.40
HGDLeft/Right Hand MICS	0.00	0.546	0.10	0.519	0.17	0.564	0.36	0.592	0.583	0.527	0.47	0.13	0.17	0.00	0.36	0.22	0.14	0.33	0.26	0.518	0.18	0.19	0.10	0.25	0.03	0.00	-	-	-	0.545	0.48	0.4910	0.36	0.07	0.00	-	-	0.32	-	-	-	0.00	0.611	0.34
HGDHand vs Feet MIWS	0.48	0.84	0.877	0.84	0.79	0.77	0.82	0.78	0.869	0.71	0.914	0.61	0.79	-	0.868	0.78	0.52	0.932	0.8610	0.74	0.74	0.80	0.82	0.80	0.00	0.61	-	-	-	0.913	0.905	0.79	0.77	0.71	0.81	-	-	0.886	-	-	0.76	0.00	0.951	0.72
HGDHand vs Feet MICS	0.37	0.802	0.70	0.75	0.50	0.54	0.72	0.795	0.63	0.777	0.7710	0.51	0.68	-	0.779	0.48	0.32	0.62	0.55	0.70	0.47	0.57	0.29	0.62	0.00	0.42	-	-	-	0.778	0.803	0.796	0.72	0.43	0.72	-	0.794	-	-	-	-	0.00	0.911	0.72
Meng2019Cursor Movement DetectionWS	0.49	0.67	0.714	0.67	0.61	0.17	0.688	0.65	0.679	0.60	0.723	0.60	0.63	0.35	0.64	0.64	0.52	0.715	0.66	0.65	0.60	0.62	0.65	0.6710	0.33	0.29	-	-	-	0.58	0.32	0.36	0.64	0.53	0.58	0.697	0.706	-	-	-	-	0.791	0.752	0.62
Meng2019Cursor Movement DetectionCS	0.38	0.46	0.45	0.469	0.42	0.17	0.43	0.40	0.44	0.43	0.495	0.42	0.46	0.30	0.44	0.4610	0.40	0.486	0.41	0.478	0.39	0.40	0.42	0.477	0.25	0.31	-	-	-	0.42	0.19	0.25	0.39	0.45	0.45	-	-	0.523	-	-	0.42	0.601	0.592	0.514
Meng2019Cursor ControlWS	0.28	0.43	0.45	0.39	0.37	0.39	0.45	0.46	0.39	0.35	0.4710	0.40	0.37	-0.01	0.41	0.36	0.33	0.487	0.494	0.40	0.45	0.488	0.45	0.486	0.01	0.23	-	-	-	0.03	0.13	0.22	0.32	0.37	0.40	-	0.485	-	-	-	0.513	0.522	0.611	0.479
Meng2019Cursor ControlCS	-0.03	0.07	0.02	0.04	-0.08	-0.03	0.11	-0.04	0.07	0.02	0.177	-0.04	0.11	-0.01	0.08	-0.06	-0.03	0.224	0.11	0.08	0.11	0.11	0.11	0.225	-0.00	0.186	-	-	-	0.04	0.1710	0.12	0.178	0.179	0.02	-	-	0.17	-	-	-	0.362	0.411	0.273
Meng2019Cursor Control + RestWS	0.25	0.52	0.604	0.52	0.49	0.27	0.586	0.52	0.53	0.48	0.577	0.50	0.50	0.20	0.50	0.50	0.43	0.603	0.568	0.53	0.50	0.52	0.53	0.569	0.16	0.14	-	-	-	0.02	0.21	0.30	0.50	0.36	0.43	-	0.585	-	-	-	0.49	0.662	0.711	0.5310
Meng2019Cursor Control + RestCS	0.17	0.29	0.27	0.27	0.28	0.12	0.318	0.26	0.26	0.25	0.3010	0.27	0.319	0.15	0.27	0.27	0.22	0.354	0.23	0.317	0.24	0.20	0.26	0.316	0.13	0.12	-	-	-	0.00	0.15	0.20	0.27	0.24	0.27	-	0.335	-	-	-	-	0.432	0.501	0.403
UCDDB-SleepSleep Staging 30s 5-classWS	0.34	0.62	0.44	0.57	0.57	0.16	0.64	0.49	0.60	0.56	0.678	0.51	0.57	0.00	0.64	0.55	0.54	0.64	0.701	0.30	0.64	0.52	0.60	0.677	0.41	-	-	0.694	0.692	0.6610	0.62	0.669	0.64	-	-	-	0.675	0.676	-	-	-	-	0.693	0.50
UCDDB-SleepSleep Staging 30s 5-classCS	0.38	0.6510	0.41	0.59	0.57	0.09	0.64	0.45	0.59	0.57	0.63	0.51	0.57	0.00	0.63	0.55	0.56	0.60	0.686	0.29	0.669	0.53	0.59	0.701	0.39	-	-	0.684	0.683	0.65	0.54	0.59	0.685	-	-	-	0.692	0.677	-	-	-	-	0.678	0.48
UCDDB-SleepSleep Staging 30s 6-classWS	0.24	0.60	0.43	0.55	0.56	0.16	0.64	0.47	0.59	0.54	0.658	0.50	0.55	0.00	0.62	0.54	0.54	0.62	0.691	0.32	0.62	0.51	0.56	0.657	0.42	-	-	0.673	0.674	0.6410	0.59	0.649	0.64	-	-	-	0.675	0.656	-	-	-	-	0.672	0.49
UCDDB-SleepSleep Staging 30s 6-classCS	0.31	0.6210	0.40	0.57	0.57	0.10	0.59	0.43	0.55	0.53	0.61	0.50	0.55	0.00	0.61	0.55	0.55	0.57	0.672	0.30	0.649	0.52	0.54	0.664	0.41	-	-	0.671	0.663	0.61	0.54	0.01	0.657	-	-	-	0.658	0.666	-	-	-	-	0.665	0.49
UCDDB-SleepSleep/Wake 30sWS	0.45	0.74	0.44	0.74	0.72	0.49	0.64	0.67	0.71	0.70	0.766	0.13	0.73	-	0.74	0.70	0.74	0.75	0.773	0.49	0.75	0.74	0.74	0.767	0.28	-	-	0.781	0.782	0.775	0.768	0.74	0.7610	-	-	-	0.75	0.769	-	-	-	-	0.774	0.65
UCDDB-SleepSleep/Wake 30sCS	0.33	0.72	0.33	0.748	0.71	0.34	0.43	0.56	0.58	0.67	0.73	0.26	0.72	-	0.73	0.71	0.72	0.73	0.764	0.54	0.7410	0.74	0.73	0.73	0.26	-	-	0.755	0.757	0.761	0.72	0.749	0.756	-	-	-	0.73	0.762	-	-	-	-	0.763	0.68
UCDDB-SleepWake/NREM/REM 30sWS	0.35	0.74	0.51	0.67	0.72	0.23	0.72	0.65	0.73	0.68	0.765	0.02	0.68	-	0.73	0.68	0.72	0.73	0.781	0.50	0.72	0.69	0.749	0.73	0.38	-	-	0.773	0.782	0.758	0.7410	0.73	0.74	-	-	-	0.766	0.757	-	-	-	-	0.774	0.64
UCDDB-SleepWake/NREM/REM 30sCS	0.31	0.72	0.48	0.70	0.72	0.15	0.64	0.58	0.72	0.64	0.753	0.29	0.70	-	0.72	0.68	0.7310	0.72	0.771	0.57	0.746	0.70	0.747	0.739	0.40	-	-	0.755	0.754	0.71	0.68	0.72	0.748	-	-	-	0.73	0.73	-	-	-	-	0.762	0.68
HMC-SleepSleep/Wake 30sWS	0.36	0.847	0.58	0.82	0.81	0.67	0.69	0.76	0.83	0.75	0.83	0.80	0.80	0.00	0.83	0.77	0.77	0.848	0.862	0.73	0.849	0.80	0.82	0.856	0.58	-	-	-	-	0.861	0.853	0.83	0.79	-	-	-	0.8310	0.855	-	-	-	-	0.854	0.75
HMC-SleepSleep/Wake 30sCS	0.19	0.68	0.49	0.60	0.63	0.46	0.44	0.62	0.737	0.63	0.745	0.67	0.719	0.00	0.69	0.62	0.59	0.69	0.64	0.62	0.69	0.58	0.70	0.718	0.58	-	-	-	-	0.771	0.763	0.762	0.754	-	-	-	0.7010	0.69	-	-	-	-	0.736	0.67
HMC-SleepWake/NREM/REM 30sWS	0.22	0.767	0.49	0.74	0.71	0.74	0.74	0.68	0.69	0.55	0.74	0.66	0.67	0.00	0.75	0.64	0.68	0.769	0.812	0.63	0.786	0.69	0.71	0.804	0.38	-	-	-	-	0.821	0.813	0.768	0.67	-	-	-	0.7610	0.73	-	-	-	-	0.785	0.62
HMC-SleepWake/NREM/REM 30sCS	0.24	0.64	0.38	0.59	0.57	0.52	0.61	0.51	0.59	0.53	0.665	0.54	0.657	0.05	0.658	0.55	0.57	0.61	0.649	0.55	0.682	0.58	0.62	0.664	0.43	-	-	-	-	0.701	0.673	0.666	0.60	-	-	-	0.6410	0.61	-	-	-	-	0.63	0.56
MigraineDBSSAEP Frequency DiscriminationWS	0.01	0.00	-0.02	0.037	-0.00	-0.00	0.03	0.00	-0.01	0.01	-0.00	0.00	0.01	-0.04	-0.00	0.0310	0.01	-0.01	0.038	0.064	0.039	0.02	-0.02	0.01	0.01	0.00	-	-	-	0.281	0.01	0.112	0.055	-0.00	0.056	0.02	-0.01	-	-	-	-	0.00	-0.01	0.093
MigraineDBSSAEP Frequency DiscriminationCS	0.01	-0.02	-0.02	-0.03	0.039	-0.00	0.02	0.038	0.01	-0.01	0.01	0.00	-0.02	0.00	0.047	0.01	-0.02	0.0210	-0.00	0.00	0.02	0.00	-0.00	-0.01	-0.06	0.00	-	-	-	0.311	-0.00	0.282	0.066	0.00	0.095	-	-	-	-	-	-0.02	0.00	0.143	0.094
MigraineDBSSVEP Frequency DiscriminationWS	-0.02	0.24	0.02	0.33	-0.01	-0.02	0.588	0.00	0.23	0.02	0.41	0.00	0.09	0.02	0.05	0.00	0.01	0.13	-0.01	0.589	-0.06	0.04	-0.02	0.617	-0.02	0.00	-	-	-	0.773	0.675	0.792	0.5310	0.00	0.656	-	-0.01	-	-	-	-	0.00	0.791	0.684
MigraineDBSSVEP Frequency DiscriminationCS	-0.01	0.26	-0.00	0.38	0.02	-0.00	0.578	-0.05	0.26	0.10	0.39	0.00	0.09	-0.00	0.16	0.00	-0.00	0.12	-0.02	0.617	0.03	0.03	0.04	0.519	-0.01	0.00	-	-	-	0.801	0.703	0.782	0.4510	0.00	0.666	-	-	-	0.00	-	-	0.00	0.704	0.675
MigraineDB4-Hz SSVEP Migraine DetectionWS	0.05	-0.02	0.918	0.39	0.26	0.04	0.65	0.39	-0.04	0.00	0.76	0.20	0.39	0.00	0.45	0.05	0.14	0.8810	0.64	0.47	0.65	0.71	0.909	0.87	0.01	0.00	-	-	-	0.994	0.985	0.956	0.82	0.992	0.54	-	0.947	-	0.05	-	0.71	1.001	0.993	0.46
MigraineDB6-Hz SSVEP Migraine DetectionWS	0.14	0.19	0.86	0.34	0.20	0.31	0.70	0.41	0.05	0.00	0.73	0.12	0.43	0.00	0.41	0.01	-0.01	0.888	0.71	0.45	0.65	0.70	0.879	0.80	0.02	0.00	-	-	-	0.994	0.995	0.957	0.77	0.992	0.54	0.986	0.8610	-	-	-	0.73	1.001	0.993	0.49
MigraineDB4-Hz SSAEP Migraine DetectionWS	0.10	0.29	0.839	0.33	0.38	0.33	0.64	0.45	0.20	0.23	0.8210	0.00	0.51	0.00	0.40	0.22	0.20	0.78	0.63	0.45	0.60	0.63	0.848	0.71	-0.00	0.00	-	-	-	0.994	0.985	0.887	0.79	1.001	0.73	-	0.936	-	-	0.01	0.67	1.002	1.003	0.57
MigraineDBResting Migraine DetectionWS	0.41	0.70	0.97	0.84	0.89	0.03	0.91	0.72	0.76	0.50	0.97	0.66	0.90	0.00	0.92	0.79	0.52	0.998	0.92	0.71	0.93	0.96	1.004	0.997	0.22	0.00	-	-	-	1.001	0.9910	0.999	0.91	1.002	-	-	0.996	1.005	-	0.00	-	1.003	-	0.40
MigraineDB6-Hz SSAEP Migraine DetectionWS	0.09	0.30	0.818	0.33	0.36	0.33	0.62	0.47	0.24	0.00	0.809	0.15	0.49	0.00	0.44	0.01	0.25	0.79	0.63	0.48	0.64	0.70	0.8010	0.76	0.03	0.00	-	-	-	0.995	0.994	0.896	0.79	1.003	0.70	-	0.877	-	-	-	-	1.001	1.002	0.58
MigraineDBSSVEP Migraine DetectionWS	0.11	0.50	0.989	0.72	0.72	0.89	0.82	0.67	0.70	0.34	0.92	0.45	0.87	-	0.84	0.61	0.51	0.9710	0.79	0.63	0.83	0.93	0.997	0.95	0.02	0.00	-	-	-	1.003	0.996	0.998	0.91	1.001	0.69	1.005	-	-	-	0.01	-	1.004	1.002	0.68
MigraineDBSSAEP Migraine DetectionWS	0.07	0.72	0.91	0.76	0.76	0.56	0.74	0.55	0.58	0.46	0.9210	0.38	0.87	-	0.79	0.64	0.63	0.929	0.75	0.64	0.77	0.88	0.987	0.978	0.09	0.00	-	-	-	1.002	0.995	0.996	0.90	1.004	0.90	-	-	-	0.00	-	-	1.001	1.003	0.73
BCIC-IV-1Left/Right Hand MIWS	-0.06	-0.01	-0.02	-0.01	0.02	-0.02	0.00	0.063	0.00	0.049	-0.01	0.00	-0.00	0.00	0.00	0.00	0.057	0.00	-0.01	0.072	0.055	0.00	-0.00	0.01	-0.02	0.03	-	-	-	0.091	-0.03	-0.03	-	-0.03	-0.02	-	0.054	-	0.0410	-	-	0.048	-0.02	0.056
BCIC-IV-1Left/Right Hand MICS	-0.17	0.049	0.095	0.00	-0.05	0.01	0.00	0.066	0.00	0.113	0.00	0.00	0.058	0.00	0.122	-0.09	-0.01	-0.03	0.00	0.0410	0.104	0.00	0.02	-0.05	0.01	-0.05	-	-	-	0.02	-0.05	0.00	-0.03	-0.06	0.00	-	0.00	-	-	-	-	0.131	0.01	0.057
BCIC-IV-1Left Hand vs Foot MIWS	-0.20	0.00	0.184	0.00	-0.07	0.00	-0.02	-0.02	0.00	-0.05	0.00	0.00	0.03	0.00	0.03	-0.15	-0.10	0.00	-0.05	0.203	0.079	-0.07	0.157	0.00	-0.02	0.301	-	-	-	0.00	0.0510	0.155	-	0.05	0.03	0.302	0.156	-	-	0.138	-	0.03	0.05	0.03

Macro F1

Dataset · task · split	Baseline Models																									Foundation Models
Dataset · task · split	ADFCNN	ATCNet	BiDANN	CTNet	DBConformer	DeepConvNet	DeepSleepNet	EEGConformer	EEGInceptionERP	EEGNet	EEGNeX	EEGWaveNet	FBCNet	HSLT	IFNet	MSCFormer	MSVTNet	ShallowConvNet	SleepEEGNet	SleepTransformer	SlimSeiz	TMSA-Net	TSception	U-Sleep	YASA	BENDR	BIOT · Prest 16ch	BIOT · Shhs Prest 18ch	BIOT · Six Datasets 18ch	CBraMod	CodeBrain	CSBrain	EEGMamba	EEGPT	LaBraM	LEAD	LUNA · Base	LUNA · Large	mdJPT	MIRepNet	NeuroGPT	NeuroRVQ	REVE · Base	REVE · Large
EEGMatMental Arithmetic vs RestWS	0.46	0.63	0.58	0.50	0.43	0.58	0.869	0.82	0.50	0.49	0.63	0.30	0.51	0.43	0.54	0.43	0.43	0.914	0.923	0.56	0.43	0.57	0.68	0.867	0.48	0.868	-	-	-	0.8510	0.906	0.905	0.64	0.70	0.70	0.951	0.75	0.77	0.43	0.43	0.84	0.43	0.932	0.54
EEGMatMental Arithmetic vs RestCS	0.44	0.48	0.55	0.45	0.43	0.43	0.62	0.63	0.47	0.48	0.52	0.25	0.44	0.43	0.45	0.43	0.43	0.724	0.6610	0.47	0.705	0.47	0.62	0.698	0.43	0.697	-	-	-	0.752	0.723	0.66	0.66	0.66	0.62	0.811	0.669	0.61	0.43	0.43	0.706	0.43	0.64	0.55
TUEVEpileptiform EventsWS	0.48	0.61	0.7610	0.63	0.62	0.23	0.62	0.64	0.64	0.52	0.70	0.49	0.63	0.12	0.64	0.60	0.50	0.74	0.71	0.59	0.70	0.65	0.66	0.838	0.41	0.68	-	-	-	0.881	0.872	0.865	0.73	0.837	0.69	0.873	0.864	0.819	0.14	0.15	0.66	0.15	0.846	0.65
TUEVEpileptiform EventsCS	0.27	0.483	0.26	0.454	0.36	0.24	0.29	0.31	0.389	0.22	0.436	0.13	0.407	0.00	0.502	0.3810	0.34	0.455	0.33	0.29	0.36	0.501	0.37	0.37	0.23	0.26	-	-	-	0.29	0.26	0.26	0.32	0.31	0.34	0.33	0.32	0.31	0.00	0.24	0.27	0.24	0.27	0.408
TUEVEpileptiform Event DetectionWS	0.62	0.89	0.94	0.90	0.90	0.29	0.86	0.92	0.90	0.81	0.92	0.88	0.91	-	0.91	0.89	0.84	0.976	0.9610	0.87	0.95	0.91	0.92	0.975	0.79	0.92	-	-	-	0.977	0.973	0.981	0.95	0.972	0.95	0.974	0.969	0.95	0.37	0.37	0.94	0.29	0.968	0.86
TUEVEpileptiform Event DetectionCS	0.09	0.841	0.69	0.786	0.7610	0.49	0.75	0.66	0.49	0.31	0.769	0.73	0.65	-	0.54	0.72	0.787	0.75	0.71	0.59	0.778	0.832	0.795	0.823	0.54	0.65	-	-	-	0.68	0.71	0.814	0.42	0.74	0.75	0.73	0.76	0.74	0.04	0.04	0.68	0.04	0.75	0.64
SHU-MILeft/Right Hand MIWS	0.59	0.65	0.75	0.64	0.62	0.64	0.81	0.65	0.68	0.62	0.70	0.68	0.64	0.50	0.64	0.63	0.57	0.76	0.82	0.84	0.72	0.66	0.70	0.858	0.49	0.50	-	-	-	0.865	0.866	0.857	0.8410	0.35	0.33	0.881	0.864	0.863	0.33	0.33	0.60	0.33	0.882	0.849
SHU-MILeft/Right Hand MICS	0.58	0.64	0.694	0.63	0.679	0.64	0.63	0.63	0.65	0.63	0.677	0.6510	0.678	0.50	0.64	0.65	0.59	0.63	0.65	0.65	0.64	0.64	0.693	0.64	0.53	0.34	-	-	-	0.65	0.65	0.63	0.64	0.56	0.33	0.722	0.685	0.686	0.34	0.34	0.57	0.34	0.721	0.65
TUSLBackground Slowing DetectionWS	0.34	0.45	0.77	0.62	0.63	0.61	0.54	0.62	0.34	0.42	0.40	0.34	0.34	0.34	0.62	0.49	0.43	0.72	0.60	0.43	0.72	0.59	0.34	0.876	0.63	0.62	-	-	-	0.8010	0.874	0.857	0.838	0.79	0.77	0.875	0.902	0.893	0.33	0.33	0.819	0.34	0.921	0.60
TUSLBackground Slowing DetectionCS	0.34	0.44	0.62	0.42	0.34	0.61	0.47	0.44	0.37	0.42	0.36	0.34	0.34	0.34	0.52	0.36	0.39	0.48	0.34	0.53	0.57	0.55	0.34	0.688	0.52	0.42	-	-	-	0.763	0.734	0.62	0.6210	0.54	0.735	0.771	0.639	0.54	0.33	0.33	0.726	0.33	0.772	0.697
TUSLSlowing + SeizureWS	0.32	0.43	0.67	0.27	0.23	0.31	0.60	0.32	0.36	0.26	0.54	0.16	0.45	0.16	0.47	0.35	0.48	0.66	0.60	0.42	0.52	0.56	0.36	0.769	0.28	0.46	-	-	-	0.806	0.852	0.844	0.7110	0.67	0.778	0.843	0.825	0.797	0.18	0.16	0.50	0.16	0.891	0.44
TUSLSlowing + SeizureCS	0.31	0.32	0.16	0.20	0.12	0.23	0.19	0.16	0.20	0.19	0.27	0.12	0.25	0.12	0.30	0.14	0.21	0.31	0.31	0.13	0.27	0.30	0.17	0.26	0.349	0.3310	-	-	-	0.562	0.701	0.534	0.29	0.446	0.553	0.535	0.378	0.28	0.17	0.12	0.27	0.12	0.437	0.32
Kaggle-INRIAP300 Feedback CorrectnessWS	0.51	-	0.637	0.61	0.41	0.56	0.6110	0.61	0.629	0.54	0.645	0.41	0.55	0.29	0.50	0.41	0.52	0.59	0.638	0.646	0.50	0.47	0.59	0.59	0.41	0.41	-	-	-	0.50	0.41	0.60	0.56	0.54	0.57	0.61	0.60	0.59	0.57	0.49	0.672	0.654	0.691	0.663
Kaggle-INRIAP300 Feedback CorrectnessCS	0.46	-	0.6010	0.58	0.46	0.58	0.58	0.59	0.634	0.59	0.635	0.46	0.60	0.13	0.50	0.46	0.50	0.49	0.57	0.633	0.46	0.48	0.51	0.59	0.46	0.608	-	-	-	0.24	0.46	0.50	0.58	0.48	0.617	0.56	0.54	0.55	0.46	0.52	0.609	0.661	0.642	0.626
ERP-BCIP300 Target DetectionWS	0.34	-	0.61	0.62	0.45	0.45	0.64	0.45	0.687	0.21	0.6510	0.15	0.56	0.45	0.24	0.45	0.45	0.23	0.54	0.735	0.45	0.45	0.24	0.744	0.45	0.54	-	-	-	0.781	0.743	0.772	-	0.678	0.706	0.63	0.659	0.45	0.45	0.15	0.45	0.45	-	-
ERP-BCIP300 Target DetectionCS	0.45	-	0.61	0.64	0.45	0.45	0.65	0.45	0.689	0.23	0.6710	0.15	0.57	0.45	0.23	0.45	0.45	0.23	0.57	0.734	0.46	0.46	0.24	0.726	0.45	0.45	-	-	-	0.781	0.725	0.762	0.733	0.45	0.707	0.66	0.688	0.67	0.45	0.15	0.45	0.45	-	-
SEEDEmotion RecognitionWS	0.35	0.65	0.748	0.66	0.66	0.49	0.63	0.65	0.66	0.58	0.719	0.66	0.68	0.30	0.67	0.63	0.59	0.804	0.69	0.50	0.68	0.7110	0.795	0.69	0.46	0.34	-	-	-	0.23	0.65	0.59	0.872	0.52	0.69	0.786	0.787	0.833	0.65	0.56	0.61	-	0.891	0.61
SEEDEmotion RecognitionCS	0.37	0.49	0.49	0.46	0.518	0.37	0.48	0.49	0.45	0.45	0.48	0.48	0.51	0.29	0.47	0.525	0.45	0.524	0.572	0.42	0.517	0.516	0.45	0.5110	0.44	0.17	-	-	-	0.44	0.43	0.39	0.50	0.47	0.44	0.47	0.533	0.48	0.519	0.33	0.46	-	0.581	0.18
FACEDEmotion RecognitionWS	0.07	0.3010	0.29	0.348	0.10	0.375	0.19	0.501	0.357	0.374	0.422	0.05	0.18	0.02	0.319	0.10	0.07	0.393	0.27	0.27	0.20	0.12	0.13	0.12	0.05	0.04	-	-	-	0.06	0.04	0.07	0.366	0.10	0.09	0.26	0.25	0.14	-	0.11	0.11	-	0.28	0.20
FACEDEmotion RecognitionCS	0.06	0.269	0.22	0.326	0.07	0.333	0.12	0.461	0.307	0.325	0.372	0.06	0.17	0.02	0.26	0.07	0.08	0.324	0.22	0.23	0.16	0.10	0.12	0.12	0.05	0.05	-	-	-	0.08	0.08	0.07	0.298	0.09	0.07	0.22	0.25	0.2610	-	0.11	0.15	-	0.25	0.19
DTU-AADGender Attention DecodingWS	0.47	0.55	0.6910	0.54	0.60	0.62	0.59	0.58	0.59	0.46	0.59	0.64	0.59	0.36	0.56	0.51	0.43	0.743	0.734	0.60	0.709	0.68	0.707	0.63	0.38	0.31	-	-	-	0.02	0.55	0.23	0.708	0.901	0.54	0.725	0.67	0.716	-	0.57	0.57	-	0.782	0.55
DTU-AADGender Attention DecodingCS	0.40	0.40	0.44	0.41	0.37	0.37	0.4810	0.488	0.00	0.25	0.24	0.41	0.45	0.37	0.42	0.45	0.41	0.35	0.504	0.38	0.507	0.43	0.29	0.522	0.37	0.33	-	-	-	0.25	0.38	0.21	0.531	0.506	0.37	0.505	0.47	0.513	-	0.37	0.489	-	0.46	0.47
DTU-AADGender x Left/Right Attention DecodingWS	0.22	0.23	0.408	0.23	0.28	0.17	0.32	0.27	0.28	0.20	0.33	0.32	0.28	0.09	0.26	0.21	0.21	0.483	0.464	0.32	0.3910	0.417	0.409	0.35	0.13	0.11	-	-	-	0.11	0.16	0.25	0.426	0.512	-	0.435	0.34	0.37	-	0.29	0.29	-	0.531	0.29
DTU-AADGender x Left/Right Attention DecodingCS	0.22	0.23	0.21	0.20	0.19	0.17	0.257	0.23	0.261	0.18	0.15	0.11	0.2410	0.17	0.21	0.15	0.19	0.22	0.256	0.19	0.21	0.255	0.258	0.249	0.21	0.11	-	-	-	0.08	0.12	0.20	0.254	0.19	0.19	0.262	0.19	0.263	-	0.19	0.17	-	0.23	0.17
DTU-AADLeft/Right Attention DecodingWS	0.45	0.16	0.597	0.50	0.45	0.31	0.55	0.52	0.51	0.35	0.54	0.49	0.51	0.51	0.51	0.37	0.48	0.681	0.662	0.53	0.633	0.615	0.606	0.5710	0.50	0.34	-	-	-	0.34	0.41	0.35	0.589	0.624	0.34	0.57	0.56	0.34	-	0.53	0.55	-	0.588	0.50
DTU-AADLeft/Right Attention DecodingCS	0.43	0.18	0.508	0.4910	0.43	0.499	0.48	0.49	0.33	0.37	0.45	0.47	0.25	0.49	0.513	0.40	0.45	0.49	0.33	0.48	0.507	0.49	0.48	0.41	0.47	0.33	-	-	-	0.32	0.44	0.19	0.521	0.43	-	0.506	0.43	0.33	-	0.41	0.512	-	0.515	0.514
BCIC-IV-2BLeft/Right Hand MIWS	0.48	0.70	0.65	0.72	0.58	0.68	0.743	0.71	0.7210	0.71	0.742	0.62	0.63	0.34	0.70	0.729	0.52	0.66	0.63	0.728	0.52	0.60	-	0.70	0.33	0.33	-	-	-	0.734	0.735	0.727	0.72	0.33	0.71	-	0.70	-	-	-	0.57	0.33	0.761	0.736
BCIC-IV-2BLeft/Right Hand MICS	0.42	0.706	0.61	0.705	0.63	0.68	0.68	0.69	0.699	0.68	0.712	0.60	0.61	0.41	0.69	0.711	0.49	0.64	0.57	0.704	0.52	0.55	-	0.67	0.50	0.52	-	-	-	0.68	0.6910	0.66	0.67	0.33	0.707	0.58	0.69	-	0.33	0.33	-	0.33	0.703	0.698
Large-MILeft/Right/Hand/LegWS	0.34	0.68	0.68	0.67	0.48	0.64	0.717	0.65	0.67	0.60	0.6910	0.44	0.60	0.14	0.63	0.62	0.34	0.733	0.715	0.734	0.58	0.54	0.52	0.716	0.27	0.40	-	-	-	0.12	0.40	0.63	0.64	0.48	0.64	-	0.68	0.708	-	0.50	0.52	0.762	0.831	0.699
Large-MILeft/Right/Hand/LegCS	0.33	0.52	0.53	0.58	0.48	0.61	0.61	0.53	0.658	0.60	0.59	0.42	0.52	0.10	0.649	0.55	0.30	0.703	0.667	0.704	0.52	0.60	0.48	0.57	0.23	0.10	-	-	-	0.10	0.29	0.62	0.60	0.44	0.676	-	0.6210	-	0.695	-	-	0.791	0.742	0.59
Large-MILeft/Right + PassiveWS	0.22	0.70	0.67	0.70	0.60	0.42	0.69	0.69	0.70	0.60	0.729	0.26	0.64	0.23	0.65	0.65	0.41	0.754	0.753	0.7110	0.61	0.65	0.54	0.746	0.35	0.17	-	-	-	0.17	0.33	0.27	0.65	0.55	0.60	-	0.745	0.728	-	0.59	0.62	0.772	0.831	0.727
Large-MILeft/Right + PassiveCS	0.29	0.64	0.55	0.62	0.64	0.62	0.676	0.63	0.63	0.62	0.62	0.25	0.64	0.32	0.64	0.63	0.40	0.6410	0.659	0.722	0.55	0.63	0.48	0.667	0.40	0.56	-	-	-	0.17	0.28	0.64	0.703	0.668	0.684	-	0.675	-	-	-	-	0.791	0.63	0.64
Large-MILeft/Right Hand MIWS	0.21	0.80	0.75	0.8110	0.72	0.78	0.826	0.78	0.819	0.78	0.827	0.00	0.73	0.34	0.75	0.79	0.53	0.828	0.824	0.833	0.77	0.80	0.45	0.825	0.50	0.79	-	-	-	0.33	0.33	0.18	0.69	0.72	0.75	-	0.78	0.80	0.73	0.71	-	0.842	0.861	0.80
Large-MILeft/Right Hand MICS	0.24	0.845	0.68	0.82	0.72	0.854	0.77	0.75	0.846	0.848	0.849	0.59	0.77	-	0.852	0.81	0.61	0.871	0.80	0.80	0.75	0.853	0.75	0.77	0.49	0.33	-	-	-	0.34	0.33	0.73	0.73	0.79	0.8410	-	0.81	-	-	-	0.72	0.847	0.78	0.76
Large-MIHand vs Leg MIWS	0.26	0.77	0.7810	0.76	0.68	0.72	0.77	0.74	0.76	0.69	0.805	0.51	0.72	0.53	0.74	0.72	0.57	0.813	0.806	0.804	0.73	0.69	0.71	0.797	0.53	0.34	-	-	-	0.18	0.54	0.50	0.788	0.65	0.76	-	0.77	-	-	-	-	0.842	0.871	0.789
Large-MIHand vs Leg MICS	0.25	0.754	0.67	0.69	0.65	0.64	0.729	0.67	0.746	0.65	0.68	0.42	0.63	0.53	0.69	0.67	0.52	0.745	0.70	0.737	0.67	0.68	0.66	0.71	0.48	0.69	-	-	-	0.33	0.62	0.60	0.70	0.63	0.763	-	0.7110	0.738	-	-	-	0.861	0.782	0.64
Large-MIIndividual FingersWS	0.17	0.38	0.3910	0.36	0.25	0.34	0.416	0.37	0.34	0.34	0.407	0.18	0.31	0.07	0.33	0.34	0.14	0.425	0.409	0.462	0.30	0.26	0.25	0.35	0.13	0.07	-	-	-	0.07	0.13	0.31	0.33	0.17	0.37	-	0.408	0.34	-	-	-	0.453	0.521	0.434
Large-MIIndividual FingersCS	0.19	0.27	0.23	0.26	0.21	0.28	0.317	0.27	0.28	0.316	0.309	0.18	0.26	0.07	0.25	0.318	0.16	0.26	0.2910	0.353	0.25	0.21	0.20	0.26	0.12	0.10	-	-	-	0.07	0.07	0.19	0.20	0.24	0.361	-	-	-	-	-	-	0.354	0.362	0.335
Large-MILeft/Right/Hand/Leg/TongueWS	0.20	0.63	0.64	0.63	0.44	0.58	0.6510	0.59	0.62	0.54	0.668	0.42	0.55	0.07	0.57	0.59	0.28	0.683	0.667	0.674	0.54	0.45	0.46	0.676	0.17	0.29	-	-	-	0.06	0.31	0.57	0.60	0.36	0.61	-	0.669	-	-	-	-	0.712	0.801	0.675
Large-MILeft/Right/Hand/Leg/TongueCS	0.19	0.50	0.52	0.55	0.49	0.57	0.5710	0.50	0.589	0.51	0.626	0.43	0.46	0.07	0.51	0.50	0.28	0.662	0.617	0.653	0.48	0.44	0.42	0.56	0.15	0.22	-	-	-	0.07	0.21	0.588	0.56	0.42	0.635	-	0.57	-	-	-	-	0.721	0.644	0.52
Large-MIWith RestWS	0.16	-	0.524	0.43	0.32	0.34	0.468	0.37	0.39	0.29	0.41	0.30	0.42	0.05	0.35	0.37	0.24	0.41	0.506	0.469	0.44	0.37	0.39	0.477	0.09	0.06	-	-	-	0.03	0.10	0.03	0.44	0.32	0.515	-	0.553	0.562	0.4510	-	-	0.591	-	-
Large-MIWith RestCS	0.22	-	0.2510	0.24	0.259	0.24	0.24	0.23	0.24	0.18	0.258	0.24	0.267	0.08	0.23	0.22	0.21	0.22	0.24	0.295	0.20	0.23	0.24	0.276	0.12	0.07	-	-	-	0.05	0.10	0.05	0.294	0.21	0.322	-	0.323	-	-	-	-	0.331	-	-
PhysioNet-MILeft/Right/Both Hands/FeetWS	0.24	0.587	0.51	0.5710	0.45	0.53	0.56	0.56	0.54	0.53	0.604	0.33	0.50	0.16	0.51	0.54	0.28	0.51	0.54	0.57	0.50	0.47	0.44	0.588	0.24	0.45	-	-	-	0.613	0.612	0.621	0.56	0.46	0.11	0.596	0.56	-	0.10	0.10	0.47	0.10	0.595	0.579
PhysioNet-MILeft/Right/Both Hands/FeetCS	0.23	0.518	0.46	0.50	0.41	0.47	0.50	0.50	0.49	0.50	0.535	0.32	0.46	0.11	0.48	0.49	0.32	0.47	0.49	0.527	0.44	0.43	0.39	0.543	0.25	0.36	-	-	-	0.561	0.544	0.552	0.519	0.46	0.50	-	0.49	0.5110	-	-	0.46	0.10	0.45	0.526
PhysioNet-MILeft/Right Hand MIWS	0.41	0.78	0.74	0.809	0.69	0.75	0.74	0.77	0.79	0.78	0.7910	0.63	0.72	0.44	0.74	0.77	0.54	0.74	0.75	0.76	0.73	0.69	0.68	0.831	0.52	0.75	-	-	-	0.833	0.824	0.825	0.79	0.73	0.76	0.832	0.818	-	0.32	0.32	0.76	0.35	0.826	0.817
PhysioNet-MILeft/Right Hand MICS	0.42	0.7510	0.72	0.75	0.71	0.74	0.71	0.75	0.75	0.774	0.776	0.60	0.72	0.34	0.72	0.75	0.56	0.72	0.74	0.74	0.71	0.69	0.64	0.782	0.37	0.73	-	-	-	0.811	0.775	0.767	-	0.63	-	-	0.71	-	-	-	0.768	0.33	0.783	0.769
PhysioNet-MIHand vs Feet MIWS	0.44	0.65	0.65	0.57	0.42	0.668	0.66	0.676	0.60	0.27	0.6610	0.44	0.52	-	0.48	0.42	0.42	0.44	0.669	0.64	0.61	0.53	0.39	0.695	0.42	0.677	-	-	-	0.721	0.703	0.722	0.65	0.59	0.65	-	0.66	-	-	0.42	0.62	0.42	0.66	0.704
PhysioNet-MIHand vs Feet MICS	0.43	0.64	0.62	0.55	0.43	0.64	0.658	0.63	0.63	0.52	0.667	0.45	0.52	-	0.52	0.43	0.43	0.44	0.62	0.62	0.58	0.21	0.56	0.676	0.43	0.62	-	-	-	0.702	0.685	0.694	0.6410	0.55	0.649	-	0.63	-	0.43	-	0.62	0.43	0.721	0.693
Stroke-MILeft/Right Hand MIWS	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.34	0.369	-	-	-	0.582	0.526	0.554	0.573	0.545	0.438	-	0.33	-	0.3410	-	-	0.34	0.601	0.487
Stroke-MILeft/Right Hand MICS	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.339	-	-	-	0.551	0.476	0.418	0.427	0.532	0.494	-	-	-	-	-	-	0.3310	0.523	0.475
BCIC-IV-2ALeft/Right Hand MIWS	0.51	0.38	0.59	0.639	0.56	0.55	0.49	0.673	0.33	0.34	0.647	0.34	0.59	0.34	0.37	0.59	0.49	0.54	0.731	0.62	0.58	0.59	0.50	0.674	0.51	0.34	-	-	-	0.6210	0.648	0.655	-	0.656	0.45	-	0.61	0.59	-	-	-	0.33	0.722	0.34
BCIC-IV-2ALeft/Right Hand MICS	0.48	0.656	0.44	0.714	0.639	0.58	0.54	0.762	0.33	0.33	0.647	0.33	0.42	0.33	0.53	0.655	0.43	0.46	0.801	0.713	0.50	0.40	0.40	0.61	0.48	0.33	-	-	-	0.51	0.48	0.59	-	0.33	0.52	0.638	0.47	-	0.33	0.33	-	0.33	0.6310	0.43
BCIC-IV-2ALeft/Right/Hand/Foot/TongueWS	0.16	0.459	0.40	0.476	0.14	0.25	0.39	0.467	0.42	0.37	0.503	0.16	0.37	0.10	0.38	0.14	0.24	0.40	0.571	0.39	0.38	0.35	0.36	0.39	0.18	0.12	-	-	-	0.494	0.4510	0.468	-	0.35	0.27	0.475	0.42	-	-	-	-	0.12	0.562	0.41
BCIC-IV-2ALeft/Right/Hand/Foot/TongueCS	0.17	0.10	0.24	0.415	0.13	0.416	0.37	0.414	0.3910	0.34	0.492	0.11	0.25	0.11	0.16	0.12	0.19	0.24	0.491	0.408	0.17	0.13	0.29	0.30	0.10	0.10	-	-	-	0.463	0.38	0.39	-	0.10	0.30	-	0.36	0.34	-	-	0.399	0.10	0.417	0.37
BCIC-IV-2AHand vs Feet MIWS	0.50	0.41	0.58	0.675	0.40	0.42	0.56	0.59	0.18	0.05	0.32	0.40	0.58	-	0.62	0.17	0.40	0.36	0.26	0.63	0.54	0.26	0.22	0.703	0.46	0.40	-	-	-	0.702	0.676	0.677	0.6410	0.56	0.60	-	0.684	0.669	-	-	-	0.40	0.721	0.668
BCIC-IV-2AHand vs Feet MICS	0.51	0.54	0.53	0.6010	0.40	0.56	0.45	0.42	0.17	-	0.36	0.40	0.45	-	0.701	0.40	0.41	0.36	0.42	0.54	0.42	0.40	0.32	0.647	0.25	0.40	-	-	-	0.684	0.655	0.683	0.609	0.51	0.57	-	0.628	-	-	-	-	0.40	0.692	0.646
OpenBMILeft/Right Hand MIWS	0.64	0.74	0.71	0.75	0.68	0.73	0.72	0.73	0.767	0.72	0.784	0.69	0.68	0.51	0.72	0.71	0.68	0.766	0.67	0.759	0.67	0.72	0.72	0.768	0.38	0.66	-	-	-	0.42	0.50	0.61	0.69	0.70	0.7510	0.822	0.72	0.73	-	-	0.75	0.823	0.871	0.775
OpenBMILeft/Right Hand MICS	0.64	0.7310	0.66	0.738	0.66	0.71	0.71	0.71	0.736	0.72	0.763	0.66	0.69	0.49	0.71	0.70	0.66	0.737	0.66	0.745	0.65	0.67	0.67	0.764	0.49	0.33	-	-	-	0.33	0.45	0.63	0.67	0.68	0.72	-	-	-	-	-	-	0.822	0.851	0.739
HGDLeft/Right/Hand/Foot/TongueWS	0.45	0.73	0.72	0.7610	0.65	0.75	0.74	0.778	0.73	0.68	0.825	0.49	0.68	0.16	0.72	0.65	0.53	0.842	0.779	0.72	0.65	0.69	0.70	0.72	0.31	0.48	-	-	-	0.843	0.834	0.807	0.71	0.63	0.59	0.816	0.74	-	0.17	-	0.74	0.17	0.891	0.70
HGDLeft/Right/Hand/Foot/TongueCS	0.44	0.755	0.63	0.756	0.68	0.71	0.65	0.792	0.67	0.727	0.55	0.36	0.48	0.33	0.7110	0.70	0.49	0.67	0.63	0.71	0.55	0.65	0.44	0.65	0.30	0.54	-	-	-	0.719	0.754	0.763	0.68	0.54	0.57	-	-	0.718	-	-	-	0.17	0.801	0.67
HGDLeft/Right Hand MIWS	0.34	0.775	0.67	0.768	0.60	0.759	0.74	0.776	0.74	0.74	0.822	0.61	0.63	0.49	0.69	0.59	0.54	0.794	0.73	0.72	0.67	0.71	0.66	0.62	0.46	0.33	-	-	-	0.813	0.767	0.7510	0.71	0.60	0.57	-	0.70	-	-	0.33	-	0.33	0.871	0.70
HGDLeft/Right Hand MICS	0.33	0.776	0.55	0.759	0.59	0.784	0.68	0.802	0.793	0.767	0.73	0.56	0.58	0.33	0.68	0.61	0.57	0.66	0.63	0.768	0.59	0.59	0.55	0.62	0.52	0.33	-	-	-	0.775	0.74	0.7410	0.68	0.54	0.33	-	-	0.65	-	-	-	0.33	0.801	0.67
HGDHand vs Feet MIWS	0.74	0.92	0.937	0.92	0.90	0.89	0.91	0.89	0.939	0.85	0.954	0.81	0.89	-	0.938	0.89	0.76	0.962	0.9310	0.87	0.87	0.90	0.91	0.90	0.40	0.81	-	-	-	0.963	0.955	0.90	0.89	0.86	0.91	-	-	0.946	-	-	0.88	0.40	0.981	0.86
HGDHand vs Feet MICS	0.68	0.902	0.85	0.58	0.75	0.76	0.86	0.895	0.81	0.887	0.8810	0.75	0.56	-	0.889	0.74	0.66	0.81	0.77	0.85	0.73	0.78	0.41	0.80	0.40	0.70	-	-	-	0.888	0.903	0.896	0.86	0.72	0.86	-	0.894	-	-	-	-	0.40	0.961	0.86
Meng2019Cursor Movement DetectionWS	0.75	0.84	0.864	0.83	0.81	0.50	0.848	0.82	0.849	0.80	0.863	0.80	0.81	0.68	0.82	0.82	0.76	0.865	0.83	0.82	0.80	0.81	0.83	0.8410	0.67	0.64	-	-	-	0.79	0.66	0.45	0.82	0.76	0.79	0.857	0.856	-	-	-	-	0.891	0.872	0.81
Meng2019Cursor Movement DetectionCS	0.69	0.73	0.72	0.73	0.71	0.34	0.71	0.70	0.72	0.71	0.755	0.71	0.739	0.65	0.72	0.7310	0.70	0.746	0.71	0.738	0.70	0.70	0.47	0.737	0.61	0.65	-	-	-	0.71	0.56	0.61	0.69	0.72	0.72	-	-	0.763	-	-	0.71	0.801	0.792	0.764
Meng2019Cursor ControlWS	0.64	0.71	0.73	0.70	0.69	0.68	0.72	0.73	0.70	0.67	0.7310	0.70	0.68	0.39	0.71	0.68	0.67	0.747	0.754	0.70	0.72	0.748	0.72	0.745	0.51	0.60	-	-	-	0.49	0.55	0.61	0.66	0.68	0.70	-	0.746	-	-	-	0.753	0.762	0.811	0.749
Meng2019Cursor ControlCS	0.48	0.53	0.51	0.52	0.45	0.47	0.54	0.47	0.54	0.51	0.596	0.48	0.56	0.37	0.54	0.47	0.48	0.614	0.55	0.54	0.55	0.55	0.56	0.615	0.50	0.588	-	-	-	0.44	0.56	0.55	0.5810	0.597	0.50	-	-	0.589	-	-	-	0.682	0.701	0.633
Meng2019Cursor Control + RestWS	0.45	0.66	0.714	0.66	0.64	0.48	0.705	0.66	0.66	0.63	0.697	0.65	0.65	0.43	0.65	0.64	0.60	0.723	0.699	0.66	0.65	0.66	0.67	0.698	0.38	0.35	-	-	-	0.30	0.45	0.52	0.64	0.55	0.60	-	0.706	-	-	-	0.66	0.762	0.791	0.6710
Meng2019Cursor Control + RestCS	0.40	0.50	0.49	0.48	0.48	0.37	0.526	0.47	0.48	0.47	0.5010	0.49	0.519	0.39	0.49	0.49	0.45	0.544	0.45	0.518	0.46	0.44	0.48	0.517	0.37	0.33	-	-	-	0.22	0.38	0.43	0.49	0.47	0.48	-	0.535	-	-	-	-	0.602	0.651	0.583
UCDDB-SleepSleep Staging 30s 5-classWS	0.46	0.66	0.56	0.61	0.61	0.18	0.738	0.55	0.53	0.61	0.72	0.55	0.63	0.11	0.71	0.60	0.59	0.70	0.761	0.35	0.70	0.56	0.64	0.745	0.50	-	-	0.753	0.752	0.7310	0.69	0.739	0.71	-	-	-	0.747	0.746	-	-	-	-	0.754	0.59
UCDDB-SleepSleep Staging 30s 5-classCS	0.47	0.68	0.51	0.61	0.60	0.15	0.719	0.55	0.62	0.61	0.68	0.54	0.63	0.10	0.67	0.61	0.60	0.63	0.727	0.34	0.70	0.56	0.63	0.751	0.47	-	-	0.735	0.734	0.7110	0.61	0.61	0.743	-	-	-	0.752	0.728	-	-	-	-	0.726	0.55
UCDDB-SleepSleep Staging 30s 6-classWS	0.31	0.54	0.46	0.50	0.50	0.15	0.60	0.45	0.54	0.50	0.60	0.46	0.52	0.08	0.59	0.50	0.50	0.58	0.632	0.35	0.58	0.47	0.52	0.617	0.43	-	-	0.633	0.634	0.6010	0.57	0.609	0.608	-	-	-	0.625	0.626	-	-	-	-	0.651	0.51
UCDDB-SleepSleep Staging 30s 6-classCS	0.37	0.57	0.42	0.51	0.50	0.13	0.5810	0.44	0.50	0.49	0.57	0.44	0.51	0.08	0.55	0.51	0.50	0.53	0.616	0.29	0.599	0.47	0.50	0.618	0.41	-	-	0.632	0.635	0.56	0.53	0.09	0.633	-	-	-	0.634	0.617	-	-	-	-	0.631	0.49
UCDDB-SleepSleep/Wake 30sWS	0.72	0.87	0.72	0.87	0.86	0.74	0.82	0.56	0.85	0.85	0.886	0.55	0.86	-	0.87	0.85	0.87	0.87	0.893	0.74	0.88	0.87	0.87	0.887	0.62	-	-	0.891	0.892	0.884	0.888	0.87	0.8810	-	-	-	0.88	0.889	-	-	-	-	0.885	0.82
UCDDB-SleepSleep/Wake 30sCS	0.65	0.86	0.66	0.878	0.85	0.65	0.70	0.78	0.52	0.84	0.86	0.62	0.86	-	0.87	0.85	0.86	0.87	0.884	0.77	0.8710	0.87	0.86	0.87	0.61	-	-	0.885	0.877	0.881	0.86	0.879	0.886	-	-	-	0.87	0.882	-	-	-	-	0.883	0.84
UCDDB-SleepWake/NREM/REM 30sWS	0.59	0.84	0.72	0.79	0.83	0.40	0.83	0.78	0.62	0.80	0.865	0.08	0.79	-	0.83	0.81	0.83	0.84	0.871	0.68	0.82	0.80	0.849	0.84	0.62	-	-	0.864	0.872	0.848	0.8410	0.83	0.84	-	-	-	0.856	0.857	-	-	-	-	0.863	0.79
UCDDB-SleepWake/NREM/REM 30sCS	0.55	0.84	0.71	0.82	0.83	0.36	0.78	0.75	0.83	0.79	0.863	0.53	0.82	-	0.83	0.81	0.8410	0.83	0.871	0.73	0.855	0.81	0.857	0.848	0.63	-	-	0.856	0.854	0.82	0.81	0.83	0.849	-	-	-	0.83	0.83	-	-	-	-	0.862	0.82
HMC-SleepSleep/Wake 30sWS	0.67	0.927	0.79	0.91	0.90	0.83	0.84	0.88	0.92	0.87	0.91	0.90	0.90	0.45	0.91	0.88	0.88	0.928	0.932	0.86	0.929	0.90	0.91	0.926	0.79	-	-	-	-	0.931	0.933	0.91	0.89	-	-	-	0.9210	0.925	-	-	-	-	0.934	0.88
HMC-SleepSleep/Wake 30sCS	0.57	0.84	0.74	0.80	0.82	0.71	0.71	0.81	0.58	0.82	0.875	0.84	0.858	0.44	0.84	0.81	0.79	0.56	0.82	0.81	0.84	0.79	0.8510	0.857	0.79	-	-	-	-	0.881	0.883	0.882	0.874	-	-	-	0.859	0.84	-	-	-	-	0.876	0.83
HMC-SleepWake/NREM/REM 30sWS	0.46	0.857	0.65	0.83	0.81	0.83	0.83	0.79	0.80	0.68	0.83	0.78	0.78	0.27	0.84	0.77	0.79	0.849	0.882	0.76	0.865	0.79	0.81	0.874	0.54	-	-	-	-	0.881	0.883	0.848	0.78	-	-	-	0.8410	0.83	-	-	-	-	0.866	0.57
HMC-SleepWake/NREM/REM 30sCS	0.48	0.75	0.58	0.71	0.70	0.41	0.73	0.67	0.71	0.68	0.768	0.68	0.767	0.30	0.766	0.68	0.71	0.74	0.7510	0.69	0.782	0.70	0.74	0.773	0.57	-	-	-	-	0.791	0.774	0.765	0.73	-	-	-	0.769	0.74	-	-	-	-	0.75	0.71
MigraineDBSSAEP Frequency DiscriminationWS	0.17	0.50	0.45	0.519	0.49	0.22	0.48	0.50	0.14	0.47	0.17	0.33	0.24	0.46	0.33	0.48	0.25	0.24	0.527	0.533	0.518	0.34	0.20	0.50	0.41	0.33	-	-	-	0.641	0.5010	0.552	0.535	0.34	0.526	0.50	0.48	-	-	-	-	0.33	0.49	0.534
MigraineDBSSAEP Frequency DiscriminationCS	0.16	0.22	0.40	0.32	0.49	0.33	0.517	0.49	0.18	0.21	0.509	0.33	0.33	0.46	0.35	0.46	0.47	0.21	0.43	0.5010	0.518	0.50	0.10	0.50	0.46	0.33	-	-	-	0.651	0.50	0.642	0.536	0.34	0.545	-	-	-	-	-	0.48	0.33	0.573	0.544
MigraineDBSSVEP Frequency DiscriminationWS	0.16	0.62	0.51	0.66	0.46	0.23	0.797	0.50	0.62	0.32	0.7110	0.33	0.55	0.49	0.52	0.50	0.49	0.28	0.49	0.798	0.47	0.52	0.31	0.806	0.47	0.33	-	-	-	0.59	0.834	0.892	0.769	0.33	0.825	-	0.34	-	-	-	-	0.33	0.901	0.843
MigraineDBSSVEP Frequency DiscriminationCS	0.17	0.63	0.49	0.69	0.49	0.17	0.798	0.47	0.63	0.52	0.70	0.33	0.35	0.46	0.58	0.50	0.33	0.27	0.45	0.817	0.50	0.51	0.24	0.759	0.33	0.33	-	-	-	0.901	0.853	0.892	0.7210	0.33	0.836	-	-	-	0.33	-	-	0.33	0.854	0.835
MigraineDB4-Hz SSVEP Migraine DetectionWS	0.49	0.46	0.968	0.69	0.63	0.51	0.82	0.70	0.36	0.32	0.88	0.59	0.69	0.34	0.72	0.49	0.53	0.9410	0.82	0.73	0.82	0.86	0.959	0.93	0.37	0.34	-	-	-	0.994	0.995	0.986	0.91	1.002	0.77	-	0.977	-	0.39	-	0.85	1.001	1.003	0.73
MigraineDB6-Hz SSVEP Migraine DetectionWS	0.54	0.57	0.93	0.66	0.57	0.65	0.85	0.71	0.45	0.32	0.86	0.55	0.71	0.34	0.70	0.46	0.42	0.948	0.85	0.72	0.82	0.85	0.939	0.90	0.39	0.34	-	-	-	1.004	0.995	0.977	0.89	1.002	0.77	0.996	0.9310	-	-	-	0.87	1.001	1.003	0.75
MigraineDB4-Hz SSAEP Migraine DetectionWS	0.53	0.62	0.929	0.66	0.67	0.64	0.82	0.72	0.60	0.59	0.9110	0.31	0.75	0.35	0.69	0.59	0.56	0.89	0.81	0.73	0.80	0.81	0.928	0.86	0.37	0.35	-	-	-	0.994	0.995	0.947	0.89	1.001	0.87	-	0.966	-	-	0.33	0.83	1.002	1.003	0.79
MigraineDBResting Migraine DetectionWS	0.70	0.85	0.99	0.92	0.94	0.36	0.95	0.86	0.88	0.75	0.98	0.83	0.95	0.34	0.96	0.89	0.76	1.008	0.96	0.85	0.97	0.98	1.004	1.007	0.59	0.34	-	-	-	1.001	0.9910	1.009	0.95	1.002	-	-	1.006	1.005	-	0.34	-	1.003	-	0.70
MigraineDB6-Hz SSAEP Migraine DetectionWS	0.52	0.64	0.918	0.66	0.66	0.63	0.81	0.73	0.62	0.31	0.909	0.56	0.74	0.35	0.71	0.45	0.60	0.89	0.82	0.74	0.82	0.85	0.9010	0.88	0.38	0.35	-	-	-	0.995	0.994	0.946	0.90	1.003	0.85	-	0.947	-	-	-	-	1.001	1.002	0.79
MigraineDBSSVEP Migraine DetectionWS	0.32	0.75	0.998	0.86	0.86	0.94	0.91	0.83	0.85	0.66	0.96	0.72	0.94	-	0.92	0.81	0.75	0.49	0.89	0.81	0.91	0.9610	0.66	0.989	0.36	0.35	-	-	-	1.003	1.006	1.007	0.95	1.001	0.85	1.005	-	-	-	0.33	-	1.004	1.002	0.84
MigraineDBSSAEP Migraine DetectionWS	0.30	0.86	0.969	0.88	0.88	0.77	0.87	0.77	0.79	0.72	0.968	0.69	0.94	-	0.90	0.82	0.81	0.48	0.87	0.82	0.89	0.94	0.996	0.987	0.50	0.30	-	-	-	1.002	1.005	0.67	0.95	1.004	0.9510	-	-	-	0.36	-	-	1.001	1.003	0.87
BCIC-IV-1Left/Right Hand MIWS	0.47	0.499	0.4910	0.49	0.37	0.36	0.35	0.42	0.35	0.48	0.32	0.32	0.495	0.32	0.36	0.46	0.46	0.32	0.32	0.531	0.496	0.32	0.33	0.36	0.498	0.514	-	-	-	0.532	0.37	0.48	-	0.48	0.47	-	0.38	-	0.48	-	-	0.523	0.497	0.41
BCIC-IV-1Left/Right Hand MICS	0.41	0.509	0.543	0.508	0.38	0.34	0.33	0.47	0.33	0.552	0.33	0.33	0.44	0.33	0.551	0.43	0.40	0.48	0.33	0.517	0.544	0.33	0.48	0.41	0.44	0.46	-	-	-	0.42	0.47	0.33	0.48	0.45	0.33	-	0.46	-	-	-	-	0.526	0.4910	0.525
BCIC-IV-1Left Hand vs Foot MIWS	0.39	0.50	0.584	0.48	0.39	0.33	0.42	0.41	0.33	0.41	0.33	0.33	0.41	0.33	0.48	0.40	0.40	0.45	0.47	0.603	0.5210	0.32	0.548	0.33	0.43	0.651	-	-	-	0.46	0.48	0.576	-	0.51	0.50	0.652	0.575	-	-	0.567	-	0.46	0.529	0.50

Weighted F1

Dataset · task · split	Baseline Models																									Foundation Models
Dataset · task · split	ADFCNN	ATCNet	BiDANN	CTNet	DBConformer	DeepConvNet	DeepSleepNet	EEGConformer	EEGInceptionERP	EEGNet	EEGNeX	EEGWaveNet	FBCNet	HSLT	IFNet	MSCFormer	MSVTNet	ShallowConvNet	SleepEEGNet	SleepTransformer	SlimSeiz	TMSA-Net	TSception	U-Sleep	YASA	BENDR	BIOT · Prest 16ch	BIOT · Shhs Prest 18ch	BIOT · Six Datasets 18ch	CBraMod	CodeBrain	CSBrain	EEGMamba	EEGPT	LaBraM	LEAD	LUNA · Base	LUNA · Large	mdJPT	MIRepNet	NeuroGPT	NeuroRVQ	REVE · Base	REVE · Large
EEGMatMental Arithmetic vs RestWS	0.67	0.75	0.73	0.69	0.66	0.67	0.909	0.86	0.68	0.67	0.74	0.25	0.70	0.66	0.71	0.66	0.66	0.934	0.943	0.71	0.66	0.70	0.74	0.908	0.63	0.907	-	-	-	0.8910	0.926	0.935	0.73	0.77	0.78	0.971	0.81	0.82	0.66	0.66	0.88	0.66	0.952	0.63
EEGMatMental Arithmetic vs RestCS	0.65	0.66	0.67	0.66	0.65	0.65	0.7410	0.70	0.62	0.66	0.68	0.19	0.65	0.65	0.66	0.65	0.65	0.812	0.73	0.67	0.795	0.67	0.70	0.767	0.65	0.768	-	-	-	0.793	0.786	0.71	0.769	0.71	0.70	0.861	0.73	0.68	0.65	0.65	0.794	0.65	0.71	0.65
TUEVEpileptiform EventsWS	0.64	0.81	0.92	0.82	0.81	0.34	0.81	0.85	0.85	0.69	0.87	0.68	0.83	0.15	0.84	0.79	0.68	0.9310	0.93	0.78	0.92	0.86	0.87	0.948	0.57	0.90	-	-	-	0.954	0.962	0.955	0.89	0.957	0.91	0.961	0.956	0.949	0.24	0.24	0.86	0.24	0.963	0.79
TUEVEpileptiform EventsCS	0.85	0.961	0.94	0.965	0.94	0.94	0.94	0.93	0.9510	0.78	0.966	0.49	0.94	0.00	0.964	0.95	0.959	0.963	0.92	0.92	0.94	0.962	0.94	0.958	0.85	0.89	-	-	-	0.92	0.93	0.95	0.92	0.93	0.93	0.967	0.93	0.92	0.00	0.94	0.89	0.94	0.94	0.92
TUEVEpileptiform Event DetectionWS	0.65	0.90	0.94	0.90	0.90	0.24	0.86	0.92	0.91	0.82	0.92	0.88	0.91	-	0.92	0.89	0.85	0.976	0.9610	0.88	0.95	0.91	0.93	0.975	0.80	0.92	-	-	-	0.977	0.973	0.981	0.95	0.972	0.95	0.974	0.969	0.95	0.44	0.44	0.94	0.24	0.968	0.87
TUEVEpileptiform Event DetectionCS	0.26	0.971	0.93	0.968	0.95	0.94	0.965	0.91	0.94	0.75	0.95	0.95	0.91	-	0.966	0.94	0.969	0.95	0.93	0.87	0.95	0.972	0.967	0.974	0.82	0.92	-	-	-	0.93	0.94	0.973	0.89	0.94	0.95	0.94	0.95	0.95	0.00	0.00	0.92	0.00	0.9610	0.91
SHU-MILeft/Right Hand MIWS	0.59	0.65	0.75	0.64	0.62	0.64	0.81	0.65	0.67	0.62	0.70	0.68	0.64	0.50	0.64	0.63	0.57	0.76	0.82	0.84	0.72	0.66	0.70	0.858	0.49	0.50	-	-	-	0.865	0.866	0.857	0.8410	0.36	0.32	0.881	0.864	0.863	0.32	0.32	0.60	0.32	0.882	0.849
SHU-MILeft/Right Hand MICS	0.58	0.64	0.694	0.63	0.679	0.64	0.63	0.63	0.65	0.63	0.677	0.6510	0.678	0.50	0.64	0.65	0.59	0.63	0.65	0.65	0.64	0.64	0.693	0.64	0.53	0.34	-	-	-	0.65	0.65	0.63	0.64	0.56	0.33	0.722	0.685	0.686	0.34	0.34	0.57	0.34	0.721	0.65
TUSLBackground Slowing DetectionWS	0.35	0.44	0.77	0.62	0.62	0.60	0.53	0.62	0.33	0.43	0.41	0.35	0.35	0.35	0.61	0.48	0.43	0.72	0.60	0.43	0.72	0.59	0.35	0.876	0.63	0.62	-	-	-	0.8010	0.884	0.857	0.838	0.79	0.77	0.875	0.902	0.893	0.31	0.31	0.819	0.35	0.921	0.60
TUSLBackground Slowing DetectionCS	0.34	0.43	0.6210	0.42	0.34	0.61	0.46	0.44	0.36	0.42	0.36	0.34	0.34	0.34	0.52	0.36	0.39	0.48	0.34	0.53	0.57	0.55	0.34	0.688	0.52	0.42	-	-	-	0.763	0.734	0.62	0.62	0.53	0.735	0.771	0.639	0.54	0.33	0.33	0.726	0.33	0.772	0.697
TUSLSlowing + SeizureWS	0.30	0.44	0.67	0.26	0.22	0.32	0.61	0.31	0.36	0.28	0.54	0.16	0.45	0.16	0.47	0.34	0.48	0.66	0.60	0.42	0.52	0.55	0.37	0.769	0.29	0.47	-	-	-	0.806	0.852	0.844	0.7110	0.67	0.778	0.843	0.825	0.797	0.20	0.16	0.50	0.14	0.891	0.44
TUSLSlowing + SeizureCS	0.32	0.33	0.15	0.18	0.07	0.25	0.19	0.12	0.18	0.20	0.27	0.07	0.24	0.07	0.30	0.11	0.21	0.31	0.349	0.09	0.27	0.29	0.18	0.26	0.31	0.31	-	-	-	0.582	0.681	0.545	0.30	0.427	0.564	0.583	0.408	0.29	0.18	0.07	0.29	0.07	0.456	0.3310
Kaggle-INRIAP300 Feedback CorrectnessWS	0.60	-	0.699	0.6910	0.56	0.63	0.68	0.68	0.706	0.57	0.713	0.56	0.65	0.23	0.62	0.56	0.62	0.67	0.698	0.705	0.62	0.60	0.66	0.65	0.56	0.56	-	-	-	0.50	0.56	0.64	0.61	0.60	0.65	0.65	0.65	0.62	0.65	0.61	0.722	0.697	0.731	0.704
Kaggle-INRIAP300 Feedback CorrectnessCS	0.63	-	0.76	0.7910	0.77	0.75	0.77	0.805	0.821	0.73	0.812	0.77	0.806	0.04	0.78	0.77	0.78	0.71	0.78	0.807	0.77	0.78	0.77	0.78	0.77	0.808	-	-	-	0.23	0.77	0.77	0.77	0.77	0.77	0.77	0.76	0.74	0.77	0.78	0.804	0.803	0.799	0.76
ERP-BCIP300 Target DetectionWS	0.72	-	0.80	0.81	0.74	0.74	0.829	0.74	0.837	0.68	0.838	0.05	0.79	0.74	0.75	0.74	0.74	0.73	0.74	0.855	0.74	0.74	0.70	0.863	0.74	0.66	-	-	-	0.881	0.854	0.872	-	0.8210	0.846	0.80	0.81	0.74	0.74	0.05	0.74	0.74	-	-
ERP-BCIP300 Target DetectionCS	0.75	-	0.80	0.82	0.75	0.75	0.82	0.75	0.839	0.74	0.848	0.05	0.79	0.75	0.75	0.75	0.75	0.72	0.76	0.854	0.75	0.75	0.70	0.846	0.75	0.75	-	-	-	0.881	0.855	0.862	0.853	0.75	0.847	0.81	0.8210	0.82	0.75	0.05	0.75	0.75	-	-
SEEDEmotion RecognitionWS	0.35	0.65	0.758	0.66	0.66	0.49	0.63	0.66	0.66	0.58	0.729	0.67	0.68	0.30	0.68	0.64	0.60	0.804	0.69	0.50	0.68	0.7110	0.795	0.69	0.46	0.34	-	-	-	0.22	0.65	0.60	0.872	0.52	0.69	0.786	0.787	0.833	0.65	0.56	0.61	-	0.891	0.61
SEEDEmotion RecognitionCS	0.37	0.49	0.49	0.47	0.517	0.38	0.49	0.49	0.45	0.45	0.49	0.48	0.51	0.29	0.48	0.525	0.46	0.534	0.572	0.42	0.518	0.526	0.45	0.5110	0.44	0.18	-	-	-	0.44	0.44	0.39	0.50	0.48	0.45	0.47	0.533	0.48	0.519	0.33	0.46	-	0.581	0.17
FACEDEmotion RecognitionWS	0.07	0.3110	0.30	0.348	0.10	0.375	0.19	0.501	0.357	0.384	0.422	0.06	0.19	0.02	0.319	0.10	0.08	0.393	0.27	0.27	0.20	0.12	0.12	0.12	0.06	0.04	-	-	-	0.06	0.04	0.07	0.376	0.12	0.10	0.26	0.26	0.14	-	0.12	0.12	-	0.29	0.20
FACEDEmotion RecognitionCS	0.07	0.279	0.22	0.326	0.07	0.333	0.12	0.461	0.307	0.324	0.372	0.07	0.17	0.02	0.26	0.08	0.09	0.325	0.22	0.24	0.17	0.11	0.12	0.12	0.06	0.06	-	-	-	0.08	0.08	0.07	0.298	0.10	0.08	0.22	0.25	0.2710	-	0.12	0.15	-	0.25	0.19
DTU-AADGender Attention DecodingWS	0.50	0.56	0.6910	0.55	0.61	0.63	0.59	0.60	0.60	0.49	0.60	0.64	0.60	0.40	0.57	0.53	0.46	0.743	0.734	0.61	0.709	0.69	0.716	0.63	0.42	0.27	-	-	-	0.05	0.55	0.49	0.718	0.901	0.55	0.725	0.68	0.717	-	0.58	0.59	-	0.792	0.56
DTU-AADGender Attention DecodingCS	0.46	0.46	0.49	0.47	0.44	0.44	0.50	0.529	0.01	0.44	0.5210	0.47	0.50	0.44	0.48	0.50	0.47	0.561	0.528	0.45	0.542	0.49	0.48	0.535	0.44	0.33	-	-	-	0.44	0.45	0.28	0.543	0.526	0.44	0.534	0.45	0.527	-	0.44	0.49	-	0.50	0.49
DTU-AADGender x Left/Right Attention DecodingWS	0.21	0.24	0.418	0.24	0.28	0.19	0.32	0.27	0.29	0.22	0.34	0.33	0.29	0.07	0.27	0.22	0.22	0.483	0.474	0.32	0.3910	0.417	0.409	0.35	0.15	0.12	-	-	-	0.09	0.17	0.26	0.426	0.512	-	0.435	0.34	0.37	-	0.30	0.30	-	0.531	0.30
DTU-AADGender x Left/Right Attention DecodingCS	0.24	0.23	0.24	0.23	0.22	0.20	0.266	0.25	0.281	0.20	0.13	0.13	0.268	0.20	0.24	0.18	0.22	0.24	0.2610	0.23	0.24	0.272	0.265	0.264	0.24	0.13	-	-	-	0.07	0.14	0.20	0.269	0.20	0.22	0.273	0.21	0.267	-	0.22	0.16	-	0.25	0.20
DTU-AADLeft/Right Attention DecodingWS	0.44	0.31	0.597	0.51	0.45	0.47	0.54	0.52	0.52	0.34	0.54	0.49	0.51	0.51	0.51	0.36	0.48	0.681	0.662	0.53	0.633	0.615	0.606	0.5710	0.50	0.35	-	-	-	0.35	0.40	0.52	0.589	0.614	0.35	0.57	0.56	0.35	-	0.53	0.55	-	0.588	0.51
DTU-AADLeft/Right Attention DecodingCS	0.43	0.36	0.508	0.49	0.43	0.49	0.48	0.49	0.509	0.37	0.45	0.47	0.5010	0.49	0.513	0.40	0.45	0.49	0.33	0.48	0.507	0.49	0.48	0.41	0.47	0.33	-	-	-	0.48	0.44	0.38	0.521	0.43	-	0.506	0.43	0.33	-	0.41	0.512	-	0.515	0.514
BCIC-IV-2BLeft/Right Hand MIWS	0.49	0.70	0.65	0.72	0.58	0.68	0.743	0.71	0.729	0.71	0.742	0.62	0.63	0.35	0.70	0.7210	0.52	0.66	0.63	0.728	0.52	0.60	-	0.70	0.32	0.32	-	-	-	0.734	0.735	0.727	0.72	0.32	0.71	-	0.70	-	-	-	0.57	0.32	0.761	0.736
BCIC-IV-2BLeft/Right Hand MICS	0.42	0.706	0.61	0.705	0.63	0.68	0.68	0.69	0.699	0.68	0.712	0.60	0.61	0.41	0.69	0.711	0.49	0.64	0.57	0.704	0.52	0.55	-	0.67	0.50	0.52	-	-	-	0.68	0.6910	0.66	0.67	0.33	0.707	0.58	0.69	-	0.33	0.33	-	0.33	0.703	0.698
Large-MILeft/Right/Hand/LegWS	0.33	0.68	0.68	0.67	0.48	0.64	0.717	0.65	0.67	0.59	0.6910	0.44	0.60	0.14	0.63	0.62	0.34	0.733	0.715	0.724	0.58	0.54	0.51	0.716	0.27	0.40	-	-	-	0.11	0.39	0.63	0.64	0.48	0.64	-	0.68	0.708	-	0.50	0.52	0.762	0.831	0.699
Large-MILeft/Right/Hand/LegCS	0.32	0.51	0.53	0.58	0.48	0.61	0.61	0.53	0.658	0.60	0.59	0.42	0.52	0.10	0.649	0.55	0.30	0.703	0.667	0.704	0.52	0.60	0.48	0.57	0.23	0.10	-	-	-	0.09	0.29	0.62	0.60	0.44	0.676	-	0.6210	-	0.695	-	-	0.781	0.742	0.59
Large-MILeft/Right + PassiveWS	0.31	0.70	0.67	0.70	0.60	0.56	0.69	0.69	0.70	0.61	0.728	0.25	0.64	0.24	0.65	0.66	0.41	0.754	0.753	0.7110	0.62	0.66	0.54	0.746	0.35	0.18	-	-	-	0.18	0.33	0.63	0.65	0.56	0.60	-	0.745	0.729	-	0.59	0.62	0.772	0.831	0.727
Large-MILeft/Right + PassiveCS	0.29	0.64	0.55	0.62	0.64	0.62	0.676	0.63	0.63	0.62	0.62	0.25	0.64	0.32	0.64	0.63	0.40	0.6410	0.659	0.722	0.55	0.63	0.48	0.667	0.40	0.56	-	-	-	0.16	0.28	0.64	0.703	0.668	0.684	-	0.675	-	-	-	-	0.791	0.63	0.64
Large-MILeft/Right Hand MIWS	0.43	0.80	0.75	0.8110	0.72	0.78	0.826	0.78	0.819	0.78	0.827	0.00	0.73	0.35	0.75	0.79	0.53	0.828	0.824	0.833	0.77	0.80	0.68	0.825	0.50	0.79	-	-	-	0.34	0.34	0.55	0.69	0.72	0.75	-	0.78	0.80	0.73	0.71	-	0.842	0.861	0.80
Large-MILeft/Right Hand MICS	0.35	0.845	0.68	0.82	0.72	0.854	0.76	0.75	0.846	0.847	0.849	0.60	0.77	-	0.852	0.81	0.61	0.871	0.80	0.80	0.75	0.853	0.75	0.77	0.49	0.33	-	-	-	0.34	0.33	0.73	0.73	0.79	0.8310	-	0.81	-	-	-	0.72	0.848	0.78	0.75
Large-MIHand vs Leg MIWS	0.51	0.77	0.7810	0.76	0.68	0.72	0.77	0.74	0.76	0.69	0.805	0.51	0.72	0.53	0.74	0.72	0.57	0.813	0.806	0.804	0.73	0.69	0.71	0.797	0.53	0.34	-	-	-	0.36	0.54	0.76	0.788	0.65	0.76	-	0.77	-	-	-	-	0.842	0.871	0.789
Large-MIHand vs Leg MICS	0.37	0.754	0.67	0.69	0.65	0.64	0.729	0.68	0.746	0.65	0.68	0.42	0.63	0.53	0.69	0.67	0.53	0.745	0.70	0.737	0.67	0.68	0.66	0.71	0.48	0.70	-	-	-	0.32	0.62	0.60	0.70	0.63	0.763	-	0.7110	0.738	-	-	-	0.861	0.782	0.64
Large-MIIndividual FingersWS	0.17	0.39	0.3910	0.37	0.26	0.34	0.426	0.37	0.34	0.35	0.417	0.19	0.32	0.06	0.34	0.34	0.14	0.425	0.409	0.462	0.31	0.26	0.26	0.35	0.13	0.07	-	-	-	0.08	0.14	0.32	0.34	0.17	0.38	-	0.408	0.35	-	-	-	0.453	0.521	0.444
Large-MIIndividual FingersCS	0.18	0.28	0.24	0.27	0.22	0.29	0.318	0.28	0.28	0.316	0.319	0.19	0.26	0.07	0.26	0.317	0.16	0.26	0.2910	0.354	0.25	0.22	0.21	0.27	0.12	0.10	-	-	-	0.07	0.07	0.19	0.20	0.24	0.371	-	-	-	-	-	-	0.353	0.362	0.335
Large-MILeft/Right/Hand/Leg/TongueWS	0.20	0.63	0.64	0.63	0.44	0.58	0.6510	0.59	0.62	0.54	0.668	0.41	0.55	0.07	0.57	0.59	0.28	0.683	0.667	0.674	0.54	0.45	0.46	0.676	0.16	0.29	-	-	-	0.06	0.31	0.57	0.60	0.36	0.61	-	0.659	-	-	-	-	0.712	0.801	0.675
Large-MILeft/Right/Hand/Leg/TongueCS	0.19	0.50	0.52	0.55	0.49	0.57	0.5710	0.50	0.589	0.51	0.626	0.42	0.46	0.07	0.51	0.50	0.28	0.662	0.617	0.653	0.48	0.44	0.42	0.56	0.15	0.23	-	-	-	0.07	0.20	0.588	0.56	0.42	0.635	-	0.57	-	-	-	-	0.721	0.644	0.52
Large-MIWith RestWS	0.21	-	0.564	0.47	0.35	0.38	0.508	0.41	0.43	0.34	0.46	0.35	0.46	0.09	0.37	0.41	0.29	0.45	0.546	0.499	0.47	0.41	0.44	0.517	0.13	0.07	-	-	-	0.05	0.13	0.05	0.46	0.35	0.545	-	0.573	0.592	0.4910	-	-	0.621	-	-
Large-MIWith RestCS	0.33	-	0.458	0.41	0.41	0.40	0.43	0.39	0.4410	0.33	0.42	0.40	0.487	0.09	0.43	0.41	0.36	0.36	0.449	0.543	0.37	0.38	0.39	0.495	0.16	0.09	-	-	-	0.05	0.11	0.05	0.494	0.35	0.592	-	0.486	-	-	-	-	0.611	-	-
PhysioNet-MILeft/Right/Both Hands/FeetWS	0.24	0.587	0.50	0.5710	0.45	0.53	0.56	0.56	0.54	0.53	0.604	0.32	0.50	0.15	0.51	0.54	0.27	0.51	0.54	0.57	0.49	0.47	0.44	0.588	0.25	0.44	-	-	-	0.603	0.612	0.611	0.56	0.46	0.11	0.596	0.56	-	0.09	0.10	0.47	0.09	0.595	0.579
PhysioNet-MILeft/Right/Both Hands/FeetCS	0.23	0.518	0.46	0.50	0.41	0.47	0.50	0.50	0.49	0.50	0.535	0.32	0.46	0.11	0.48	0.49	0.32	0.47	0.49	0.527	0.44	0.43	0.39	0.543	0.25	0.36	-	-	-	0.561	0.544	0.552	0.519	0.46	0.50	-	0.49	0.5110	-	-	0.46	0.10	0.45	0.526
PhysioNet-MILeft/Right Hand MIWS	0.43	0.78	0.74	0.819	0.69	0.75	0.74	0.77	0.79	0.78	0.7910	0.63	0.72	0.46	0.74	0.77	0.54	0.74	0.76	0.76	0.73	0.69	0.69	0.831	0.52	0.75	-	-	-	0.833	0.834	0.825	0.79	0.73	0.76	0.832	0.818	-	0.29	0.29	0.76	0.37	0.826	0.817
PhysioNet-MILeft/Right Hand MICS	0.42	0.7510	0.72	0.75	0.70	0.74	0.71	0.75	0.75	0.774	0.776	0.60	0.72	0.34	0.72	0.75	0.56	0.72	0.74	0.74	0.71	0.69	0.64	0.782	0.38	0.73	-	-	-	0.811	0.775	0.767	-	0.63	-	-	0.71	-	-	-	0.768	0.33	0.783	0.769
PhysioNet-MIHand vs Feet MIWS	0.63	0.74	0.73	0.69	0.62	0.73	0.72	0.7410	0.72	0.68	0.756	0.47	0.68	-	0.65	0.62	0.62	0.757	0.74	0.73	0.72	0.67	0.70	0.774	0.62	0.73	-	-	-	0.791	0.783	0.782	0.759	0.68	0.74	-	0.74	-	-	0.62	0.72	0.62	0.758	0.765
PhysioNet-MIHand vs Feet MICS	0.64	0.74	0.71	0.70	0.64	0.74	0.74	0.72	0.7410	0.69	0.767	0.64	0.69	-	0.69	0.64	0.64	0.749	0.71	0.73	0.70	0.64	0.68	0.766	0.64	0.73	-	-	-	0.782	0.765	0.773	0.758	0.66	0.74	-	0.74	-	0.64	-	0.72	0.64	0.791	0.764
Stroke-MILeft/Right Hand MIWS	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	0.35	-	-	-	0.582	0.526	0.564	0.573	0.555	0.438	-	0.31	-	0.359	-	-	0.3510	0.601	0.487
Stroke-MILeft/Right Hand MICS	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.33	0.339	-	-	-	0.551	0.476	0.418	0.427	0.532	0.494	-	-	-	-	-	-	0.3310	0.523	0.475
BCIC-IV-2ALeft/Right Hand MIWS	0.51	0.38	0.59	0.639	0.56	0.55	0.49	0.673	0.33	0.34	0.647	0.34	0.59	0.34	0.37	0.59	0.49	0.53	0.731	0.61	0.58	0.59	0.50	0.674	0.51	0.34	-	-	-	0.6210	0.648	0.655	-	0.656	0.45	-	0.61	0.59	-	-	-	0.33	0.722	0.34
BCIC-IV-2ALeft/Right Hand MICS	0.48	0.656	0.44	0.714	0.639	0.58	0.54	0.762	0.33	0.33	0.647	0.33	0.42	0.33	0.53	0.655	0.43	0.46	0.801	0.713	0.50	0.40	0.40	0.61	0.48	0.33	-	-	-	0.51	0.48	0.59	-	0.33	0.52	0.638	0.47	-	0.33	0.33	-	0.33	0.6310	0.43
BCIC-IV-2ALeft/Right/Hand/Foot/TongueWS	0.15	0.469	0.42	0.486	0.16	0.25	0.39	0.477	0.42	0.38	0.513	0.15	0.38	0.10	0.39	0.16	0.26	0.40	0.571	0.40	0.39	0.36	0.37	0.40	0.19	0.14	-	-	-	0.494	0.4610	0.478	-	0.36	0.29	0.485	0.43	-	-	-	-	0.14	0.562	0.42
BCIC-IV-2ALeft/Right/Hand/Foot/TongueCS	0.17	0.10	0.24	0.415	0.13	0.416	0.37	0.414	0.3910	0.34	0.492	0.11	0.25	0.11	0.16	0.12	0.19	0.24	0.491	0.408	0.17	0.13	0.29	0.30	0.10	0.10	-	-	-	0.463	0.38	0.39	-	0.10	0.30	-	0.36	0.34	-	-	0.399	0.10	0.417	0.37
BCIC-IV-2AHand vs Feet MIWS	0.55	0.66	0.59	0.724	0.52	0.54	0.63	0.66	0.18	0.09	0.56	0.52	0.65	-	0.68	0.18	0.52	0.61	0.18	0.67	0.61	0.52	0.44	0.723	0.55	0.52	-	-	-	0.732	0.707	0.706	0.6910	0.60	0.64	-	0.715	0.699	-	-	-	0.52	0.751	0.698
BCIC-IV-2AHand vs Feet MICS	0.59	0.62	0.62	0.659	0.53	0.6510	0.57	0.54	0.17	-	0.55	0.53	0.56	-	0.741	0.53	0.54	0.62	0.55	0.63	0.55	0.53	0.58	0.668	0.17	0.53	-	-	-	0.724	0.677	0.732	0.64	0.60	0.64	-	0.686	-	-	-	-	0.53	0.723	0.695
OpenBMILeft/Right Hand MIWS	0.64	0.74	0.71	0.75	0.68	0.73	0.72	0.73	0.767	0.72	0.784	0.69	0.68	0.51	0.72	0.71	0.68	0.766	0.67	0.759	0.67	0.72	0.72	0.768	0.38	0.66	-	-	-	0.42	0.50	0.61	0.69	0.70	0.7510	0.822	0.72	0.73	-	-	0.75	0.823	0.871	0.775
OpenBMILeft/Right Hand MICS	0.64	0.7310	0.66	0.738	0.66	0.71	0.71	0.71	0.736	0.72	0.763	0.66	0.69	0.49	0.71	0.70	0.66	0.737	0.66	0.745	0.65	0.67	0.67	0.764	0.49	0.33	-	-	-	0.33	0.45	0.63	0.67	0.68	0.72	-	-	-	-	-	-	0.822	0.851	0.739
HGDLeft/Right/Hand/Foot/TongueWS	0.45	0.73	0.72	0.7610	0.65	0.75	0.74	0.778	0.73	0.68	0.825	0.48	0.67	0.16	0.72	0.65	0.53	0.842	0.779	0.72	0.65	0.69	0.70	0.72	0.31	0.48	-	-	-	0.833	0.834	0.807	0.71	0.63	0.58	0.816	0.74	-	0.18	-	0.74	0.16	0.891	0.70
HGDLeft/Right/Hand/Foot/TongueCS	0.44	0.755	0.63	0.756	0.68	0.71	0.65	0.792	0.67	0.728	0.737	0.36	0.64	0.33	0.71	0.70	0.49	0.67	0.63	0.71	0.55	0.65	0.44	0.65	0.30	0.54	-	-	-	0.719	0.754	0.763	0.68	0.54	0.57	-	-	0.7110	-	-	-	0.17	0.801	0.67
HGDLeft/Right Hand MIWS	0.33	0.775	0.67	0.768	0.60	0.759	0.75	0.776	0.74	0.74	0.822	0.61	0.63	0.49	0.69	0.59	0.54	0.794	0.73	0.72	0.67	0.71	0.66	0.61	0.45	0.31	-	-	-	0.813	0.767	0.7510	0.71	0.60	0.57	-	0.70	-	-	0.31	-	0.31	0.871	0.70
HGDLeft/Right Hand MICS	0.33	0.776	0.55	0.759	0.59	0.784	0.68	0.802	0.793	0.767	0.73	0.56	0.58	0.33	0.68	0.61	0.57	0.66	0.63	0.768	0.59	0.59	0.55	0.62	0.52	0.33	-	-	-	0.775	0.74	0.7410	0.68	0.54	0.33	-	-	0.65	-	-	-	0.33	0.801	0.67
HGDHand vs Feet MIWS	0.77	0.93	0.947	0.93	0.91	0.90	0.92	0.90	0.949	0.87	0.964	0.83	0.91	-	0.948	0.90	0.79	0.972	0.9410	0.88	0.89	0.91	0.92	0.91	0.54	0.83	-	-	-	0.963	0.955	0.91	0.90	0.87	0.92	-	-	0.956	-	-	0.90	0.54	0.981	0.88
HGDHand vs Feet MICS	0.73	0.912	0.87	0.89	0.79	0.80	0.88	0.915	0.84	0.909	0.908	0.79	0.86	-	0.907	0.77	0.71	0.84	0.81	0.86	0.77	0.81	0.62	0.83	0.53	0.71	-	-	-	0.9010	0.913	0.916	0.87	0.75	0.88	-	0.914	-	-	-	-	0.53	0.961	0.88
Meng2019Cursor Movement DetectionWS	0.75	0.84	0.864	0.83	0.81	0.50	0.848	0.82	0.849	0.80	0.863	0.80	0.81	0.68	0.82	0.82	0.76	0.865	0.83	0.82	0.80	0.81	0.83	0.8410	0.67	0.64	-	-	-	0.79	0.66	0.67	0.82	0.76	0.79	0.857	0.856	-	-	-	-	0.891	0.872	0.81
Meng2019Cursor Movement DetectionCS	0.69	0.73	0.72	0.73	0.71	0.50	0.71	0.70	0.72	0.71	0.755	0.71	0.739	0.65	0.72	0.7310	0.70	0.746	0.71	0.738	0.70	0.70	0.71	0.737	0.61	0.65	-	-	-	0.71	0.56	0.61	0.69	0.72	0.72	-	-	0.763	-	-	0.71	0.801	0.792	0.764
Meng2019Cursor ControlWS	0.64	0.71	0.73	0.70	0.69	0.68	0.72	0.73	0.70	0.67	0.7310	0.70	0.68	0.39	0.71	0.68	0.67	0.747	0.754	0.70	0.72	0.748	0.72	0.745	0.51	0.59	-	-	-	0.49	0.55	0.61	0.66	0.68	0.70	-	0.746	-	-	-	0.753	0.762	0.811	0.749
Meng2019Cursor ControlCS	0.48	0.53	0.51	0.52	0.45	0.47	0.54	0.47	0.54	0.51	0.596	0.48	0.56	0.37	0.54	0.47	0.48	0.614	0.55	0.54	0.55	0.55	0.56	0.615	0.50	0.588	-	-	-	0.44	0.56	0.55	0.5810	0.597	0.50	-	-	0.589	-	-	-	0.682	0.701	0.633
Meng2019Cursor Control + RestWS	0.52	0.70	0.754	0.70	0.68	0.46	0.736	0.70	0.70	0.67	0.737	0.69	0.69	0.50	0.69	0.68	0.64	0.753	0.728	0.70	0.68	0.70	0.7110	0.729	0.46	0.42	-	-	-	0.36	0.50	0.56	0.68	0.60	0.64	-	0.745	-	-	-	0.68	0.792	0.821	0.71
Meng2019Cursor Control + RestCS	0.47	0.55	0.54	0.55	0.55	0.37	0.5610	0.53	0.54	0.53	0.569	0.54	0.578	0.46	0.55	0.55	0.51	0.594	0.51	0.577	0.52	0.50	0.54	0.576	0.45	0.42	-	-	-	0.33	0.45	0.47	0.54	0.52	0.54	-	0.585	-	-	-	-	0.652	0.691	0.623
UCDDB-SleepSleep Staging 30s 5-classWS	0.51	0.69	0.57	0.65	0.64	0.18	0.74	0.59	0.68	0.64	0.749	0.59	0.67	0.20	0.73	0.63	0.62	0.72	0.771	0.40	0.72	0.60	0.67	0.755	0.53	-	-	0.763	0.772	0.7410	0.71	0.748	0.73	-	-	-	0.756	0.757	-	-	-	-	0.764	0.61
UCDDB-SleepSleep Staging 30s 5-classCS	0.51	0.71	0.54	0.65	0.64	0.15	0.7310	0.57	0.66	0.65	0.70	0.59	0.66	0.18	0.70	0.64	0.63	0.66	0.746	0.39	0.73	0.60	0.66	0.771	0.51	-	-	0.755	0.754	0.739	0.64	0.65	0.753	-	-	-	0.762	0.748	-	-	-	-	0.747	0.58
UCDDB-SleepSleep Staging 30s 6-classWS	0.38	0.65	0.54	0.61	0.61	0.18	0.719	0.55	0.65	0.61	0.7110	0.56	0.63	0.17	0.69	0.60	0.60	0.69	0.741	0.44	0.69	0.57	0.63	0.727	0.52	-	-	0.733	0.734	0.71	0.67	0.718	0.71	-	-	-	0.735	0.726	-	-	-	-	0.742	0.58
UCDDB-SleepSleep Staging 30s 6-classCS	0.45	0.6810	0.50	0.62	0.62	0.16	0.68	0.54	0.61	0.60	0.67	0.55	0.63	0.15	0.66	0.62	0.61	0.64	0.723	0.40	0.709	0.58	0.61	0.726	0.50	-	-	0.721	0.722	0.67	0.63	0.16	0.725	-	-	-	0.718	0.727	-	-	-	-	0.724	0.57
UCDDB-SleepSleep/Wake 30sWS	0.81	0.91	0.81	0.90	0.90	0.83	0.88	0.89	0.90	0.90	0.926	0.71	0.90	-	0.91	0.89	0.90	0.91	0.923	0.83	0.91	0.90	0.90	0.917	0.76	-	-	0.921	0.922	0.924	0.919	0.91	0.918	-	-	-	0.91	0.9110	-	-	-	-	0.925	0.87
UCDDB-SleepSleep/Wake 30sCS	0.77	0.90	0.76	0.909	0.89	0.77	0.80	0.85	0.85	0.88	0.90	0.75	0.90	-	0.90	0.89	0.89	0.90	0.914	0.84	0.9010	0.90	0.90	0.90	0.75	-	-	0.915	0.916	0.911	0.90	0.908	0.917	-	-	-	0.90	0.912	-	-	-	-	0.913	0.88
UCDDB-SleepWake/NREM/REM 30sWS	0.70	0.88	0.77	0.84	0.87	0.66	0.87	0.84	0.87	0.85	0.895	0.07	0.85	-	0.87	0.85	0.86	0.88	0.901	0.76	0.87	0.85	0.88	0.87	0.72	-	-	0.893	0.902	0.888	0.8810	0.87	0.889	-	-	-	0.896	0.887	-	-	-	-	0.894	0.83
UCDDB-SleepWake/NREM/REM 30sCS	0.64	0.86	0.74	0.84	0.86	0.59	0.82	0.79	0.86	0.82	0.873	0.61	0.85	-	0.86	0.84	0.86	0.86	0.881	0.77	0.876	0.84	0.877	0.869	0.70	-	-	0.875	0.874	0.85	0.84	0.86	0.878	-	-	-	0.86	0.8610	-	-	-	-	0.882	0.84
HMC-SleepSleep/Wake 30sWS	0.84	0.965	0.89	0.95	0.95	0.89	0.92	0.93	0.95	0.93	0.95	0.94	0.94	0.75	0.95	0.93	0.93	0.959	0.962	0.93	0.958	0.94	0.95	0.967	0.89	-	-	-	-	0.961	0.963	0.95	0.94	-	-	-	0.9510	0.966	-	-	-	-	0.964	0.93
HMC-SleepSleep/Wake 30sCS	0.76	0.89	0.84	0.86	0.88	0.77	0.83	0.88	0.916	0.88	0.917	0.89	0.909	0.70	0.90	0.88	0.85	0.90	0.88	0.88	0.90	0.85	0.90	0.918	0.87	-	-	-	-	0.921	0.923	0.922	0.924	-	-	-	0.9010	0.90	-	-	-	-	0.915	0.89
HMC-SleepWake/NREM/REM 30sWS	0.63	0.887	0.75	0.87	0.85	0.86	0.87	0.84	0.84	0.77	0.87	0.83	0.83	0.53	0.87	0.82	0.83	0.889	0.912	0.82	0.895	0.84	0.86	0.904	0.69	-	-	-	-	0.911	0.913	0.888	0.83	-	-	-	0.8810	0.86	-	-	-	-	0.896	0.81
HMC-SleepWake/NREM/REM 30sCS	0.61	0.80	0.68	0.77	0.77	0.70	0.79	0.74	0.79	0.76	0.826	0.76	0.817	0.52	0.818	0.76	0.76	0.80	0.819	0.77	0.832	0.77	0.80	0.824	0.70	-	-	-	-	0.841	0.823	0.825	0.79	-	-	-	0.8110	0.79	-	-	-	-	0.81	0.77
MigraineDBSSAEP Frequency DiscriminationWS	0.34	0.50	0.45	0.519	0.49	0.33	0.48	0.50	0.28	0.47	0.27	0.33	0.48	0.46	0.50	0.48	0.50	0.48	0.527	0.533	0.518	0.5010	0.41	0.50	0.40	0.33	-	-	-	0.641	0.50	0.552	0.535	0.34	0.526	0.50	0.48	-	-	-	-	0.33	0.49	0.534
MigraineDBSSAEP Frequency DiscriminationCS	0.32	0.44	0.40	0.48	0.49	0.33	0.518	0.49	0.35	0.42	0.5010	0.33	0.49	0.46	0.527	0.46	0.47	0.41	0.43	0.50	0.519	0.50	0.21	0.50	0.46	0.33	-	-	-	0.651	0.50	0.642	0.536	0.34	0.545	-	-	-	-	-	0.48	0.33	0.573	0.544
MigraineDBSSVEP Frequency DiscriminationWS	0.33	0.62	0.51	0.66	0.46	0.47	0.798	0.50	0.62	0.48	0.71	0.34	0.55	0.49	0.52	0.50	0.49	0.56	0.49	0.799	0.47	0.52	0.46	0.807	0.47	0.33	-	-	-	0.893	0.835	0.892	0.7610	0.33	0.826	-	0.34	-	-	-	-	0.34	0.901	0.844
MigraineDBSSVEP Frequency DiscriminationCS	0.33	0.63	0.49	0.69	0.49	0.34	0.798	0.47	0.63	0.52	0.70	0.33	0.53	0.46	0.58	0.50	0.49	0.55	0.45	0.817	0.50	0.51	0.48	0.759	0.33	0.33	-	-	-	0.901	0.853	0.892	0.7210	0.33	0.836	-	-	-	0.33	-	-	0.33	0.854	0.835
MigraineDB4-Hz SSVEP Migraine DetectionWS	0.49	0.45	0.968	0.69	0.63	0.52	0.82	0.70	0.35	0.31	0.88	0.59	0.69	0.36	0.72	0.49	0.54	0.9410	0.82	0.73	0.82	0.86	0.959	0.93	0.36	0.36	-	-	-	0.994	0.995	0.986	0.91	1.002	0.77	-	0.977	-	0.40	-	0.85	1.001	1.003	0.73
MigraineDB6-Hz SSVEP Migraine DetectionWS	0.54	0.58	0.93	0.66	0.58	0.65	0.85	0.71	0.44	0.31	0.87	0.56	0.71	0.36	0.70	0.47	0.43	0.948	0.85	0.72	0.82	0.85	0.939	0.90	0.38	0.36	-	-	-	1.004	0.995	0.977	0.89	1.002	0.77	0.996	0.9310	-	-	-	0.87	1.001	1.003	0.75
MigraineDB4-Hz SSAEP Migraine DetectionWS	0.53	0.63	0.929	0.67	0.68	0.64	0.82	0.73	0.61	0.60	0.9110	0.28	0.76	0.39	0.70	0.61	0.57	0.89	0.82	0.73	0.80	0.82	0.928	0.86	0.35	0.39	-	-	-	0.994	0.995	0.947	0.90	1.001	0.87	-	0.966	-	-	0.30	0.84	1.002	1.003	0.79
MigraineDBResting Migraine DetectionWS	0.70	0.85	0.99	0.92	0.94	0.35	0.95	0.86	0.88	0.75	0.98	0.83	0.95	0.35	0.96	0.89	0.76	1.008	0.96	0.86	0.97	0.98	1.004	1.007	0.60	0.35	-	-	-	1.001	0.9910	1.009	0.96	1.002	-	-	1.006	1.005	-	0.35	-	1.003	-	0.70
MigraineDB6-Hz SSAEP Migraine DetectionWS	0.51	0.65	0.918	0.66	0.67	0.62	0.81	0.74	0.62	0.28	0.909	0.57	0.75	0.39	0.72	0.47	0.61	0.89	0.82	0.74	0.82	0.85	0.9010	0.88	0.36	0.39	-	-	-	0.995	0.994	0.946	0.90	1.003	0.85	-	0.947	-	-	-	-	1.001	1.002	0.79
MigraineDBSSVEP Migraine DetectionWS	0.46	0.75	0.999	0.86	0.86	0.94	0.91	0.83	0.85	0.67	0.96	0.72	0.94	-	0.92	0.81	0.75	0.9910	0.90	0.82	0.91	0.96	1.007	0.98	0.33	0.38	-	-	-	1.003	1.006	1.008	0.96	1.001	0.85	1.005	-	-	-	0.30	-	1.004	1.002	0.84
MigraineDBSSAEP Migraine DetectionWS	0.42	0.86	0.96	0.88	0.88	0.76	0.87	0.78	0.79	0.73	0.9610	0.70	0.94	-	0.90	0.82	0.82	0.969	0.88	0.82	0.89	0.94	0.997	0.998	0.53	0.26	-	-	-	1.002	1.006	1.005	0.95	1.004	0.95	-	-	-	0.41	-	-	1.001	1.003	0.87
BCIC-IV-1Left/Right Hand MIWS	0.47	0.496	0.49	0.48	0.39	0.34	0.37	0.41	0.37	0.4910	0.30	0.30	0.497	0.30	0.38	0.45	0.47	0.30	0.30	0.531	0.505	0.30	0.31	0.38	0.499	0.524	-	-	-	0.523	0.38	0.49	-	0.48	0.47	-	0.36	-	0.48	-	-	0.522	0.498	0.43
BCIC-IV-1Left/Right Hand MICS	0.41	0.509	0.543	0.508	0.38	0.34	0.33	0.47	0.33	0.552	0.33	0.33	0.44	0.33	0.551	0.43	0.40	0.48	0.33	0.517	0.544	0.33	0.48	0.41	0.44	0.46	-	-	-	0.42	0.47	0.33	0.48	0.45	0.33	-	0.46	-	-	-	-	0.526	0.4910	0.525
BCIC-IV-1Left Hand vs Foot MIWS	0.39	0.50	0.584	0.48	0.39	0.33	0.42	0.41	0.33	0.41	0.33	0.33	0.41	0.33	0.48	0.40	0.40	0.45	0.47	0.603	0.5210	0.32	0.548	0.33	0.43	0.651	-	-	-	0.46	0.48	0.576	-	0.51	0.50	0.652	0.575	-	-	0.567	-	0.46	0.529	0.50

Performance Rankings

Rankings are separated into broad-coverage tasks and channel-constrained tasks, so models with specialized input coverage are compared in a more appropriate task group.

Broad-Coverage Tasks · Top-N Frequency

Models are ordered by Top-N appearances across task splits that most high-coverage models can evaluate.

Top 5

Frequency order

REVE · BaseFoundation model

75Rank 4.8

CBraModFoundation model

49Rank 13.3

CodeBrainFoundation model

43Rank 14.3

U-SleepBaseline model

38Rank 9.7

CSBrainFoundation model

34Rank 12.7

SleepEEGNetBaseline model

32Rank 12.4

ShallowConvNetBaseline model

31Rank 11.4

EEGNeXBaseline model

28Rank 10.0

LUNA · BaseFoundation model

25Rank 9.7

SleepTransformerBaseline model

22Rank 15.0

REVE · LargeFoundation model

18Rank 15.5

EEGMambaFoundation model

15Rank 12.5

EEGPTFoundation model

15Rank 18.9

ATCNetBaseline model

10Rank 13.9

SlimSeizBaseline model

10Rank 15.9

EEGConformerBaseline model

10Rank 16.5

TSceptionBaseline model

9Rank 17.5

BiDANNBaseline model

7Rank 17.2

IFNetBaseline model

7Rank 15.2

CTNetBaseline model

6Rank 14.1

EEGInceptionERPBaseline model

6Rank 15.1

EEGNetBaseline model

6Rank 20.8

TMSA-NetBaseline model

6Rank 18.5

DeepSleepNetBaseline model

4Rank 14.3

DeepConvNetBaseline model

4Rank 20.8

MSCFormerBaseline model

4Rank 20.2

BENDRFoundation model

3Rank 25.1

FBCNetBaseline model

1Rank 18.2

YASABaseline model

1Rank 28.9

HSLTBaseline model

1Rank 29.9

DBConformerBaseline model

0Rank 20.8

MSVTNetBaseline model

0Rank 24.9

ADFCNNBaseline model

0Rank 27.9

EEGWaveNetBaseline model

0Rank 24.4

Top 10

Frequency order

REVE · BaseFoundation model

85Rank 4.8

U-SleepBaseline model

71Rank 9.7

EEGNeXBaseline model

66Rank 10.0

CBraModFoundation model

62Rank 13.3

CSBrainFoundation model

57Rank 12.7

CodeBrainFoundation model

55Rank 14.3

ShallowConvNetBaseline model

54Rank 11.4

LUNA · BaseFoundation model

54Rank 9.7

SleepEEGNetBaseline model

50Rank 12.4

EEGMambaFoundation model

41Rank 12.5

ATCNetBaseline model

39Rank 13.9

SleepTransformerBaseline model

38Rank 15.0

REVE · LargeFoundation model

37Rank 15.5

CTNetBaseline model

37Rank 14.1

SlimSeizBaseline model

33Rank 15.9

BiDANNBaseline model

31Rank 17.2

DeepSleepNetBaseline model

30Rank 14.3

EEGInceptionERPBaseline model

28Rank 15.1

EEGPTFoundation model

23Rank 18.9

EEGConformerBaseline model

23Rank 16.5

TSceptionBaseline model

21Rank 17.5

IFNetBaseline model

20Rank 15.2

EEGNetBaseline model

14Rank 20.8

TMSA-NetBaseline model

13Rank 18.5

DeepConvNetBaseline model

12Rank 20.8

MSCFormerBaseline model

10Rank 20.2

BENDRFoundation model

10Rank 25.1

FBCNetBaseline model

9Rank 18.2

DBConformerBaseline model

5Rank 20.8

MSVTNetBaseline model

4Rank 24.9

ADFCNNBaseline model

3Rank 27.9

YASABaseline model

2Rank 28.9

EEGWaveNetBaseline model

2Rank 24.4

HSLTBaseline model

1Rank 29.9

Top 20

Frequency order

EEGNeXBaseline model

98Rank 10.0

REVE · BaseFoundation model

94Rank 4.8

U-SleepBaseline model

93Rank 9.7

ShallowConvNetBaseline model

90Rank 11.4

DeepSleepNetBaseline model

87Rank 14.3

EEGMambaFoundation model

83Rank 12.5

EEGInceptionERPBaseline model

83Rank 15.1

IFNetBaseline model

83Rank 15.2

CTNetBaseline model

80Rank 14.1

SleepEEGNetBaseline model

79Rank 12.4

LUNA · BaseFoundation model

78Rank 9.7

CSBrainFoundation model

77Rank 12.7

ATCNetBaseline model

77Rank 13.9

SleepTransformerBaseline model

72Rank 15.0

SlimSeizBaseline model

70Rank 15.9

EEGConformerBaseline model

69Rank 16.5

CBraModFoundation model

68Rank 13.3

REVE · LargeFoundation model

68Rank 15.5

FBCNetBaseline model

67Rank 18.2

CodeBrainFoundation model

66Rank 14.3

BiDANNBaseline model

64Rank 17.2

TSceptionBaseline model

63Rank 17.5

TMSA-NetBaseline model

60Rank 18.5

MSCFormerBaseline model

50Rank 20.2

DeepConvNetBaseline model

48Rank 20.8

DBConformerBaseline model

44Rank 20.8

EEGNetBaseline model

40Rank 20.8

EEGPTFoundation model

36Rank 18.9

EEGWaveNetBaseline model

26Rank 24.4

MSVTNetBaseline model

23Rank 24.9

BENDRFoundation model

22Rank 25.1

ADFCNNBaseline model

9Rank 27.9

YASABaseline model

7Rank 28.9

HSLTBaseline model

6Rank 29.9

Top 30

Frequency order

EEGNeXBaseline model

104Rank 10.0

IFNetBaseline model

104Rank 15.2

U-SleepBaseline model

103Rank 9.7

FBCNetBaseline model

103Rank 18.2

ShallowConvNetBaseline model

102Rank 11.4

SleepEEGNetBaseline model

102Rank 12.4

SleepTransformerBaseline model

102Rank 15.0

SlimSeizBaseline model

102Rank 15.9

DeepSleepNetBaseline model

102Rank 14.3

EEGInceptionERPBaseline model

102Rank 15.1

TMSA-NetBaseline model

102Rank 18.5

DBConformerBaseline model

102Rank 20.8

CTNetBaseline model

101Rank 14.1

BiDANNBaseline model

101Rank 17.2

EEGConformerBaseline model

101Rank 16.5

REVE · BaseFoundation model

98Rank 4.8

CSBrainFoundation model

98Rank 12.7

EEGMambaFoundation model

96Rank 12.5

TSceptionBaseline model

96Rank 17.5

MSCFormerBaseline model

96Rank 20.2

ATCNetBaseline model

95Rank 13.9

REVE · LargeFoundation model

95Rank 15.5

EEGNetBaseline model

94Rank 20.8

CodeBrainFoundation model

92Rank 14.3

MSVTNetBaseline model

89Rank 24.9

EEGWaveNetBaseline model

89Rank 24.4

DeepConvNetBaseline model

87Rank 20.8

CBraModFoundation model

84Rank 13.3

LUNA · BaseFoundation model

83Rank 9.7

EEGPTFoundation model

76Rank 18.9

ADFCNNBaseline model

71Rank 27.9

YASABaseline model

60Rank 28.9

BENDRFoundation model

55Rank 25.1

HSLTBaseline model

33Rank 29.9

Top 40

Frequency order

U-SleepBaseline model

104Rank 9.7

EEGNeXBaseline model

104Rank 10.0

CBraModFoundation model

104Rank 13.3

CSBrainFoundation model

104Rank 12.7

CodeBrainFoundation model

104Rank 14.3

ShallowConvNetBaseline model

104Rank 11.4

SleepEEGNetBaseline model

104Rank 12.4

SleepTransformerBaseline model

104Rank 15.0

CTNetBaseline model

104Rank 14.1

SlimSeizBaseline model

104Rank 15.9

BiDANNBaseline model

104Rank 17.2

DeepSleepNetBaseline model

104Rank 14.3

EEGInceptionERPBaseline model

104Rank 15.1

EEGConformerBaseline model

104Rank 16.5

IFNetBaseline model

104Rank 15.2

TMSA-NetBaseline model

104Rank 18.5

DeepConvNetBaseline model

104Rank 20.8

MSCFormerBaseline model

104Rank 20.2

FBCNetBaseline model

104Rank 18.2

DBConformerBaseline model

104Rank 20.8

MSVTNetBaseline model

104Rank 24.9

ADFCNNBaseline model

104Rank 27.9

YASABaseline model

104Rank 28.9

EEGWaveNetBaseline model

104Rank 24.4

EEGNetBaseline model

103Rank 20.8

TSceptionBaseline model

102Rank 17.5

REVE · LargeFoundation model

100Rank 15.5

REVE · BaseFoundation model

99Rank 4.8

ATCNetBaseline model

98Rank 13.9

EEGMambaFoundation model

96Rank 12.5

HSLTBaseline model

89Rank 29.9

LUNA · BaseFoundation model

84Rank 9.7

EEGPTFoundation model

84Rank 18.9

BENDRFoundation model

84Rank 25.1

Broad-Coverage Tasks · Mean Rank

The same broad-coverage task group is ordered by lower mean rank across comparable task splits.

Top 5

Mean rank order

REVE · BaseFoundation model

75Rank 4.8

U-SleepBaseline model

38Rank 9.7

LUNA · BaseFoundation model

25Rank 9.7

EEGNeXBaseline model

28Rank 10.0

ShallowConvNetBaseline model

31Rank 11.4

SleepEEGNetBaseline model

32Rank 12.4

EEGMambaFoundation model

15Rank 12.5

CSBrainFoundation model

34Rank 12.7

CBraModFoundation model

49Rank 13.3

ATCNetBaseline model

10Rank 13.9

CTNetBaseline model

6Rank 14.1

CodeBrainFoundation model

43Rank 14.3

DeepSleepNetBaseline model

4Rank 14.3

SleepTransformerBaseline model

22Rank 15.0

EEGInceptionERPBaseline model

6Rank 15.1

IFNetBaseline model

7Rank 15.2

REVE · LargeFoundation model

18Rank 15.5

SlimSeizBaseline model

10Rank 15.9

EEGConformerBaseline model

10Rank 16.5

BiDANNBaseline model

7Rank 17.2

TSceptionBaseline model

9Rank 17.5

FBCNetBaseline model

1Rank 18.2

TMSA-NetBaseline model

6Rank 18.5

EEGPTFoundation model

15Rank 18.9

MSCFormerBaseline model

4Rank 20.2

DeepConvNetBaseline model

4Rank 20.8

DBConformerBaseline model

0Rank 20.8

EEGNetBaseline model

6Rank 20.8

EEGWaveNetBaseline model

0Rank 24.4

MSVTNetBaseline model

0Rank 24.9

BENDRFoundation model

3Rank 25.1

ADFCNNBaseline model

0Rank 27.9

YASABaseline model

1Rank 28.9

HSLTBaseline model

1Rank 29.9

Top 10

Mean rank order

REVE · BaseFoundation model

85Rank 4.8

U-SleepBaseline model

71Rank 9.7

LUNA · BaseFoundation model

54Rank 9.7

EEGNeXBaseline model

66Rank 10.0

ShallowConvNetBaseline model

54Rank 11.4

SleepEEGNetBaseline model

50Rank 12.4

EEGMambaFoundation model

41Rank 12.5

CSBrainFoundation model

57Rank 12.7

CBraModFoundation model

62Rank 13.3

ATCNetBaseline model

39Rank 13.9

CTNetBaseline model

37Rank 14.1

CodeBrainFoundation model

55Rank 14.3

DeepSleepNetBaseline model

30Rank 14.3

SleepTransformerBaseline model

38Rank 15.0

EEGInceptionERPBaseline model

28Rank 15.1

IFNetBaseline model

20Rank 15.2

REVE · LargeFoundation model

37Rank 15.5

SlimSeizBaseline model

33Rank 15.9

EEGConformerBaseline model

23Rank 16.5

BiDANNBaseline model

31Rank 17.2

TSceptionBaseline model

21Rank 17.5

FBCNetBaseline model

9Rank 18.2

TMSA-NetBaseline model

13Rank 18.5

EEGPTFoundation model

23Rank 18.9

MSCFormerBaseline model

10Rank 20.2

DeepConvNetBaseline model

12Rank 20.8

DBConformerBaseline model

5Rank 20.8

EEGNetBaseline model

14Rank 20.8

EEGWaveNetBaseline model

2Rank 24.4

MSVTNetBaseline model

4Rank 24.9

BENDRFoundation model

10Rank 25.1

ADFCNNBaseline model

3Rank 27.9

YASABaseline model

2Rank 28.9

HSLTBaseline model

1Rank 29.9

Top 20

Mean rank order

REVE · BaseFoundation model

94Rank 4.8

U-SleepBaseline model

93Rank 9.7

LUNA · BaseFoundation model

78Rank 9.7

EEGNeXBaseline model

98Rank 10.0

ShallowConvNetBaseline model

90Rank 11.4

SleepEEGNetBaseline model

79Rank 12.4

EEGMambaFoundation model

83Rank 12.5

CSBrainFoundation model

77Rank 12.7

CBraModFoundation model

68Rank 13.3

ATCNetBaseline model

77Rank 13.9

CTNetBaseline model

80Rank 14.1

DeepSleepNetBaseline model

87Rank 14.3

CodeBrainFoundation model

66Rank 14.3

SleepTransformerBaseline model

72Rank 15.0

EEGInceptionERPBaseline model

83Rank 15.1

IFNetBaseline model

83Rank 15.2

REVE · LargeFoundation model

68Rank 15.5

SlimSeizBaseline model

70Rank 15.9

EEGConformerBaseline model

69Rank 16.5

BiDANNBaseline model

64Rank 17.2

TSceptionBaseline model

63Rank 17.5

FBCNetBaseline model

67Rank 18.2

TMSA-NetBaseline model

60Rank 18.5

EEGPTFoundation model

36Rank 18.9

MSCFormerBaseline model

50Rank 20.2

DeepConvNetBaseline model

48Rank 20.8

DBConformerBaseline model

44Rank 20.8

EEGNetBaseline model

40Rank 20.8

EEGWaveNetBaseline model

26Rank 24.4

MSVTNetBaseline model

23Rank 24.9

BENDRFoundation model

22Rank 25.1

ADFCNNBaseline model

9Rank 27.9

YASABaseline model

7Rank 28.9

HSLTBaseline model

6Rank 29.9

Top 30

Mean rank order

REVE · BaseFoundation model

98Rank 4.8

U-SleepBaseline model

103Rank 9.7

LUNA · BaseFoundation model

83Rank 9.7

EEGNeXBaseline model

104Rank 10.0

ShallowConvNetBaseline model

102Rank 11.4

SleepEEGNetBaseline model

102Rank 12.4

EEGMambaFoundation model

96Rank 12.5

CSBrainFoundation model

98Rank 12.7

CBraModFoundation model

84Rank 13.3

ATCNetBaseline model

95Rank 13.9

CTNetBaseline model

101Rank 14.1

DeepSleepNetBaseline model

102Rank 14.3

CodeBrainFoundation model

92Rank 14.3

SleepTransformerBaseline model

102Rank 15.0

EEGInceptionERPBaseline model

102Rank 15.1

IFNetBaseline model

104Rank 15.2

REVE · LargeFoundation model

95Rank 15.5

SlimSeizBaseline model

102Rank 15.9

EEGConformerBaseline model

101Rank 16.5

BiDANNBaseline model

101Rank 17.2

TSceptionBaseline model

96Rank 17.5

FBCNetBaseline model

103Rank 18.2

TMSA-NetBaseline model

102Rank 18.5

EEGPTFoundation model

76Rank 18.9

MSCFormerBaseline model

96Rank 20.2

DBConformerBaseline model

102Rank 20.8

DeepConvNetBaseline model

87Rank 20.8

EEGNetBaseline model

94Rank 20.8

EEGWaveNetBaseline model

89Rank 24.4

MSVTNetBaseline model

89Rank 24.9

BENDRFoundation model

55Rank 25.1

ADFCNNBaseline model

71Rank 27.9

YASABaseline model

60Rank 28.9

HSLTBaseline model

33Rank 29.9

Top 40

Mean rank order

REVE · BaseFoundation model

99Rank 4.8

U-SleepBaseline model

104Rank 9.7

LUNA · BaseFoundation model

84Rank 9.7

EEGNeXBaseline model

104Rank 10.0

ShallowConvNetBaseline model

104Rank 11.4

SleepEEGNetBaseline model

104Rank 12.4

EEGMambaFoundation model

96Rank 12.5

CSBrainFoundation model

104Rank 12.7

CBraModFoundation model

104Rank 13.3

ATCNetBaseline model

98Rank 13.9

CTNetBaseline model

104Rank 14.1

CodeBrainFoundation model

104Rank 14.3

DeepSleepNetBaseline model

104Rank 14.3

SleepTransformerBaseline model

104Rank 15.0

EEGInceptionERPBaseline model

104Rank 15.1

IFNetBaseline model

104Rank 15.2

REVE · LargeFoundation model

100Rank 15.5

SlimSeizBaseline model

104Rank 15.9

EEGConformerBaseline model

104Rank 16.5

BiDANNBaseline model

104Rank 17.2

TSceptionBaseline model

102Rank 17.5

FBCNetBaseline model

104Rank 18.2

TMSA-NetBaseline model

104Rank 18.5

EEGPTFoundation model

84Rank 18.9

MSCFormerBaseline model

104Rank 20.2

DeepConvNetBaseline model

104Rank 20.8

DBConformerBaseline model

104Rank 20.8

EEGNetBaseline model

103Rank 20.8

EEGWaveNetBaseline model

104Rank 24.4

MSVTNetBaseline model

104Rank 24.9

BENDRFoundation model

84Rank 25.1

ADFCNNBaseline model

104Rank 27.9

YASABaseline model

104Rank 28.9

HSLTBaseline model

89Rank 29.9

Channel-Constrained Tasks · Top-N Frequency

Channel-constrained task splits are ranked separately because several models are only valid on a narrower input space.

Top 5

Frequency order

CBraModFoundation model

12Rank 6.8

ATCNetBaseline model

11Rank 6.8

BIOT · Six Datasets 18chFoundation model

9Rank 4.8

BIOT · Shhs Prest 18chFoundation model

7Rank 4.6

CTNetBaseline model

6Rank 10.6

CSBrainFoundation model

6Rank 9.3

BIOT · Prest 16chFoundation model

6Rank 7.4

CodeBrainFoundation model

5Rank 10.8

EEGWaveNetBaseline model

5Rank 7.7

EEGInceptionERPBaseline model

5Rank 10.6

EEGNetBaseline model

4Rank 9.6

ADFCNNBaseline model

4Rank 11.7

SleepEEGNetBaseline model

4Rank 7.9

LUNA · BaseFoundation model

3Rank 7.9

DBConformerBaseline model

3Rank 10.2

DeepConvNetBaseline model

3Rank 11.0

LUNA · LargeFoundation model

2Rank 10.5

LUNA · HugeFoundation model

1Rank 9.2

ShallowConvNetBaseline model

1Rank 11.1

YASABaseline model

1Rank 16.6

LEADFoundation model

1Rank 4.5

TSceptionBaseline model

1Rank 11.6

BiDANNBaseline model

1Rank 14.8

EEGNeXBaseline model

1Rank 16.4

NeuroGPTFoundation model

1Rank 7.5

MIRepNetFoundation model

1Rank 9.0

REVE · BaseFoundation model

1Rank 19.0

TMSA-NetBaseline model

0Rank 12.3

EEGMambaFoundation model

0Rank 16.9

LaBraMFoundation model

0Rank 12.2

NeuroRVQFoundation model

0Rank 13.9

EEGPTFoundation model

0Rank 15.0

EEGConformerBaseline model

0Rank 19.0

SlimSeizBaseline model

0Rank 19.1

DeepSleepNetBaseline model

0Rank 19.3

FBCNetBaseline model

0Rank 20.3

MSVTNetBaseline model

0Rank 16.1

IFNetBaseline model

0Rank 16.6

REVE · LargeFoundation model

0Rank 18.6

U-SleepBaseline model

0Rank 19.1

SleepTransformerBaseline model

0Rank 20.6

MSCFormerBaseline model

0Rank 24.7

HSLTBaseline model

0Rank 30.5

BENDRFoundation model

0Rank 34.0

Top 10

Frequency order

CBraModFoundation model

18Rank 6.8

ATCNetBaseline model

18Rank 6.8

CTNetBaseline model

13Rank 10.6

BIOT · Shhs Prest 18chFoundation model

12Rank 4.6

CSBrainFoundation model

12Rank 9.3

CodeBrainFoundation model

12Rank 10.8

LUNA · LargeFoundation model

12Rank 10.5

BIOT · Six Datasets 18chFoundation model

11Rank 4.8

LUNA · BaseFoundation model

10Rank 7.9

BIOT · Prest 16chFoundation model

8Rank 7.4

DBConformerBaseline model

8Rank 10.2

LUNA · HugeFoundation model

8Rank 9.2

EEGNetBaseline model

7Rank 9.6

ADFCNNBaseline model

7Rank 11.7

EEGWaveNetBaseline model

6Rank 7.7

EEGInceptionERPBaseline model

6Rank 10.6

SleepEEGNetBaseline model

5Rank 7.9

DeepConvNetBaseline model

5Rank 11.0

ShallowConvNetBaseline model

5Rank 11.1

YASABaseline model

4Rank 16.6

TMSA-NetBaseline model

3Rank 12.3

LEADFoundation model

2Rank 4.5

TSceptionBaseline model

2Rank 11.6

BiDANNBaseline model

2Rank 14.8

EEGNeXBaseline model

2Rank 16.4

EEGMambaFoundation model

2Rank 16.9

NeuroGPTFoundation model

1Rank 7.5

MIRepNetFoundation model

1Rank 9.0

REVE · BaseFoundation model

1Rank 19.0

LaBraMFoundation model

1Rank 12.2

NeuroRVQFoundation model

1Rank 13.9

EEGPTFoundation model

1Rank 15.0

EEGConformerBaseline model

1Rank 19.0

SlimSeizBaseline model

1Rank 19.1

DeepSleepNetBaseline model

1Rank 19.3

FBCNetBaseline model

1Rank 20.3

MSVTNetBaseline model

0Rank 16.1

IFNetBaseline model

0Rank 16.6

REVE · LargeFoundation model

0Rank 18.6

U-SleepBaseline model

0Rank 19.1

SleepTransformerBaseline model

0Rank 20.6

MSCFormerBaseline model

0Rank 24.7

HSLTBaseline model

0Rank 30.5

BENDRFoundation model

0Rank 34.0

Top 20

Frequency order

ATCNetBaseline model

20Rank 6.8

ADFCNNBaseline model

20Rank 11.7

CBraModFoundation model

18Rank 6.8

BiDANNBaseline model

18Rank 14.8

CSBrainFoundation model

17Rank 9.3

CTNetBaseline model

16Rank 10.6

LUNA · LargeFoundation model

16Rank 10.5

CodeBrainFoundation model

14Rank 10.8

LUNA · BaseFoundation model

14Rank 7.9

DBConformerBaseline model

14Rank 10.2

BIOT · Shhs Prest 18chFoundation model

12Rank 4.6

BIOT · Six Datasets 18chFoundation model

12Rank 4.8

BIOT · Prest 16chFoundation model

12Rank 7.4

LUNA · HugeFoundation model

11Rank 9.2

NeuroRVQFoundation model

11Rank 13.9

ShallowConvNetBaseline model

9Rank 11.1

EEGWaveNetBaseline model

8Rank 7.7

DeepConvNetBaseline model

8Rank 11.0

MSVTNetBaseline model

8Rank 16.1

EEGNetBaseline model

7Rank 9.6

U-SleepBaseline model

7Rank 19.1

EEGInceptionERPBaseline model

6Rank 10.6

SleepEEGNetBaseline model

6Rank 7.9

YASABaseline model

6Rank 16.6

TMSA-NetBaseline model

6Rank 12.3

TSceptionBaseline model

6Rank 11.6

IFNetBaseline model

6Rank 16.6

EEGMambaFoundation model

5Rank 16.9

LaBraMFoundation model

5Rank 12.2

EEGConformerBaseline model

5Rank 19.0

DeepSleepNetBaseline model

5Rank 19.3

REVE · LargeFoundation model

5Rank 18.6

SlimSeizBaseline model

4Rank 19.1

REVE · BaseFoundation model

3Rank 19.0

FBCNetBaseline model

3Rank 20.3

SleepTransformerBaseline model

3Rank 20.6

LEADFoundation model

2Rank 4.5

EEGNeXBaseline model

2Rank 16.4

NeuroGPTFoundation model

2Rank 7.5

MIRepNetFoundation model

2Rank 9.0

EEGPTFoundation model

1Rank 15.0

MSCFormerBaseline model

0Rank 24.7

HSLTBaseline model

0Rank 30.5

BENDRFoundation model

0Rank 34.0

Top 30

Frequency order

ATCNetBaseline model

21Rank 6.8

ADFCNNBaseline model

21Rank 11.7

CTNetBaseline model

20Rank 10.6

CBraModFoundation model

19Rank 6.8

CSBrainFoundation model

19Rank 9.3

BiDANNBaseline model

19Rank 14.8

CodeBrainFoundation model

18Rank 10.8

LUNA · LargeFoundation model

18Rank 10.5

DBConformerBaseline model

15Rank 10.2

LUNA · BaseFoundation model

14Rank 7.9

BIOT · Shhs Prest 18chFoundation model

12Rank 4.6

BIOT · Six Datasets 18chFoundation model

12Rank 4.8

BIOT · Prest 16chFoundation model

12Rank 7.4

LUNA · HugeFoundation model

11Rank 9.2

NeuroRVQFoundation model

11Rank 13.9

EEGNetBaseline model

9Rank 9.6

EEGWaveNetBaseline model

9Rank 7.7

DeepConvNetBaseline model

9Rank 11.0

ShallowConvNetBaseline model

9Rank 11.1

MSVTNetBaseline model

9Rank 16.1

IFNetBaseline model

9Rank 16.6

U-SleepBaseline model

9Rank 19.1

YASABaseline model

8Rank 16.6

DeepSleepNetBaseline model

8Rank 19.3

FBCNetBaseline model

8Rank 20.3

EEGInceptionERPBaseline model

7Rank 10.6

SleepEEGNetBaseline model

7Rank 7.9

TSceptionBaseline model

7Rank 11.6

EEGMambaFoundation model

7Rank 16.9

EEGConformerBaseline model

7Rank 19.0

SlimSeizBaseline model

7Rank 19.1

SleepTransformerBaseline model

7Rank 20.6

TMSA-NetBaseline model

6Rank 12.3

REVE · BaseFoundation model

6Rank 19.0

REVE · LargeFoundation model

6Rank 18.6

EEGNeXBaseline model

5Rank 16.4

LaBraMFoundation model

5Rank 12.2

MSCFormerBaseline model

3Rank 24.7

LEADFoundation model

2Rank 4.5

NeuroGPTFoundation model

2Rank 7.5

MIRepNetFoundation model

2Rank 9.0

EEGPTFoundation model

2Rank 15.0

HSLTBaseline model

1Rank 30.5

BENDRFoundation model

0Rank 34.0

Top 40

Frequency order

ATCNetBaseline model

21Rank 6.8

ADFCNNBaseline model

21Rank 11.7

CBraModFoundation model

20Rank 6.8

CTNetBaseline model

20Rank 10.6

BiDANNBaseline model

20Rank 14.8

CSBrainFoundation model

19Rank 9.3

CodeBrainFoundation model

18Rank 10.8

LUNA · LargeFoundation model

18Rank 10.5

DBConformerBaseline model

15Rank 10.2

LUNA · BaseFoundation model

14Rank 7.9

BIOT · Shhs Prest 18chFoundation model

12Rank 4.6

BIOT · Six Datasets 18chFoundation model

12Rank 4.8

BIOT · Prest 16chFoundation model

12Rank 7.4

LUNA · HugeFoundation model

11Rank 9.2

NeuroRVQFoundation model

11Rank 13.9

EEGNetBaseline model

9Rank 9.6

EEGWaveNetBaseline model

9Rank 7.7

DeepConvNetBaseline model

9Rank 11.0

ShallowConvNetBaseline model

9Rank 11.1

YASABaseline model

9Rank 16.6

MSVTNetBaseline model

9Rank 16.1

IFNetBaseline model

9Rank 16.6

U-SleepBaseline model

9Rank 19.1

EEGInceptionERPBaseline model

8Rank 10.6

DeepSleepNetBaseline model

8Rank 19.3

FBCNetBaseline model

8Rank 20.3

SleepEEGNetBaseline model

7Rank 7.9

TSceptionBaseline model

7Rank 11.6

EEGMambaFoundation model

7Rank 16.9

EEGConformerBaseline model

7Rank 19.0

SlimSeizBaseline model

7Rank 19.1

REVE · LargeFoundation model

7Rank 18.6

SleepTransformerBaseline model

7Rank 20.6

TMSA-NetBaseline model

6Rank 12.3

REVE · BaseFoundation model

6Rank 19.0

EEGNeXBaseline model

5Rank 16.4

LaBraMFoundation model

5Rank 12.2

MSCFormerBaseline model

3Rank 24.7

LEADFoundation model

2Rank 4.5

NeuroGPTFoundation model

2Rank 7.5

MIRepNetFoundation model

2Rank 9.0

EEGPTFoundation model

2Rank 15.0

HSLTBaseline model

2Rank 30.5

BENDRFoundation model

2Rank 34.0

Channel-Constrained Tasks · Mean Rank

The channel-constrained task group is also ordered by mean rank, which is less sensitive to different task counts.

Top 5

Mean rank order

LEADFoundation model

1Rank 4.5

BIOT · Shhs Prest 18chFoundation model

7Rank 4.6

BIOT · Six Datasets 18chFoundation model

9Rank 4.8

CBraModFoundation model

12Rank 6.8

ATCNetBaseline model

11Rank 6.8

BIOT · Prest 16chFoundation model

6Rank 7.4

NeuroGPTFoundation model

1Rank 7.5

EEGWaveNetBaseline model

5Rank 7.7

SleepEEGNetBaseline model

4Rank 7.9

LUNA · BaseFoundation model

3Rank 7.9

MIRepNetFoundation model

1Rank 9.0

LUNA · HugeFoundation model

1Rank 9.2

CSBrainFoundation model

6Rank 9.3

EEGNetBaseline model

4Rank 9.6

DBConformerBaseline model

3Rank 10.2

LUNA · LargeFoundation model

2Rank 10.5

CTNetBaseline model

6Rank 10.6

EEGInceptionERPBaseline model

5Rank 10.6

CodeBrainFoundation model

5Rank 10.8

DeepConvNetBaseline model

3Rank 11.0

ShallowConvNetBaseline model

1Rank 11.1

TSceptionBaseline model

1Rank 11.6

ADFCNNBaseline model

4Rank 11.7

LaBraMFoundation model

0Rank 12.2

TMSA-NetBaseline model

0Rank 12.3

NeuroRVQFoundation model

0Rank 13.9

BiDANNBaseline model

1Rank 14.8

EEGPTFoundation model

0Rank 15.0

MSVTNetBaseline model

0Rank 16.1

EEGNeXBaseline model

1Rank 16.4

YASABaseline model

1Rank 16.6

IFNetBaseline model

0Rank 16.6

EEGMambaFoundation model

0Rank 16.9

REVE · LargeFoundation model

0Rank 18.6

REVE · BaseFoundation model

1Rank 19.0

EEGConformerBaseline model

0Rank 19.0

U-SleepBaseline model

0Rank 19.1

SlimSeizBaseline model

0Rank 19.1

DeepSleepNetBaseline model

0Rank 19.3

FBCNetBaseline model

0Rank 20.3

SleepTransformerBaseline model

0Rank 20.6

MSCFormerBaseline model

0Rank 24.7

HSLTBaseline model

0Rank 30.5

BENDRFoundation model

0Rank 34.0

Top 10

Mean rank order

LEADFoundation model

2Rank 4.5

BIOT · Shhs Prest 18chFoundation model

12Rank 4.6

BIOT · Six Datasets 18chFoundation model

11Rank 4.8

CBraModFoundation model

18Rank 6.8

ATCNetBaseline model

18Rank 6.8

BIOT · Prest 16chFoundation model

8Rank 7.4

NeuroGPTFoundation model

1Rank 7.5

EEGWaveNetBaseline model

6Rank 7.7

LUNA · BaseFoundation model

10Rank 7.9

SleepEEGNetBaseline model

5Rank 7.9

MIRepNetFoundation model

1Rank 9.0

LUNA · HugeFoundation model

8Rank 9.2

CSBrainFoundation model

12Rank 9.3

EEGNetBaseline model

7Rank 9.6

DBConformerBaseline model

8Rank 10.2

LUNA · LargeFoundation model

12Rank 10.5

CTNetBaseline model

13Rank 10.6

EEGInceptionERPBaseline model

6Rank 10.6

CodeBrainFoundation model

12Rank 10.8

DeepConvNetBaseline model

5Rank 11.0

ShallowConvNetBaseline model

5Rank 11.1

TSceptionBaseline model

2Rank 11.6

ADFCNNBaseline model

7Rank 11.7

LaBraMFoundation model

1Rank 12.2

TMSA-NetBaseline model

3Rank 12.3

NeuroRVQFoundation model

1Rank 13.9

BiDANNBaseline model

2Rank 14.8

EEGPTFoundation model

1Rank 15.0

MSVTNetBaseline model

0Rank 16.1

EEGNeXBaseline model

2Rank 16.4

YASABaseline model

4Rank 16.6

IFNetBaseline model

0Rank 16.6

EEGMambaFoundation model

2Rank 16.9

REVE · LargeFoundation model

0Rank 18.6

REVE · BaseFoundation model

1Rank 19.0

EEGConformerBaseline model

1Rank 19.0

U-SleepBaseline model

0Rank 19.1

SlimSeizBaseline model

1Rank 19.1

DeepSleepNetBaseline model

1Rank 19.3

FBCNetBaseline model

1Rank 20.3

SleepTransformerBaseline model

0Rank 20.6

MSCFormerBaseline model

0Rank 24.7

HSLTBaseline model

0Rank 30.5

BENDRFoundation model

0Rank 34.0

Top 20

Mean rank order

LEADFoundation model

2Rank 4.5

BIOT · Shhs Prest 18chFoundation model

12Rank 4.6

BIOT · Six Datasets 18chFoundation model

12Rank 4.8

CBraModFoundation model

18Rank 6.8

ATCNetBaseline model

20Rank 6.8

BIOT · Prest 16chFoundation model

12Rank 7.4

NeuroGPTFoundation model

2Rank 7.5

EEGWaveNetBaseline model

8Rank 7.7

LUNA · BaseFoundation model

14Rank 7.9

SleepEEGNetBaseline model

6Rank 7.9

MIRepNetFoundation model

2Rank 9.0

LUNA · HugeFoundation model

11Rank 9.2

CSBrainFoundation model

17Rank 9.3

EEGNetBaseline model

7Rank 9.6

DBConformerBaseline model

14Rank 10.2

LUNA · LargeFoundation model

16Rank 10.5

CTNetBaseline model

16Rank 10.6

EEGInceptionERPBaseline model

6Rank 10.6

CodeBrainFoundation model

14Rank 10.8

DeepConvNetBaseline model

8Rank 11.0

ShallowConvNetBaseline model

9Rank 11.1

TSceptionBaseline model

6Rank 11.6

ADFCNNBaseline model

20Rank 11.7

LaBraMFoundation model

5Rank 12.2

TMSA-NetBaseline model

6Rank 12.3

NeuroRVQFoundation model

11Rank 13.9

BiDANNBaseline model

18Rank 14.8

EEGPTFoundation model

1Rank 15.0

MSVTNetBaseline model

8Rank 16.1

EEGNeXBaseline model

2Rank 16.4

YASABaseline model

6Rank 16.6

IFNetBaseline model

6Rank 16.6

EEGMambaFoundation model

5Rank 16.9

REVE · LargeFoundation model

5Rank 18.6

EEGConformerBaseline model

5Rank 19.0

REVE · BaseFoundation model

3Rank 19.0

U-SleepBaseline model

7Rank 19.1

SlimSeizBaseline model

4Rank 19.1

DeepSleepNetBaseline model

5Rank 19.3

FBCNetBaseline model

3Rank 20.3

SleepTransformerBaseline model

3Rank 20.6

MSCFormerBaseline model

0Rank 24.7

HSLTBaseline model

0Rank 30.5

BENDRFoundation model

0Rank 34.0

Top 30

Mean rank order

LEADFoundation model

2Rank 4.5

BIOT · Shhs Prest 18chFoundation model

12Rank 4.6

BIOT · Six Datasets 18chFoundation model

12Rank 4.8

CBraModFoundation model

19Rank 6.8

ATCNetBaseline model

21Rank 6.8

BIOT · Prest 16chFoundation model

12Rank 7.4

NeuroGPTFoundation model

2Rank 7.5

EEGWaveNetBaseline model

9Rank 7.7

LUNA · BaseFoundation model

14Rank 7.9

SleepEEGNetBaseline model

7Rank 7.9

MIRepNetFoundation model

2Rank 9.0

LUNA · HugeFoundation model

11Rank 9.2

CSBrainFoundation model

19Rank 9.3

EEGNetBaseline model

9Rank 9.6

DBConformerBaseline model

15Rank 10.2

LUNA · LargeFoundation model

18Rank 10.5

CTNetBaseline model

20Rank 10.6

EEGInceptionERPBaseline model

7Rank 10.6

CodeBrainFoundation model

18Rank 10.8

DeepConvNetBaseline model

9Rank 11.0

ShallowConvNetBaseline model

9Rank 11.1

TSceptionBaseline model

7Rank 11.6

ADFCNNBaseline model

21Rank 11.7

LaBraMFoundation model

5Rank 12.2

TMSA-NetBaseline model

6Rank 12.3

NeuroRVQFoundation model

11Rank 13.9

BiDANNBaseline model

19Rank 14.8

EEGPTFoundation model

2Rank 15.0

MSVTNetBaseline model

9Rank 16.1

EEGNeXBaseline model

5Rank 16.4

IFNetBaseline model

9Rank 16.6

YASABaseline model

8Rank 16.6

EEGMambaFoundation model

7Rank 16.9

REVE · LargeFoundation model

6Rank 18.6

EEGConformerBaseline model

7Rank 19.0

REVE · BaseFoundation model

6Rank 19.0

U-SleepBaseline model

9Rank 19.1

SlimSeizBaseline model

7Rank 19.1

DeepSleepNetBaseline model

8Rank 19.3

FBCNetBaseline model

8Rank 20.3

SleepTransformerBaseline model

7Rank 20.6

MSCFormerBaseline model

3Rank 24.7

HSLTBaseline model

1Rank 30.5

BENDRFoundation model

0Rank 34.0

Top 40

Mean rank order

LEADFoundation model

2Rank 4.5

BIOT · Shhs Prest 18chFoundation model

12Rank 4.6

BIOT · Six Datasets 18chFoundation model

12Rank 4.8

CBraModFoundation model

20Rank 6.8

ATCNetBaseline model

21Rank 6.8

BIOT · Prest 16chFoundation model

12Rank 7.4

NeuroGPTFoundation model

2Rank 7.5

EEGWaveNetBaseline model

9Rank 7.7

LUNA · BaseFoundation model

14Rank 7.9

SleepEEGNetBaseline model

7Rank 7.9

MIRepNetFoundation model

2Rank 9.0

LUNA · HugeFoundation model

11Rank 9.2

CSBrainFoundation model

19Rank 9.3

EEGNetBaseline model

9Rank 9.6

DBConformerBaseline model

15Rank 10.2

LUNA · LargeFoundation model

18Rank 10.5

CTNetBaseline model

20Rank 10.6

EEGInceptionERPBaseline model

8Rank 10.6

CodeBrainFoundation model

18Rank 10.8

DeepConvNetBaseline model

9Rank 11.0

ShallowConvNetBaseline model

9Rank 11.1

TSceptionBaseline model

7Rank 11.6

ADFCNNBaseline model

21Rank 11.7

LaBraMFoundation model

5Rank 12.2

TMSA-NetBaseline model

6Rank 12.3

NeuroRVQFoundation model

11Rank 13.9

BiDANNBaseline model

20Rank 14.8

EEGPTFoundation model

2Rank 15.0

MSVTNetBaseline model

9Rank 16.1

EEGNeXBaseline model

5Rank 16.4

YASABaseline model

9Rank 16.6

IFNetBaseline model

9Rank 16.6

EEGMambaFoundation model

7Rank 16.9

REVE · LargeFoundation model

7Rank 18.6

EEGConformerBaseline model

7Rank 19.0

REVE · BaseFoundation model

6Rank 19.0

U-SleepBaseline model

9Rank 19.1

SlimSeizBaseline model

7Rank 19.1

DeepSleepNetBaseline model

8Rank 19.3

FBCNetBaseline model

8Rank 20.3

SleepTransformerBaseline model

7Rank 20.6

MSCFormerBaseline model

3Rank 24.7

HSLTBaseline model

2Rank 30.5

BENDRFoundation model

2Rank 34.0

Overall Performance Gain (Δ)

For each dataset-task split, Δ is computed as Δ_FM=S^*_FM−S^*_baseline; positive values mean the best foundation model outperforms the best baseline.

EEG FMs perform betterSupervised baselines perform better

Positive EEG-FM gains are concentrated in ERP, Clinical, and part of Motor Imagery, while strong supervised baselines remain competitive in MI, Auditory, Emotion, and Migraine settings.

EEGMatMental Arithmetic vs RestWS+0.04

EEGMatMental Arithmetic vs RestCS+0.12

TUEVEpileptiform EventsWS+0.06

TUEVEpileptiform EventsCS-0.13

TUEVEpileptiform Event DetectionWS+0.03

TUEVEpileptiform Event DetectionCS-0.06

SHU-MILeft/Right Hand MIWS+0.03

SHU-MILeft/Right Hand MICS+0.02

TUSLBackground Slowing DetectionWS+0.05

TUSLBackground Slowing DetectionCS+0.10

TUSLSlowing + SeizureWS+0.20

TUSLSlowing + SeizureCS+0.34

Kaggle-INRIAP300 Feedback CorrectnessWS+0.07

Kaggle-INRIAP300 Feedback CorrectnessCS+0.02

ERP-BCIP300 Target DetectionWS+0.08

ERP-BCIP300 Target DetectionCS+0.11

SEEDEmotion RecognitionWS+0.14

SEEDEmotion RecognitionCS+0.01

FACEDEmotion RecognitionWS-0.15

FACEDEmotion RecognitionCS-0.19

DTU-AADGender Attention DecodingWS+0.32

DTU-AADGender Attention DecodingCS-0.01

DTU-AADGender x Left/Right Attention DecodingWS+0.06

DTU-AADGender x Left/Right Attention DecodingCS+0.00

DTU-AADLeft/Right Attention DecodingWS-0.10

DTU-AADLeft/Right Attention DecodingCS+0.01

BCIC-IV-2BLeft/Right Hand MIWS+0.02

BCIC-IV-2BLeft/Right Hand MICS-0.01

Large-MILeft/Right/Hand/LegWS+0.17

Large-MILeft/Right/Hand/LegCS+0.11

Large-MILeft/Right + PassiveWS+0.16

Large-MILeft/Right + PassiveCS+0.10

Large-MILeft/Right Hand MIWS+0.06

Large-MILeft/Right Hand MICS-0.05

Large-MIHand vs Leg MIWS+0.11

Large-MIHand vs Leg MICS+0.21

Large-MIIndividual FingersWS+0.07

Large-MIIndividual FingersCS+0.01

Large-MILeft/Right/Hand/Leg/TongueWS+0.21

Large-MILeft/Right/Hand/Leg/TongueCS+0.07

Large-MIWith RestWS+0.18

Large-MIWith RestCS+0.08

PhysioNet-MILeft/Right/Both Hands/FeetWS+0.02

PhysioNet-MILeft/Right/Both Hands/FeetCS+0.03

PhysioNet-MILeft/Right Hand MIWS-0.00

PhysioNet-MILeft/Right Hand MICS+0.03

PhysioNet-MIHand vs Feet MIWS+0.06

PhysioNet-MIHand vs Feet MICS+0.11

Stroke-MILeft/Right Hand MIWS+0.10

Stroke-MILeft/Right Hand MICS+0.05

BCIC-IV-2ALeft/Right Hand MIWS-0.01

BCIC-IV-2ALeft/Right Hand MICS-0.15

BCIC-IV-2ALeft/Right/Hand/Foot/TongueWS-0.01

BCIC-IV-2ALeft/Right/Hand/Foot/TongueCS-0.05

BCIC-IV-2AHand vs Feet MIWS+0.05

BCIC-IV-2AHand vs Feet MICS-0.03

OpenBMILeft/Right Hand MIWS+0.09

OpenBMILeft/Right Hand MICS+0.09

HGDLeft/Right/Hand/Foot/TongueWS+0.07

HGDLeft/Right/Hand/Foot/TongueCS+0.00

HGDLeft/Right Hand MIWS+0.05

HGDLeft/Right Hand MICS+0.01

HGDHand vs Feet MIWS+0.02

HGDHand vs Feet MICS+0.11

Meng2019Cursor Movement DetectionWS+0.07

Meng2019Cursor Movement DetectionCS+0.10

Meng2019Cursor ControlWS+0.06

Meng2019Cursor ControlCS+0.09

Meng2019Cursor Control + RestWS+0.11

Meng2019Cursor Control + RestCS+0.15

UCDDB-SleepSleep Staging 30s 5-classWS-0.01

UCDDB-SleepSleep Staging 30s 5-classCS-0.02

UCDDB-SleepSleep Staging 30s 6-classWS-0.01

UCDDB-SleepSleep Staging 30s 6-classCS+0.00

UCDDB-SleepSleep/Wake 30sWS+0.00

UCDDB-SleepSleep/Wake 30sCS+0.01

UCDDB-SleepWake/NREM/REM 30sWS-0.00

UCDDB-SleepWake/NREM/REM 30sCS-0.01

HMC-SleepSleep/Wake 30sWS+0.01

HMC-SleepSleep/Wake 30sCS+0.03

HMC-SleepWake/NREM/REM 30sWS+0.00

HMC-SleepWake/NREM/REM 30sCS+0.02

MigraineDBSSAEP Frequency DiscriminationWS+0.22

MigraineDBSSAEP Frequency DiscriminationCS+0.27

MigraineDBSSVEP Frequency DiscriminationWS+0.19

MigraineDBSSVEP Frequency DiscriminationCS+0.19

MigraineDB4-Hz SSVEP Migraine DetectionWS+0.05

MigraineDB6-Hz SSVEP Migraine DetectionWS+0.06

MigraineDB4-Hz SSAEP Migraine DetectionWS+0.08

MigraineDBResting Migraine DetectionWS+0.00

MigraineDB6-Hz SSAEP Migraine DetectionWS+0.09

MigraineDBSSVEP Migraine DetectionWS+0.01

MigraineDBSSAEP Migraine DetectionWS+0.02

BCIC-IV-1Left/Right Hand MIWS+0.01

BCIC-IV-1Left/Right Hand MICS+0.00

BCIC-IV-1Left Hand vs Foot MIWS+0.05

CAP-SleepSleep Staging 30s 6-classWS+0.01

CAP-SleepSleep Staging 30s 6-classCS+0.01

CAP-SleepSleep/Wake 30sWS+0.01

CAP-SleepSleep/Wake 30sCS-0.00

CAP-SleepWake/NREM/REM 30sWS+0.01

CAP-SleepWake/NREM/REM 30sCS+0.02

CAP-SleepCAP Detection 14sWS+0.02

CAP-SleepCAP Detection 14sCS+0.05