PASCAL Workshop on Methods of Data Analysis in Computational Neuroscience and Brain Computer Interfaces

New BCI approaches: Selective Attention to Auditory and Tactile Stimulus Streams

author:Jeremy Hill, Max Planck Institute for Biological Cybernetics, Max Planck Institute
published: Sept. 24, 2007, recorded: June 2007, views: 273

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Slides

Slides
0:02	New BCI approaches Selective Attention to Auditory and Tactile Stimulus Streams
1:44	Overview pt 1
2:37	Overview pt 2
2:51	Overview pt 3
3:06	Overview pt 4
3:30	Overview pt 5
3:37	Why Non-Visual pt 1
3:38	Why Non-Visual pt 2
3:58	Why Non-Visual pt 3
6:12	Why Non-Motor pt 1
6:55	Why Non-Motor pt 2
7:06	Why Non-Motor pt 3
7:17	Why Non-Motor pt 4
7:54	Auditory and Tactile BCI pt 1
8:07	Auditory and Tactile BCI pt 2
8:13	Auditory and Tactile BCI pt 3
8:18	Auditory and Tactile BCI pt 4
8:45	Auditory and Tactile BCI pt 5
8:59	Auditory and Tactile BCI pt 6
9:22	I - Auditory Stimulation in EEG pt 1
9:54	I - Auditory Stimulation in EEG pt 2
10:07	I - Auditory Stimulation in EEG pt 3
11:15	I - Auditory Stimulation in EEG pt 4
11:27	I - Auditory Stimulation in EEG pt 5
11:36	I - Auditory Stimulation in EEG pt 6
11:37	I - Auditory Stimulation in EEG pt 7
12:16	Trial Structure
12:52	Data Structure
13:27	II - Tactile Stimulation in MEG pt 1
16:12	II - Tactile Stimulation in MEG pt 2
16:43	Classification pt 1
18:14	Classification pt 2
18:19	Classification pt 3
18:21	Classification pt 4
18:24	Classification pt 5
18:36	Classification pt 6
18:45	Classification pt 7
18:47	Classification pt 8
20:11	Classification pt 9
20:46	Classification pt 10
21:35	Classification pt 11
21:59	Classification pt 12
22:05	Classification pt 13
22:14	Bilinear Discriminant Analysis pt 1
22:56	Bilinear Discriminant Analysis pt 2
23:14	Bilinear Discriminant Analysis pt 3
23:40	Bilinear Discriminant Analysis pt 4
23:55	Bilinear Discriminant Analysis pt 5
24:22	Bilinear Discriminant Analysis pt 6
24:56	Bilinear Discriminant Analysis pt 7
25:10	Bilinear Discriminant Analysis pt 8
25:30	Bilinear Discriminant Analysis pt 9
26:07	Bilinear Discriminant Analysis pt 10
26:28	Bilinear Discriminant Analysis pt 11
26:37	Bilinear Discriminant Analysis pt 12
27:17	Bilinear Discriminant Analysis pt 13
27:29	Spatial Whitening in ERP Classification pt 1
28:27	Spatial Whitening in ERP Classification pt 2
28:31	Spatial Whitening in ERP Classification pt 3
28:34	Spatial Whitening in ERP Classification pt 4
28:37	Spatial Whitening in ERP Classification pt 5
28:47	Spatial Whitening in ERP Classification pt 6
28:51	Spatial Whitening in ERP Classification pt 7
29:18	Spatial Whitening in ERP Classification pt 8
30:11	Spatial Whitening in ERP Classification pt 9
32:02	Spatial Whitening in ERP Classification pt 10
32:14	Spatial Whitening in ERP Classification pt 11
32:43	Filters and Patterns pt 1
33:33	Filters and Patterns pt 2
34:16	Filters and Patterns pt 3
34:28	Filters and Patterns pt 4
34:50	Preconditioning and Regularization pt 1
34:53	Preconditioning and Regularization pt 2
35:36	Preconditioning and Regularization pt 3
35:59	Preconditioning and Prior Knowledge pt 1
36:43	Preconditioning and Prior Knowledge pt 2
37:12	Preconditioning and Prior Knowledge pt 3
37:56	Preconditioning and Prior Knowledge pt 4
38:43	Preconditioning and Prior Knowledge pt 5
38:46	Bilinear Discriminant Component Analysis pt 1
39:25	Bilinear Discriminant Component Analysis pt 2
39:29	Bilinear Discriminant Component Analysis pt 3
40:35	Sparsification
41:25	Does a Low-Rank Constraint Help pt 1
42:09	Does a Low-Rank Constraint Help pt 2
42:46	Example Decomposition (Auditory) pt 1
43:37	Example Decomposition (Auditory) pt 2
43:50	Example Decomposition (Auditory) pt 3
43:54	Example Decomposition (Auditory) pt 4
44:04	Example Decomposition (Auditory) pt 5
44:46	Classification Performance (Auditory)
45:06	Example Decomposition (Tactile) pt 1
45:36	Example Decomposition (Tactile) pt 2
46:00	Example Decomposition (Tactile) pt 3
46:01	Example Decomposition (Tactile) pt 4
46:03	Slow Waves Indicating Attention pt 1
46:58	Slow Waves Indicating Attention pt 2
47:13	Classification Performance
48:05	Bit Rates
48:34	Conclusions pt 1
49:03	Conclusions pt 2
50:26	Thank You

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