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

Symbolic Dynamics of Neurophysiological Data

author: Peter beim Graben, University of Reading

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*Slides*
0:00	Symbolic Dynamics of Neurophysiological Data
0:20	Content
0:59	Ion Channels I
2:40	Ion Channels II
3:28	Action Potentials I
4:31	Action Potentials II
6:01	Event-Related Potentials I
6:49	Event-Related Potentials II
7:39	Event-Related Potentials III
8:25	The Dynamical Approach
10:17	Phase Space Portrait
11:39	Coarse-Graining
12:01	Symbolic Dynamics of Noisy Data
13:31	Cylinder Sets of ERP
16:22	Measures of Complexity
17:08	Entropy
17:36	Signal-to-Noise Ratios
19:22	One-Threshold Encodings
20:04	Signal-to-Noise Ratios (a)
21:42	One-Threshold Encodings (a)
23:09	Two-Threshold Encoding
24:11	Symbolic Resonance Analysis pt 1
25:17	Symbolic Resonance Analysis pt 2
26:07	Mean-Field Transformation pt 1
27:59	Mean-Field Transformation pt 2
28:06	Mean-Field Transformation pt 3
28:30	Mean-Field Transformation pt 4
28:46	Mean-Field Transformation pt 5
28:49	Mean-Field Transformation pt 6
28:51	Mean-Field Transformation pt 7
28:53	Mean-Field Transformation pt 8
29:01	Mean-Field Transformation pt 9
29:11	Mean-Field Transformation pt 10
30:19	Mean-Field Transformation pt 11
30:50	Signal Dissociation I
33:42	Signal Dissociation II
34:55	Applications
34:56	Oddball Experiment
35:17	Baseline Encoding I
36:31	Baseline Encoding II
36:53	Baseline Encoding III
37:18	Median Encoding I
37:42	Median Encoding II
37:57	Median Encoding III
38:05	Symbolic Resonance Analysis pt 3
38:23	Symbolic Resonance Analysis pt 4
39:43	Time-Threshold-Analysis
40:28	Negative Polarity Processing
42:24	Acknowledgements
44:33	Time-Threshold-Analysis (a)
45:31	Symbolic Resonance Analysis pt 4 (a)

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