en
0.25
0.5
0.75
1.25
1.5
1.75
2
Separating Sources and Analysing Connectivity in EEG/MEG Using Probabilistic Models
Published on 2012-12-033841 Views
Currently, there is increasing interest in analysing brain activity in resting state, or under relatively natural conditions such as while watching a movie. When using functional magnetic resonance im
Related categories
Presentation
Separating sources and analysing connectivity in EEG/MEG using probabilistic models00:00
Abstract00:13
Problem of blind source separation01:57
A solution is possible (1)02:56
A solution is possible (2)03:14
Independent Component Analysis04:27
When can the ICA model be estimated?05:40
Reminder: Principal component analysis07:24
Comparison of ICA, factor analysis and principal component analysis09:05
Some examples of nongaussianity 12:00
Why classic methods cannot find original components or sources13:54
Nongaussianity, with independence, gives more information15:44
Illustration18:32
Illustration of problem with gaussian distributions20:03
Basic intuitive principle of ICA estimation22:24
Illustration of changes in nongaussianity27:11
Development of ICA algorithms28:04
Sparsity is the dominant form of non-Gaussianity 31:34
Combining ICA with factor analysis or PCA33:57
The brain at rest37:19
Is anything happening in the brain at rest?39:53
ICA finds resting-state networks in fMRI (1)41:28
ICA finds resting-state networks in fMRI (2)43:02
How about EEG and MEG?43:50
Different sparsities of EEG/MEG data (1)44:28
Different sparsities of EEG/MEG data (2)45:34
Different sparsities of EEG/MEG data (3)46:16
Different sparsities of EEG/MEG data (4)47:04
Spectral sparsity: Fourier-ICA (1)47:36
Spectral sparsity: Fourier-ICA (2)49:33
Spatial sparsity (spatial ICA)50:54
Spatial ICA in MEG52:27
Testing ICs: motivation (1)54:54
Testing ICs: motivation (2)57:54
Testing ICs: results01:00:49
Causal analysis: Introduction01:02:52
Structural equation models (1)01:08:26
Structural equation models (2)01:09:47
Simple measures of causal direction01:11:05
Sample of results on MEG01:13:46
Discussion (1)01:15:05
Discussion (2)01:16:22
Discussion (3)01:17:03