Example for applying the COMSTAT multimodal factor analysis algorithm to EEG data to describe variance sources

An example is given for the application of the COMSTAT algorithm for multimodal factor analysis to EEG power spectral data. The COMSTAT algorithm enlarges Tucker 's three-mode factor analysis to a multimodal one, and improves his algorithm by a least squares solution. The EEG power spectral data from 65 healthy subjects with an occipital rhythm between 8 and 12 Hz were taken. For demonstration purposes we selected three modes, which have been used by other authors: mode 1: 29 frequency classes, 1n of relative power, in delta f = 1.0-Hz steps between 1 and 30 Hz; mode 2: 16 segments, 40 s each, during the two situational vigilance conditions reaction time (RT) and resting (RS), and mode 3: 65 persons. The frequency mode could be described sufficiently by five factors which we called: delta F/alpha F1; nu F/alpha F2; beta F1/alpha F1; beta F2; beta F3. The factor-loading profiles were similar to those described earlier in independent data. Thus, in the three-mode model we obtained results comparable to those of two-mode models. In the level of 16 situational segments only two factors were extractable. They described the two situations RT, higher vigilance level, and RS, lower vigilance level. In order to demonstrate the changes in factor structure, if a two-mode model is enlarged by a third mode, we used two models for the description of personal (P) variance. When the matrix persons X segments (P X V) was taken, only two factors were extractable.(ABSTRACT TRUNCATED AT 250 WORDS)