5. DISCUSSION
5.3 T HE MODULATOR FLUCTUATIONS FROM ALERTNESS TO DROWSINESS
In this study, we employed independent modulator decomposition to the spectral fluctuations of independent components, and two independent modulators related to performance changes were found in all subjects.
The alpha modulators were very sensitive to the performance changes, so the alpha modulator fluctuates very large during the low LDE periods. Therefore, the alpha modulator in this study might be partially contributed by cortical idling, decreased attentiveness and decline of movements. In the earlier finding (Lee et al., 1999), the frequency of the 8-14 Hz synchronizes in the thalamocortical system during quiet sleep. The EEG fluctuations from low error to high error were similarly during frontal, central-parietal and occipital lobe in the experiment. So that the alpha modulator maybe also modulated by thalamus during drowsiness.
The theta-beta modulators increase monotonically from low LDE to high LDE. Theta rhythm is the EEG characteristic of sleep stage 1 and microsleep (Bear et al., 2001; Gennaro et al., 2001; Thomas et al., 2003). Past studies also reported the fluctuations in the modulation of the beta-wave amplitude related to an indirect measurement of drowsiness (Poupard et al., 2001). Jung et al. (1997) also reported theta and beta band power were high correlated with performance changes.
The correlation coefficient between modulator power change and LDE is shown in Table 4-2. The standard deviation is large because the inter-subject behavior states are varied. Some subjects were involved more period of stage 1 sleep, others included more time of cortical idling, so that results of the independent modulator decomposition depend on drowsiness state.
6. Conclusions
In this study, we model spectral fluctuations of independent components from EEG activations as the actions of independently modulator processes, and report two main classes of spectral modulation patterns, alpha modulator and theta-beta modulator. The theta-beta modulator fluctuates very little during the low LDE periods, and increases monotonically from low LDE to high LDE. Different with the theta-beta band, the alpha modulator fluctuates very large during the low LDE periods. Therefore, the theta-beta modulator is high correlated with performance changes, and alpha modulator in this study might be partially contributed by cortical idling. In our modulation model, these modulators are modulated by the subcortical nucleus or synchronized by cortical-cortical interaction to influence on the rhythmic activations of cortical areas. The neuromodulatory systems can be explored more by the method we propose here.
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