Abstract
Heterogeneity of the posterior alpha rhythm (AR) is a widely assumed but rarely tested phenomenon. We decomposed the posterior AR in the cortical source space with a 3-way PARAFAC technique, taking into account the spatial, frequency, and temporal aspects of mid-density EEG. We found a multicomponent AR structure in 90% of a group of 29 healthy adults. The typical resting-state structure consisted of a high-frequency occipito-parietal component of the AR (ARC1) and a low-frequency occipito-temporal component (ARC2), characterized by individual dynamics in time. In a few cases, we found a 3-component structure, with two ARC1s and one ARC2. The AR structures were stable in their frequency and spatial features over weeks to months, thus representing individual EEG alpha phenotypes. Cortical topography, individual stability, and similarity to the primate AR organization link ARC1 to the dorsal visual stream and ARC2 to the ventral one. Understanding how many and what kind of posterior AR components contribute to the EEG is essential for clinical neuroscience as an objective basis for AR segmentation and for interpreting AR dynamics under various conditions, both normal and pathological, which can selectively affect individual components.
Highlights
Heterogeneity of the posterior alpha rhythm (AR) is a widely assumed but rarely tested phenomenon
The above findings suggest that the surface-recorded posterior AR represents a combination of rhythms, their number as well as their cortical sources require a systematic investigation, which would involve an analytical determination of AR components (ARCs) based on EEG spectra obtained with a high frequency resolution
The decomposition with the parallel factor analysis (PARAFAC) method showed that 26 out of 29 subjects had more than one ARC
Summary
Heterogeneity of the posterior alpha rhythm (AR) is a widely assumed but rarely tested phenomenon. The above findings suggest that the surface-recorded posterior AR represents a combination of rhythms, their number as well as their cortical sources require a systematic investigation, which would involve an analytical determination of AR components (ARCs) based on EEG spectra obtained with a high frequency resolution. Along these lines, Chiang and colleagues[18] studied the AR structure in 1500 healthy subjects by means of cluster analysis. Account the visibility of separate spectral peaks, but underestimated the spatial and temporal dynamics of the AR because of crude spatial sampling (19 electrodes) and short EEG recordings (2 min)
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