Decomposing the time-frequency representation of EEG using non- negative matrix and multi-way factorization

We demonstrate how non-negative matrix factorization (NMF) can be used to decompose the inter trial phase coherence (ITPC) of multi-channel EEG to yield a unique decomposition of time-frequency signatures present in various degrees in the recording channels. The NMF optimization is easily generalized to a parallel factor (PARAFAC) model to form a non-negative multi-way factorization (NMWF). While the NMF can examine subject specific activities the NMWF can effectively extract the most similar activities across subjects and or conditions. The methods are tested on a proprioceptive stimulus consisting of a weight change in a handheld load. While somatosensory gamma oscillations have previously only been evoked by electrical stimuli we hypothesized that a natural proprioceptive stimulus also would be able to evoke gamma oscillations. ITPC maxima were determined by visual inspection and these results were compared to the NMF and NMWF decompositions. Agreement between the results of the visual pattern inspection and the mathematical decompositions was satisfactory showing two significant coherent activities; the predicted 40Hz activity 60 ms after stimulus onset in the frontal-parietal region contralateral to stimulus side and additionally an unexpected 20Hz activity slightly lateralized in the frontal central region. Consequently, also proprioceptive stimuli are able to elicit evoked gamma activity.