A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Group analysis of ongoing EEG data based on fast double-coupled nonnegative tensor decomposition (2020)


Wang, X., Liu, W., Toiviainen, P., Ristaniemi, T., & Cong, F. (2020). Group analysis of ongoing EEG data based on fast double-coupled nonnegative tensor decomposition. Journal of Neuroscience Methods, 330, Article 108502. https://doi.org/10.1016/j.jneumeth.2019.108502


JYU-tekijät tai -toimittajat


Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Wang, Xiulin; Liu, Wenya; Toiviainen, Petri; Ristaniemi, Tapani; Cong, Fengyu

Lehti tai sarja: Journal of Neuroscience Methods

ISSN: 0165-0270

eISSN: 1872-678X

Julkaisuvuosi: 2020

Volyymi: 330

Artikkelinumero: 108502

Kustantaja: Elsevier BV

Julkaisumaa: Alankomaat

Julkaisun kieli: englanti

DOI: https://doi.org/10.1016/j.jneumeth.2019.108502

Julkaisun avoin saatavuus: Avoimesti saatavilla

Julkaisukanavan avoin saatavuus: Osittain avoin julkaisukanava

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/67020


Tiivistelmä

Background
Ongoing EEG data are recorded as mixtures of stimulus-elicited EEG, spontaneous EEG and noises, which require advanced signal processing techniques for separation and analysis. Existing methods cannot simultaneously consider common and individual characteristics among/within subjects when extracting stimulus-elicited brain activities from ongoing EEG elicited by 512-s long modern tango music.

New method
Aiming to discover the commonly music-elicited brain activities among subjects, we provide a comprehensive framework based on fast double-coupled nonnegative tensor decomposition (FDC-NTD) algorithm. The proposed algorithm with a generalized model is capable of simultaneously decomposing EEG tensors into common and individual components.

Results
With the proposed framework, the brain activities can be effectively extracted and sorted into the clusters of interest. The proposed algorithm based on the generalized model achieved higher fittings and stronger robustness. In addition to the distribution of centro-parietal and occipito-parietal regions with theta and alpha oscillations, the music-elicited brain activities were also located in the frontal region and distributed in the 4–11 Hz band.

Comparison with existing method(s)
The present study, by providing a solution of how to separate common stimulus-elicited brain activities using coupled tensor decomposition, has shed new light on the processing and analysis of ongoing EEG data in multi-subject level. It can also reveal more links between brain responses and the continuous musical stimulus.

Conclusions
The proposed framework based on coupled tensor decomposition can be successfully applied to group analysis of ongoing EEG data, as it can be reliably inferred that those brain activities we obtained are associated with musical stimulus.


YSO-asiasanat: EEG; signaalianalyysi; musiikki; ärsykkeet

Vapaat asiasanat: coupled; music; nonnegative; tensor decomposition; ongoing EEG


Liittyvät organisaatiot


OKM-raportointi: Kyllä

Raportointivuosi: 2020

JUFO-taso: 1


Viimeisin päivitys 2021-07-07 klo 21:31