A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening (2020)


Zhu, Y., Zhang, C., Poikonen, H., Toiviainen, P., Huotilainen, M., Mathiak, K., Ristaniemi, T., & Cong, F. (2020). Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening. Brain Topography, 33(3), 289-302. https://doi.org/10.1007/s10548-020-00758-5


JYU-tekijät tai -toimittajat


Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Zhu, Yongjie; Zhang, Chi; Poikonen, Hanna; Toiviainen, Petri; Huotilainen, Minna; Mathiak, Klaus; Ristaniemi, Tapani; Cong, Fengyu

Lehti tai sarja: Brain Topography

ISSN: 0896-0267

eISSN: 1573-6792

Julkaisuvuosi: 2020

Volyymi: 33

Lehden numero: 3

Artikkelin sivunumerot: 289-302

Kustantaja: Springer

Julkaisumaa: Yhdysvallat (USA)

Julkaisun kieli: englanti

DOI: https://doi.org/10.1007/s10548-020-00758-5

Julkaisun avoin saatavuus: Avoimesti saatavilla

Julkaisukanavan avoin saatavuus: Osittain avoin julkaisukanava

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/68037

Rinnakkaistallenteen verkko-osoite (pre-print): https://www.biorxiv.org/content/10.1101/509802v1.abstract


Tiivistelmä

Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that combined music information retrieval with spatial Fourier Independent Components Analysis (spatial Fourier–ICA) to probe the interplay between the spatial profiles and the spectral patterns of the brain network emerging from music listening. Correlation analysis was performed between time courses of brain networks extracted from EEG data and musical feature time series extracted from music stimuli to derive the musical feature related oscillatory patterns in the listening brain. We found brain networks of musical feature processing were frequency-dependent. Musical feature time series, especially fluctuation centroid and key feature, were associated with an increased beta activation in the bilateral superior temporal gyrus. An increased alpha oscillation in the bilateral occipital cortex emerged during music listening, which was consistent with alpha functional suppression hypothesis in task-irrelevant regions. We also observed an increased delta–beta oscillatory activity in the prefrontal cortex associated with musical feature processing. In addition to these findings, the proposed method seems valuable for characterizing the large-scale frequency-dependent brain activity engaged in musical feature processing.


YSO-asiasanat: aivot; aivotutkimus; musiikki; kuunteleminen; taajuus; EEG; aivokuori

Vapaat asiasanat: frequency-specific networks; music information retrieval; EEG; independent components analysis


Liittyvät organisaatiot


OKM-raportointi: Kyllä

Raportointivuosi: 2020

JUFO-taso: 1


Viimeisin päivitys 2021-07-07 klo 21:38