Semi-blind independent component analysis of functional MRI elicited by continuous listening to music

Tuomas Puolivali; Fengyu Cong; Vinoo Alluri; Qiu Hua Lin; Petri Toiviainen; Asoke K. Nandi; Elvira Brattico; Tapani Ristaniemi

doi:10.1109/ICASSP.2013.6637863

Semi-blind independent component analysis of functional MRI elicited by continuous listening to music

Tuomas Puolivali, Fengyu Cong, Vinoo Alluri, Qiu Hua Lin, Petri Toiviainen, Asoke K. Nandi, Elvira Brattico, Tapani Ristaniemi

Neurotieteen ja lääketieteellisen tekniikan laitos

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference contribution › Scientific › vertaisarvioitu

5 Sitaatiot (Scopus)

Abstrakti

This study presents a method to analyze blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals associated with listening to continuous music. Semi-blind independent component analysis (ICA) was applied to decompose the fMRI data to source level activation maps and their respective temporal courses. The unmixing matrix in the source separation process of ICA was constrained by a variety of acoustic features derived from the piece of music used as the stimulus in the experiment. This allowed more stable estimation and extraction of more activation maps of interest compared to conventional ICA methods.

Alkuperäiskieli	Englanti
Otsikko	2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Sivut	1310-1314
Sivumäärä	5
DOI - pysyväislinkit	https://doi.org/10.1109/ICASSP.2013.6637863
Tila	Julkaistu - 18 lokak. 2013
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisuussa
Tapahtuma	IEEE International Conference on Acoustics, Speech, and Signal Processing - Vancouver, Kanada Kesto: 26 toukok. 2013 → 31 toukok. 2013 Konferenssinumero: 38

Julkaisusarja

Nimi	International Conference on Acoustics Speech and Signal Processing ICASSP
ISSN (painettu)	1520-6149

Conference

Conference	IEEE International Conference on Acoustics, Speech, and Signal Processing
Lyhennettä	ICASSP
Maa/Alue	Kanada
Kaupunki	Vancouver
Ajanjakso	26/05/2013 → 31/05/2013

Pääsy asiakirjaan

10.1109/ICASSP.2013.6637863

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Koko teksti

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Puolivali, T., Cong, F., Alluri, V., Lin, Q. H., Toiviainen, P., Nandi, A. K., Brattico, E., & Ristaniemi, T. (2013). Semi-blind independent component analysis of functional MRI elicited by continuous listening to music. teoksessa 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings (Sivut 1310-1314). [6637863] (International Conference on Acoustics Speech and Signal Processing ICASSP). https://doi.org/10.1109/ICASSP.2013.6637863

@inproceedings{0b25dc5b86394c8698af4c466b8defe2,

title = "Semi-blind independent component analysis of functional MRI elicited by continuous listening to music",

abstract = "This study presents a method to analyze blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals associated with listening to continuous music. Semi-blind independent component analysis (ICA) was applied to decompose the fMRI data to source level activation maps and their respective temporal courses. The unmixing matrix in the source separation process of ICA was constrained by a variety of acoustic features derived from the piece of music used as the stimulus in the experiment. This allowed more stable estimation and extraction of more activation maps of interest compared to conventional ICA methods.",

keywords = "acoustic features, functional magnetic, independent component analysis, natural music, resonance imaging, semiblind",

author = "Tuomas Puolivali and Fengyu Cong and Vinoo Alluri and Lin, {Qiu Hua} and Petri Toiviainen and Nandi, {Asoke K.} and Elvira Brattico and Tapani Ristaniemi",

year = "2013",

month = oct,

day = "18",

doi = "10.1109/ICASSP.2013.6637863",

language = "English",

isbn = "9781479903566",

series = "International Conference on Acoustics Speech and Signal Processing ICASSP",

pages = "1310--1314",

booktitle = "2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings",

note = "IEEE International Conference on Acoustics, Speech, and Signal Processing , ICASSP ; Conference date: 26-05-2013 Through 31-05-2013",

}

Puolivali, T, Cong, F, Alluri, V, Lin, QH, Toiviainen, P, Nandi, AK, Brattico, E & Ristaniemi, T 2013, Semi-blind independent component analysis of functional MRI elicited by continuous listening to music. julkaisussa 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings., 6637863, International Conference on Acoustics Speech and Signal Processing ICASSP, Sivut 1310-1314, IEEE International Conference on Acoustics, Speech, and Signal Processing , Vancouver, Kanada, 26/05/2013. https://doi.org/10.1109/ICASSP.2013.6637863

Semi-blind independent component analysis of functional MRI elicited by continuous listening to music. / Puolivali, Tuomas; Cong, Fengyu; Alluri, Vinoo et al.

2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings. 2013. s. 1310-1314 6637863 (International Conference on Acoustics Speech and Signal Processing ICASSP).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference contribution › Scientific › vertaisarvioitu

TY - GEN

T1 - Semi-blind independent component analysis of functional MRI elicited by continuous listening to music

AU - Puolivali, Tuomas

AU - Cong, Fengyu

AU - Alluri, Vinoo

AU - Lin, Qiu Hua

AU - Toiviainen, Petri

AU - Nandi, Asoke K.

AU - Brattico, Elvira

AU - Ristaniemi, Tapani

N1 - Conference code: 38

PY - 2013/10/18

Y1 - 2013/10/18

N2 - This study presents a method to analyze blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals associated with listening to continuous music. Semi-blind independent component analysis (ICA) was applied to decompose the fMRI data to source level activation maps and their respective temporal courses. The unmixing matrix in the source separation process of ICA was constrained by a variety of acoustic features derived from the piece of music used as the stimulus in the experiment. This allowed more stable estimation and extraction of more activation maps of interest compared to conventional ICA methods.

AB - This study presents a method to analyze blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals associated with listening to continuous music. Semi-blind independent component analysis (ICA) was applied to decompose the fMRI data to source level activation maps and their respective temporal courses. The unmixing matrix in the source separation process of ICA was constrained by a variety of acoustic features derived from the piece of music used as the stimulus in the experiment. This allowed more stable estimation and extraction of more activation maps of interest compared to conventional ICA methods.

KW - acoustic features

KW - functional magnetic

KW - independent component analysis

KW - natural music

KW - resonance imaging

KW - semiblind

UR - http://www.scopus.com/inward/record.url?scp=84890496484&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2013.6637863

DO - 10.1109/ICASSP.2013.6637863

M3 - Conference contribution

AN - SCOPUS:84890496484

SN - 9781479903566

T3 - International Conference on Acoustics Speech and Signal Processing ICASSP

SP - 1310

EP - 1314

BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings

T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 26 May 2013 through 31 May 2013

ER -

Puolivali T, Cong F, Alluri V, Lin QH, Toiviainen P, Nandi AK et al. Semi-blind independent component analysis of functional MRI elicited by continuous listening to music. julkaisussa 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings. 2013. s. 1310-1314. 6637863. (International Conference on Acoustics Speech and Signal Processing ICASSP). doi: 10.1109/ICASSP.2013.6637863

Semi-blind independent component analysis of functional MRI elicited by continuous listening to music

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