6533b7cffe1ef96bd125914c
RESEARCH PRODUCT
Semi-blind Independent Component Analysis of functional MRI elicited by continuous listening to music
Petri ToiviainenQiu-hua LinElvira BratticoAsoke K. NandiTapani RistaniemiFengyu CongVinoo AlluriTuomas Puolivälisubject
STIMULATIONComputer scienceSpeech recognitionTIME-SERIES050105 experimental psychologynatural music03 medical and health sciencesMatrix (mathematics)0302 clinical medicinesemi-blindSource separationmedicine0501 psychology and cognitive sciencesActive listeningta113SPATIAL ICAmedicine.diagnostic_test05 social sciencesIndependent component analysisfunctional magnetic resonance imagingacoustic featuresSemi blindindependent component analysisFMRI DATAta6131Functional magnetic resonance imaging030217 neurology & neurosurgerydescription
This study presents a method to analyze blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (tMRI) signals associated with listening to continuous music. Semi-blind independent component analysis (ICA) was applied to decompose the tMRI 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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2013-05-01 |