Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

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Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film. / Lahnakoski, Juha M; Salmi, Juha; Jääskeläinen, Iiro P.; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko.

In: PloS one, Vol. 7, No. 4, e35215, 2012, p. 1-14.

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@article{3c5565bed55b4970ac98585f3ac4b935,
title = "Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.",
abstract = "Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.",
author = "Lahnakoski, {Juha M} and Juha Salmi and J{\"a}{\"a}skel{\"a}inen, {Iiro P.} and Jouko Lampinen and Enrico Glerean and Pia Tikka and Mikko Sams",
year = "2012",
doi = "10.1371/journal.pone.0035215",
language = "English",
volume = "7",
pages = "1--14",
journal = "PloS one",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "4",

}

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TY - JOUR

T1 - Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

AU - Lahnakoski, Juha M

AU - Salmi, Juha

AU - Jääskeläinen, Iiro P.

AU - Lampinen, Jouko

AU - Glerean, Enrico

AU - Tikka, Pia

AU - Sams, Mikko

PY - 2012

Y1 - 2012

N2 - Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

AB - Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

UR - http://dx.plos.org/10.1371/journal.pone.0035215

U2 - 10.1371/journal.pone.0035215

DO - 10.1371/journal.pone.0035215

M3 - Article

VL - 7

SP - 1

EP - 14

JO - PloS one

JF - PloS one

SN - 1932-6203

IS - 4

M1 - e35215

ER -

ID: 954762