Spatiotemporal Dynamics of Attention Networks Revealed by Representational Similarity Analysis of EEG and fMRI

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Spatiotemporal Dynamics of Attention Networks Revealed by Representational Similarity Analysis of EEG and fMRI. / Salmela, V.; Salo, E.; Salmi, J.; Alho, K.

In: Cerebral Cortex, Vol. 28, No. 2, 01.02.2018, p. 549-560.

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Salmela, V. ; Salo, E. ; Salmi, J. ; Alho, K. / Spatiotemporal Dynamics of Attention Networks Revealed by Representational Similarity Analysis of EEG and fMRI. In: Cerebral Cortex. 2018 ; Vol. 28, No. 2. pp. 549-560.

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@article{5e8d69f5cb744c3ea19eac544fa5d757,
title = "Spatiotemporal Dynamics of Attention Networks Revealed by Representational Similarity Analysis of EEG and fMRI",
abstract = "The fronto-parietal attention networks have been extensively studied with functional magnetic resonance imaging (fMRI), but spatiotemporal dynamics of these networks are not well understood. We measured event-related potentials (ERPs) with electroencephalography (EEG) and collected fMRI data from identical experiments where participants performed visual and auditory discrimination tasks separately or simultaneously and with or without distractors. To overcome the low temporal resolution of fMRI, we used a novel ERP-based application of multivariate representational similarity analysis (RSA) to parse time-averaged fMRI pattern activity into distinct spatial maps that each corresponded, in representational structure, to a short temporal ERP segment. Discriminant analysis of ERP-fMRI correlations revealed 8 cortical networks - 2 sensory, 3 attention, and 3 other - segregated by 4 orthogonal, temporally multifaceted and spatially distributed functions. We interpret these functions as 4 spatiotemporal components of attention: modality-dependent and stimulus-driven orienting, top-down control, mode transition, and response preparation, selection and execution.",
keywords = "attention, brain networks, EEG, fMRI, representational similarity analysis",
author = "V. Salmela and E. Salo and J. Salmi and K. Alho",
year = "2018",
month = "2",
day = "1",
doi = "10.1093/cercor/bhw389",
language = "English",
volume = "28",
pages = "549--560",
journal = "Cerebral Cortex",
issn = "1047-3211",
number = "2",

}

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TY - JOUR

T1 - Spatiotemporal Dynamics of Attention Networks Revealed by Representational Similarity Analysis of EEG and fMRI

AU - Salmela, V.

AU - Salo, E.

AU - Salmi, J.

AU - Alho, K.

PY - 2018/2/1

Y1 - 2018/2/1

N2 - The fronto-parietal attention networks have been extensively studied with functional magnetic resonance imaging (fMRI), but spatiotemporal dynamics of these networks are not well understood. We measured event-related potentials (ERPs) with electroencephalography (EEG) and collected fMRI data from identical experiments where participants performed visual and auditory discrimination tasks separately or simultaneously and with or without distractors. To overcome the low temporal resolution of fMRI, we used a novel ERP-based application of multivariate representational similarity analysis (RSA) to parse time-averaged fMRI pattern activity into distinct spatial maps that each corresponded, in representational structure, to a short temporal ERP segment. Discriminant analysis of ERP-fMRI correlations revealed 8 cortical networks - 2 sensory, 3 attention, and 3 other - segregated by 4 orthogonal, temporally multifaceted and spatially distributed functions. We interpret these functions as 4 spatiotemporal components of attention: modality-dependent and stimulus-driven orienting, top-down control, mode transition, and response preparation, selection and execution.

AB - The fronto-parietal attention networks have been extensively studied with functional magnetic resonance imaging (fMRI), but spatiotemporal dynamics of these networks are not well understood. We measured event-related potentials (ERPs) with electroencephalography (EEG) and collected fMRI data from identical experiments where participants performed visual and auditory discrimination tasks separately or simultaneously and with or without distractors. To overcome the low temporal resolution of fMRI, we used a novel ERP-based application of multivariate representational similarity analysis (RSA) to parse time-averaged fMRI pattern activity into distinct spatial maps that each corresponded, in representational structure, to a short temporal ERP segment. Discriminant analysis of ERP-fMRI correlations revealed 8 cortical networks - 2 sensory, 3 attention, and 3 other - segregated by 4 orthogonal, temporally multifaceted and spatially distributed functions. We interpret these functions as 4 spatiotemporal components of attention: modality-dependent and stimulus-driven orienting, top-down control, mode transition, and response preparation, selection and execution.

KW - attention

KW - brain networks

KW - EEG

KW - fMRI

KW - representational similarity analysis

UR - http://www.scopus.com/inward/record.url?scp=85041670704&partnerID=8YFLogxK

U2 - 10.1093/cercor/bhw389

DO - 10.1093/cercor/bhw389

M3 - Article

VL - 28

SP - 549

EP - 560

JO - Cerebral Cortex

JF - Cerebral Cortex

SN - 1047-3211

IS - 2

ER -

ID: 17686399