The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study

Tommi Mononen; Jan Kujala; Mia Liljeström; Eemeli Leppäaho; Samuel Kaski; Riitta Salmelin

doi:10.3389/fnins.2022.1019572

The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study

Tommi Mononen^*, Jan Kujala, Mia Liljeström, Eemeli Leppäaho, Samuel Kaski, Riitta Salmelin

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

2 Citations (Scopus)

112 Downloads (Pure)

Abstract

Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relationship between electromagnetic and hemodynamic measures have revealed correlated patterns across brain regions but the role of the applied stimulation or experimental tasks in these correlation patterns is still poorly understood. Here, we evaluated the across-tasks variability of MEG-fMRI relationship using data recorded during three distinct naming tasks (naming objects and actions from action images, and objects from object images), from the same set of participants. Our results demonstrate that the MEG-fMRI correlation pattern varies according to the performed task, and that this variability shows distinct spectral profiles across brain regions. Notably, analysis of the MEG data alone did not reveal modulations across the examined tasks in the time-frequency windows emerging from the MEG-fMRI correlation analysis. Our results suggest that the electromagnetic-hemodynamic correlation could serve as a more sensitive proxy for task-dependent neural engagement in cognitive tasks than isolated within-modality measures.

Original language	English
Article number	1019572
Pages (from-to)	1-16
Number of pages	16
Journal	Frontiers in Neuroscience
Volume	16
DOIs	https://doi.org/10.3389/fnins.2022.1019572
Publication status	Published - 3 Nov 2022
MoE publication type	A1 Journal article-refereed

Funding

This work was financially supported by the Academy of Finland (Finnish Center of Excellence in Computational Inference Research COIN and grants #292334, #294238 to SK; #255349, #315553 to RS; #257576 to JK; #286405 funding for TM), the Sigrid Jusélius Foundation (grant to RS), the Finnish Cultural Foundation (grant to ML), the Swedish Cultural Foundation in Finland (grant to ML), the Maud Kuistila Memorial Foundation (grant to ML), and Aalto Brain Center.

Keywords

clustering
correlation patterns
data fusion
fMRI
MEG
multimodal data
picture naming

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-: Individual cortical markers of language function
Salmelin, R. (Principal investigator), Hukari, A. (Project Member), Saarinen, T. (Project Member), Liljeström, M. (Project Member), Mäkelä, S. (Project Member), Rinkinen, O. (Project Member), Ghazaryan, G. (Project Member) & Cotroneo, S. (Project Member)
01/09/2018 → 31/12/2022
Project: Academy of Finland: Other research funding
Interactive machine learning from multiple biodata sources
Kaski, S. (Principal investigator) & Filstroff, L. (Project Member)
01/01/2016 → 31/08/2021
Project: Academy of Finland: Other research funding
Interactive machine learning from multiple biodata sources
Kaski, S. (Principal investigator), Musaev, M. (Project Member), Hegde, P. (Project Member), Rogers-Smith, C. (Project Member), Aushev, A. (Project Member), Chen, Y. (Project Member), Afrabandpey, H. (Project Member), Bhat, A. (Project Member), Çelikok, M. M. (Project Member), Kaurila, K. (Project Member), Siren, J. (Project Member), Blomstedt, P. (Project Member), Qin, X. (Project Member), Jälkö, J. (Project Member), Eranti, P. (Project Member), Honkamaa, J. (Project Member), Sundin, I. (Project Member), Peltola, T. (Project Member), Shen, Z. (Project Member), Blomqvist, K. (Project Member), Kangas, J.-K. (Project Member), Daee, P. (Project Member), Pesonen, H. (Project Member) & Reinvall, J. (Project Member)
01/01/2016 → 31/12/2018
Project: Academy of Finland: Other research funding

Aalto Neuroimaging Infrastructure
Jousmäki, V. (Manager)
School of Science
Facility/equipment: Facility

Aalto University School of Science and Technology Researchers Focus on Neuroscience (The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal ...)
Salmelin, R. & Kaski, S.
17/11/2022
1 item of Media coverage
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Cite this

Mononen, T., Kujala, J., Liljeström, M., Leppäaho, E., Kaski, S., & Salmelin, R. (2022). The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study. Frontiers in Neuroscience, 16, 1-16. Article 1019572. https://doi.org/10.3389/fnins.2022.1019572

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title = "The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study",

abstract = "Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relationship between electromagnetic and hemodynamic measures have revealed correlated patterns across brain regions but the role of the applied stimulation or experimental tasks in these correlation patterns is still poorly understood. Here, we evaluated the across-tasks variability of MEG-fMRI relationship using data recorded during three distinct naming tasks (naming objects and actions from action images, and objects from object images), from the same set of participants. Our results demonstrate that the MEG-fMRI correlation pattern varies according to the performed task, and that this variability shows distinct spectral profiles across brain regions. Notably, analysis of the MEG data alone did not reveal modulations across the examined tasks in the time-frequency windows emerging from the MEG-fMRI correlation analysis. Our results suggest that the electromagnetic-hemodynamic correlation could serve as a more sensitive proxy for task-dependent neural engagement in cognitive tasks than isolated within-modality measures.",

keywords = "clustering, correlation patterns, data fusion, fMRI, MEG, multimodal data, picture naming",

author = "Tommi Mononen and Jan Kujala and Mia Liljestr{\"o}m and Eemeli Lepp{\"a}aho and Samuel Kaski and Riitta Salmelin",

note = "Funding Information: This work was financially supported by the Academy of Finland (Finnish Center of Excellence in Computational Inference Research COIN and grants \#292334, \#294238 to SK; \#255349, \#315553 to RS; \#257576 to JK; \#286405 funding for TM), the Sigrid Jus{\'e}lius Foundation (grant to RS), the Finnish Cultural Foundation (grant to ML), the Swedish Cultural Foundation in Finland (grant to ML), the Maud Kuistila Memorial Foundation (grant to ML), and Aalto Brain Center. Publisher Copyright: Copyright {\textcopyright} 2022 Mononen, Kujala, Liljestr{\"o}m, Lepp{\"a}aho, Kaski and Salmelin.",

year = "2022",

month = nov,

day = "3",

doi = "10.3389/fnins.2022.1019572",

language = "English",

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journal = "Frontiers in Neuroscience",

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Mononen, T, Kujala, J , Liljeström, M, Leppäaho, E, Kaski, S & Salmelin, R 2022, 'The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study', Frontiers in Neuroscience, vol. 16, 1019572, pp. 1-16. https://doi.org/10.3389/fnins.2022.1019572

The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study. / Mononen, Tommi; Kujala, Jan ; Liljeström, Mia et al.
In: Frontiers in Neuroscience, Vol. 16, 1019572, 03.11.2022, p. 1-16.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study

AU - Mononen, Tommi

AU - Kujala, Jan

AU - Liljeström, Mia

AU - Leppäaho, Eemeli

AU - Kaski, Samuel

AU - Salmelin, Riitta

N1 - Funding Information: This work was financially supported by the Academy of Finland (Finnish Center of Excellence in Computational Inference Research COIN and grants #292334, #294238 to SK; #255349, #315553 to RS; #257576 to JK; #286405 funding for TM), the Sigrid Jusélius Foundation (grant to RS), the Finnish Cultural Foundation (grant to ML), the Swedish Cultural Foundation in Finland (grant to ML), the Maud Kuistila Memorial Foundation (grant to ML), and Aalto Brain Center. Publisher Copyright: Copyright © 2022 Mononen, Kujala, Liljeström, Leppäaho, Kaski and Salmelin.

PY - 2022/11/3

Y1 - 2022/11/3

N2 - Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relationship between electromagnetic and hemodynamic measures have revealed correlated patterns across brain regions but the role of the applied stimulation or experimental tasks in these correlation patterns is still poorly understood. Here, we evaluated the across-tasks variability of MEG-fMRI relationship using data recorded during three distinct naming tasks (naming objects and actions from action images, and objects from object images), from the same set of participants. Our results demonstrate that the MEG-fMRI correlation pattern varies according to the performed task, and that this variability shows distinct spectral profiles across brain regions. Notably, analysis of the MEG data alone did not reveal modulations across the examined tasks in the time-frequency windows emerging from the MEG-fMRI correlation analysis. Our results suggest that the electromagnetic-hemodynamic correlation could serve as a more sensitive proxy for task-dependent neural engagement in cognitive tasks than isolated within-modality measures.

AB - Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relationship between electromagnetic and hemodynamic measures have revealed correlated patterns across brain regions but the role of the applied stimulation or experimental tasks in these correlation patterns is still poorly understood. Here, we evaluated the across-tasks variability of MEG-fMRI relationship using data recorded during three distinct naming tasks (naming objects and actions from action images, and objects from object images), from the same set of participants. Our results demonstrate that the MEG-fMRI correlation pattern varies according to the performed task, and that this variability shows distinct spectral profiles across brain regions. Notably, analysis of the MEG data alone did not reveal modulations across the examined tasks in the time-frequency windows emerging from the MEG-fMRI correlation analysis. Our results suggest that the electromagnetic-hemodynamic correlation could serve as a more sensitive proxy for task-dependent neural engagement in cognitive tasks than isolated within-modality measures.

KW - clustering

KW - correlation patterns

KW - data fusion

KW - fMRI

KW - MEG

KW - multimodal data

KW - picture naming

UR - https://www.scopus.com/pages/publications/85142148763

U2 - 10.3389/fnins.2022.1019572

DO - 10.3389/fnins.2022.1019572

M3 - Article

AN - SCOPUS:85142148763

SN - 1662-4548

VL - 16

SP - 1

EP - 16

JO - Frontiers in Neuroscience

JF - Frontiers in Neuroscience

M1 - 1019572

ER -

The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study

Abstract

Funding

Keywords

Access to Document

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Fingerprint

Projects

-: Individual cortical markers of language function

Interactive machine learning from multiple biodata sources

Interactive machine learning from multiple biodata sources

Equipment

Aalto Neuroimaging Infrastructure

Press/Media

Aalto University School of Science and Technology Researchers Focus on Neuroscience (The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal ...)

Cite this