Large-scale neural dynamics in a shared low-dimensionalstate space reflect cognitive and attentional dynamics

Abstract
Data availability
Article and author information
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Abstract

Cognition and attention arise from the adaptive coordination of neural systems in response to external and internal demands. The low-dimensional latent subspace that underlies large-scale neural dynamics and the relationships of these dynamics to cognitive and attentional states, however, are unknown. We conducted functional magnetic resonance imaging as human participants performed attention tasks, watched comedy sitcom episodes and an educational documentary, and rested. Whole-brain dynamics traversed a common set of latent states that spanned canonical gradients of functional brain organization, with global desynchronization among functional networks modulating state transitions. Neural state dynamics were synchronized across people during engaging movie watching and aligned to narrative event structures. Neural state dynamics reflected attention fluctuations such that different states indicated engaged attention in task and naturalistic contexts whereas a common state indicated attention lapses in both contexts. Together, these results demonstrate that traversals along large-scale gradients of human brain organization reflect cognitive and attentional dynamics.

Data availability

Raw fMRI data from the SitcOm, Nature documentary, Gradual-onset continuous performance task (SONG) dataset are available on OpenNeuro;https://openneuro.org/datasets/ds004592/versions/1.0.1. Behavioral data, processed fMRI output, and main analysis scripts are published on Github; https://github.com/hyssong/neuraldynamics

The following data sets were generated

(2023) SONG dataset
https://doi.org/10.18112/openneuro.ds004592.v1.0.1.

https://openneuro.org/datasets/ds004592/versions/1.0.1

The following previously published data sets were used

1. Nastase SA
2. Liu Y
3. Hillman H
4. Zadbood A
5. Hasenfratz L
6. Keshavarzian N
7. Chen J
8. Honey CJ
9. Yeshurun Y
10. Regev M
11. Nguyen M
12. Chang CHC
13. Baldassano C
14. Lositsky O
15. Simony E
16. Chow MA
17. Leong YC
18. Brooks PP
19. Micciche E
20. Choe G
21. Goldstein A
22. Vanderwal T
23. Halchenko YO
24. Norman KA
25. Hasson U
(2020) Narratives
OpenNeuro.

https://openneuro.org/datasets/ds002345/versions/1.1.4
1. Chen J
2. Leong YC
3. Honey CJ
4. Yong CH
5. Norman KA
6. Hasson U
(2018) Sherlock
OpenNeuro.

https://openneuro.org/datasets/ds001132/versions/1.0.0
(2016) Gradient
Neurovault.

https://neurovault.org/collections/1598/
1. Van Essen DC
2. Smith SM
3. Barch DM
4. Behrens TEJ
5. Yacoub E
6. Ugurbil K
(2017) Young Adult HCP 1200 Subjects Data Release
Human Connectome Project.

https://www.humanconnectome.org/study/hcp-young-adult/document/1200-subjects-data-release
1. Yeo BTT
2. Krienen FM
3. Sepulcre J
4. Sabuncu MR
5. Lashkari D
6. Hollinshead M
7. Roffman JL
8. Smoller JW
9. Zöllei L
10. Polimeni JR
11. Fisch B
12. Liu H
13. Buckner RL
(2011) Cortical Parcellation
Freesurfer.

https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation_Yeo2011
(2020) Subcortical Parcellation
Github.

https://github.com/yetianmed/subcortex
(2021) Narrative Engagement
Github.

https://github.com/hyssong/NarrativeEngagement
1. Schaefer A
2. Kong R
3. Gordon EM
4. Laumann TO
5. Zuo XN
6. Holmes AJ
7. Eickhoff SB
8. Yeo BTT
(2018) Schaefer atlas
Github.

https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal

Article and author information

Author details

Hayoung Song

Department of Psychology, University of Chicago, Chicago, United States

For correspondence
hyssong@uchicago.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-5970-8076
Won Mok Shim

Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea

For correspondence
wonmokshim@skku.edu

Competing interests
The authors declare that no competing interests exist.
Monica D Rosenberg

Department of Psychology, University of Chicago, Chicago, United States

For correspondence
mdrosenberg@uchicago.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-6179-4025

Funding

Institute for Basic Science (R015-D1)

Won Mok Shim

National Research Foundation of Korea (NRF-2019M3E5D2A01060299)

Won Mok Shim

National Research Foundation of Korea (NRF-2019R1A2C1085566)

Won Mok Shim

National Science Foundation (BCS-2043740)

Monica D Rosenberg

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Informed consent and consent to publish were obtained from the participants prior to the experiments, and the possible consequences of the study were explained. The study was approved by the Institutional Review Board of Sungkyunkwan University.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.