Large-scale neural dynamics in a shared low-dimensional state space reflect cognitive and attentional dynamics
- 1. University of Chicago
- 2. Sungkyunkwan University
Description
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 (copy archived at Song, 2023).
The following data sets were generated:
Song H Shim WM Rosenberg MD (2023) OpenNeuro SONG dataset. https://doi.org/10.18112/openneuro.ds004592.v1.0.1
The following previously published data sets were used:
Nastase SA Liu Y Hillman H Zadbood A Hasenfratz L Keshavarzian N Chen J Honey CJ Yeshurun Y Regev M Nguyen M Chang CHC Baldassano C Lositsky O Simony E Chow MA Leong YC Brooks PP Micciche E Choe G Goldstein A Vanderwal T Halchenko YO Norman KA Hasson U (2020) OpenNeuro Narratives: fMRI data for evaluating models of naturalistic language comprehension. https://doi.org/10.18112/openneuro.ds002345.v1.1.4
Chen J Leong YC Honey CJ Yong CH Norman KA Hasson U (2018) OpenNeuro Sherlock. https://doi.org/10.18112/openneuro.ds001132.v1.0.0
Margulies DS Ghosh SS Goulas A Falkiewicz M Huntenburg JM Langs G Bezgin G Eickhoff SB Castellanos FX Petrides M Jefferies E Smallwood J (2016) NeuroVault ID 1598. Situating the default-mode network along a principal gradient of macroscale cortical organization. https://identifiers.org/neurovault.collection:1598
Files
Large-scale-neural-dynamics-in-a-shared-low-dimensional-state-space-reflect-cognitive-and-attentional-dynamics.pdf
Files
(6.7 MB)
| Name | Size | Download all |
|---|---|---|
|
Additional file md5:6a2a9670ef92414dcb8548066b208763 |
208.9 kB | Preview Download |
|
Article md5:3ab8fbfafb62bcc6f5c7802bf49d6a1c |
6.5 MB | Preview Download |
Additional details
Identifiers
- DOI
- 10.7554/eLife.85487
- Other
- oai:uchicago.tind.io:7714
Funding
- Institute for Basic Science
- IBS R015-D1
- National Research Foundation of Korea
- NRF-2019M3E5D2A01060299
- National Research Foundation of Korea
- NRF-2019R1A2C1085566
- National Science Foundation
- BCS-2043740