Evidence map›Paper›PMID 37565644›Full record

ArticleeLife2023

Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing.

Sydney M Bailes, Daniel E P Gomez, Beverly Setzer, Laura D Lewis

Open access · goldAbstract read
In one paragraph

Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 20 citations in OpenAlex.

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  11. Hierarchical gradients of multiple timescales in the mammalian forebrain.Proceedings of the National Academy of Sciences of the United States of America · 2024
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  12. Review
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  16. Estimating fMRI timescale maps.Imaging neuroscience (Cambridge, Mass.)
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Sydney M BailesDepartment of Biomedical Engineering, Boston University, Boston, United States.ORCID 0000-0003-1712-9233
Daniel E P GomezDepartment of Biomedical Engineering, Boston University, Boston, United States.
Beverly SetzerDepartment of Biomedical Engineering, Boston University, Boston, United States.
Laura D LewisDepartment of Biomedical Engineering, Boston University, Boston, United States.ORCID 0000-0002-4003-0277
Boston University · US

Funding

Project 4U19NS123717 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI LINNINGER, ANDREAS A · 2021 to 2025
$13.4M
TRAINING PROGRAM IN QUANTITATIVE BIOLOGY AND PHYSIOLOGYT32GM008764 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI WHITE, JOHN A. · 2001 to 2021
$5.9M
Sleep-dependent modulation of cerebrospinal fluid flow in aging and across genetic risk for Alzheimers diseaseR01AG070135 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LEWIS, LAURA DIANE · 2021 to 2025
$3.3M
Imaging neural dynamics at high temporal resolution in sleep and sleep deprivationR00MH111748 · NIMH · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI LEWIS, LAURA DIANE · 2019 to 2021
$746k
NIA NIH HHS R01 AG070135NIH HHS R00-MH111748NIH HHS R01-AG070135NIH HHS T32-GM008764NIH HHS U19-NS123717
6 · The paper itself

Abstract

Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here, we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, because differences in fMRI frequency content can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.

Indexed as

HemodynamicsMagnetic Resonance ImagingBrainBrain MappingGeniculate BodiesHumansBOLDfMRIhemodynamic responsehumanneuroscienceneurovascular couplingresting-state fMRI

Identifiers

PMID37565644
PMCPMC10506795
OpenAlexW4385751356

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.