Evidence map›Paper›PMID 37961684›Full record

ArticlebioRxiv : the preprint server for biology2023

The biological role of local and global fMRI BOLD signal variability in human brain organization.

Giulia Baracchini, Yigu Zhou, Jason da Silva Castanheira, Justine Y Hansen, Jenny Rieck, Gary R Turner, Cheryl L Grady, Bratislav Misic, Jason Nomi, Lucina Q Uddin and 1 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Giulia BaracchiniMontreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.ORCID 0000-0001-9198-2780
Yigu ZhouMontreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
Jason da Silva CastanheiraMontreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.ORCID 0000-0002-7022-9009
Justine Y HansenMontreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
Jenny RieckHealth Canada, Ottawa, ON, Canada.ORCID 0000-0002-3242-6407
Gary R TurnerDepartment of Psychology, York University, Toronto, ON, Canada.
Cheryl L GradyRotman Research Institute at Baycrest, and Department of Psychiatry and Psychology, University of Toronto, Toronto, ON, Canada.
Bratislav MisicMontreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
Jason NomiDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, USA.
Lucina Q UddinDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, USA.
R Nathan SprengMontreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.ORCID 0000-0003-1530-8916

Funding

Investigating the impact of loneliness on brain aging and pre-symptomatic Alzheimer's disease progressionR01AG068563 · NIA · MCGILL UNIVERSITY · PI BZDOK, DANILO, SPRENG, ROBERT NATHAN · 2020 to 2024
$2.3M
3T MR scanner for imaging from mouse to humanS10RR025145 · NCRR · CORNELL UNIVERSITY · PI WANG, YI · 2009 to 2009
$2.0M
NCRR NIH HHS S10 RR025145NIA NIH HHS R01 AG068563
6 · The paper itself

Abstract

Variability drives the organization and behavior of complex systems, including the human brain. Understanding the variability of brain signals is thus necessary to broaden our window into brain function and behavior. Few empirical investigations of macroscale brain signal variability have yet been undertaken, given the difficulty in separating biological sources of variance from artefactual noise. Here, we characterize the temporal variability of the most predominant macroscale brain signal, the fMRI BOLD signal, and systematically investigate its statistical, topographical and neurobiological properties. We contrast fMRI acquisition protocols, and integrate across histology, microstructure, transcriptomics, neurotransmitter receptor and metabolic data, fMRI static connectivity, and empirical and simulated magnetoencephalography data. We show that BOLD signal variability represents a spatially heterogeneous, central property of multi-scale multi-modal brain organization, distinct from noise. Our work establishes the biological relevance of BOLD signal variability and provides a lens on brain stochasticity across spatial and temporal scales.

Identifiers

PMID37961684
PMCPMC10634715

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.