Evidence map›Paper›PMID 25300278›Full record

ArticleBrain connectivity2014

Neuronal and physiological correlation to hemodynamic resting-state fluctuations in health and disease.

Alberto L Vazquez, Matthew C Murphy, Seong-Gi Kim

Abstract read
In one paragraph

Article in Brain connectivity, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Spatiotemporal analysis of blood plasma and blood cell flow fluctuations of cerebral microcirculation in anesthetized rats.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023
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  7. Review
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  11. Mesoscale Mapping of Mouse Cortex Reveals Frequency-Dependent Cycling between Distinct Macroscale Functional Modules.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2017
    Article
  12. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alberto L Vazquez1 Department of Bioengineering, University of Pittsburgh , Pittsburgh, Pennsylvania.
Matthew C Murphy
Seong-Gi Kim

Funding

Neurovascular Mechanisms of Layer-specific fMRIR01EB003324 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FUKUDA, MITSUHIRO · 2003 to 2019
$4.7M
Functional relationship between neural, metabolic and hemodynamic responsesK01NS066131 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI VAZQUEZ, ALBERTO L · 2010 to 2014
$617k
NIBIB NIH HHS R01-EB003324NINDS NIH HHS K01 NS066131NINDS NIH HHS K01-NS066131
6 · The paper itself

Abstract

Low-frequency, spatially coherent fluctuations present in functional magnetic resonance imaging time series have had a tremendous impact on brain connectomics. This work aims to explore the degree with which hemodynamic connectivity is associated with neuronal, metabolic, and vascular connectivity measures. For this purpose, GCaMP and nontransgenic mice were used to image neuronal activity and oxidative metabolism activity, respectively, along with blood-oxygenation- and cerebral blood volume (CBV)-sensitive hemodynamic changes from the same animals. Although network clusters calculated using either GCaMP (neuronal activity) or optical imaging of intrinsic signal (OIS)-BOLD (blood oxygenation) data did not exhibit strong spatial similarity, the strengths of node-to-node connectivity measured with these modalities were strongly correlated with one another. This finding suggests that hemodynamic connectivity as measured by blood oxygenation measurements, such as functional connectivity magnetic resonance imaging, is a valuable surrogate for the underlying neuronal connectivity. In nontransgenic animals, greater connectivity correlation was observed between tissue oxidative metabolism (flavoprotein autofluorescence imaging [FAI]) and blood oxygenation measurements, suggesting that metabolic contributions to hemodynamic signals are likely responsible for its significant correlation with neuronal connectivity. Lastly, a mouse model of Alzheimer's disease was used to explore the source of decreases in connectivity reported in these mice, a finding that is thought to be associated with amyloid load-driven metabolic decline. The intercluster connectivity measured by metabolic-sensitive measurements (FAI and OIS-BOLD) was maintained while vascular-only signals (OIS-CBV) provided negligible correlation. Therefore, metabolism-sensitive measurements as used in this work are better positioned to capture changes in neuronal connectivity, such that decreases in hemodynamic connectivity likely reflect decreases in oxidative metabolic function.

Indexed as

Age FactorsAlzheimer DiseaseAmyloid beta-Protein PrecursorAnimalsBrainDisease Models, AnimalHumansImage Processing, Computer-AssistedLuminescent ProteinsMagnetic Resonance ImagingMaleMiceMice, Inbred C57BLMice, TransgenicMutationNeural PathwaysAmyloid beta-Protein PrecursorLuminescent ProteinsOxygenPresenilin-1PSEN1 protein, humancalcium imagingFAIfunctional connectivityGCaMPneuronal activityoptical imagingoxidative metabolismresting state

Identifiers

PMID25300278
PMCPMC4238243

What OpenQuestion holds

Textmetadata
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.