Evidence map›Paper›PMID 40837202›Full record

ArticleNeurophotonics2025

Arterial-wall origin and transient dynamics of flow- and vaso-motion activities in the awake mouse brain revealed by laser speckle contrast imaging.

Mia Viuf Skøtt, Vladimir Matchkov, Dmitry D Postnov

Abstract read
In one paragraph

Article in Neurophotonics, 2025. 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

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.

Mia Viuf SkøttAarhus University, Center of Functionally Integrative Neuroscience, Aarhus, Denmark.
Vladimir MatchkovAarhus University, Department of Biomedicine, Aarhus, Denmark.ORCID https://orcid.org/0000-0002-3303-1095
Dmitry D PostnovAarhus University, Center of Functionally Integrative Neuroscience, Aarhus, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Cerebral vasomotion and associated flowmotion are considered crucial for optimal brain perfusion and metabolic regulation, with reduced vasomotion being linked to cerebrovascular and neurodegenerative disorders. However, the underlying mechanisms and spatiotemporal dynamics of cerebral vasomotion are still poorly understood, underscoring the need for further research and methodological approaches for its comprehensive characterization. Aim: We aimed to develop an approach for comprehensively characterizing spatiotemporal vasomotion and flowmotion dynamics and apply it to study resting-state activity at vasomotion frequencies (0.05 to 0.25 Hz) in the awake mouse brain. Approach: Laser speckle contrast imaging (LSCI) was used to image cortical blood flow in awake mice with high spatiotemporal resolution. Pixel-wise wavelet transforms and pulsatility-based segmentation enabled the identification and quantification of transient events at the vasomotion frequency range. Results: We identified both vasomotion and flowmotion events, which displayed intermittent periods of high and low activity lasting Conclusions: Our data suggest the arterial wall origin of transient vasomotion events and their consequent propagation as flowmotion in the awake mouse brain. The combined use of pulsatility imaging, wavelet analysis, and temporal clustering in the LSCI analysis provides a framework for the comprehensive characterization of vasomotion-associated blood flow dynamics.

Indexed as

cerebral blood flowflowmotionlaser speckle contrast imagingvasomotion

Identifiers

PMID40837202
PMCPMC12361817

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.