Evidence map›Paper›PMID 41353503›Full record

ArticleScientific reports2025

Temporal and spatial characterization of physiological noise in rs-fMRI at a high temporal resolution.

Olga Kuldavletova, Marin Mauboussin, Mikael Naveau, Anais Vandevelde, Nicolas Delcroix, Marc Joliot, Olivier Etard

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Olga KuldavletovaNormandie Université, UNICAEN, INSERM, COMETE, CYCERON, CHU Caen, Caen, France. olga.kuldavletova@unicaen.fr.
Marin MauboussinNormandie Université, UNICAEN, INSERM, COMETE, CYCERON, CHU Caen, Caen, France.
Mikael NaveauNormandie Université, UNICAEN, CNRS, INSERM, CYCERON, Caen, UAR3408/US50, France.
Anais VandeveldeCHRU de Tours, Tours, France.
Nicolas DelcroixNormandie Université, UNICAEN, CNRS, INSERM, CYCERON, Caen, UAR3408/US50, France.
Marc JoliotGIN, IMN, UMR5293, CEA, CNRS, Université de Bordeaux, Bordeaux, France.
Olivier EtardNormandie Université, UNICAEN, INSERM, COMETE, CYCERON, CHU Caen, Caen, France.

Funding

Agence Nationale de la Recherche ANR-11-INBS-0006 and ANR-24-CE19-4467
6 · The paper itself

Abstract

The fMRI signal contains "noise" components resulting from physiological processes that interfere with the component due to neuronal activation and obscure the understanding of brain function. Having the neuronal activation component as the unknown, it is crucial to characterize the spatial and temporal aspects of the signal component that is due to cardiac and breathing cycles. 17 fMRI exams were performed in 9 subjects with a 3T Philipps MRI scanner with high sampling frequency (repetition time 125 ms, one slice). Photoplethysmography was used to track the cardiac cycle, and a pneumatic thoracic respiration transducer was used to measure the breathing cycle. The impact of the physiological signal on fMRI signal was evaluated in four regions of interest: (1) a region encompassing all areas below the subarachnoid space (Global Signal - GS), (2) ventricles (CSF), (3) venous return (VR), and (4) the region surrounding Middle Cerebral Arteries (MCA). Physiological noise is found heterogeneous across the ROIs in terms of amplitude and phase. The impact of respiration on the fMRI signal is greater than that of the heart, and it may be mediated by modulation of the venous return.

Indexed as

BrainMagnetic Resonance ImagingAdultBrain MappingFemaleHumansMaleMiddle AgedRespirationYoung AdultCardiac cycle. cerebral blood flowFMRI noisePhysiological noiseRespiratory cycle

Identifiers

PMID41353503
PMCPMC12796172

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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.