Evidence map›Paper›PMID 41043798›Full record

ArticleNeuroImage2025

HyPER: Region-specific hypersampling of fMRI to resolve low-frequency, respiratory, and cardiac pulsations, revealing age-related differences.

Adam M Wright, Tianyin Xu, Yunjie Tong, Qiuting Wen

Abstract read
In one paragraph

Article in NeuroImage, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Mapping cardiac and respiratory pulsations simultaneously with functional connectivity in the rat brain using zero echo time fMRI.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
    Article
  3. Article
  4. 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

4 authors.

Adam M WrightDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Weldon School of Biomedical Engineering Department, Purdue University, West Lafayette, IN, USA.
Tianyin XuWeldon School of Biomedical Engineering Department, Purdue University, West Lafayette, IN, USA.
Yunjie TongWeldon School of Biomedical Engineering Department, Purdue University, West Lafayette, IN, USA. Electronic address: tong61@purdue.edu.
Qiuting WenDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Weldon School of Biomedical Engineering Department, Purdue University, West Lafayette, IN, USA. Electronic address: wenq@iu.edu.

Funding

Indiana Medical Scientist/Engineer Training ProgramT32GM077229 · NIGMS · INDIANA UNIVERSITY INDIANAPOLIS · PI GASTON, BENJAMIN, HERBERT, BRITTNEY-SHEA · 2008 to 2022
$6.0M
Map Paravascular Fluid Dynamic Signatures of Key Aging and AD Processes Using Dynamics Diffusion-Weighted ImagingRF1AG083762 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI WEN, QIUTING · 2023 to 2023
$2.3M
Image based modeling of biomechanical factors for risk assessment of developing periventricular white matter hyperintensitiesR21AG068962 · NIA · PURDUE UNIVERSITY · PI TONG, YUNJIE · 2021 to 2021
$423k
Clinically feasible functional MRI providing independent assessments of cerebrovascular stiffness and microcirculation in typical aging and Alzheimer's Disease cohortsF30AG084336 · NIA · PURDUE UNIVERSITY · PI Adam M Wright · 2023 to 2026
$216k
NIA NIH HHS F30 AG084336NIA NIH HHS R21 AG068962NIA NIH HHS RF1 AG083762NIGMS NIH HHS T32 GM077229
6 · The paper itself

Abstract

Resting-state functional MRI (fMRI) signals capture physiological processes, including systemic low-frequency oscillations (LFOs), respiration, and cardiac pulsations. These physiological oscillations-often treated as noise in functional connectivity analysis-reflect fundamental aspects of brain physiology and have recently been recognized as key drivers of brain waste clearance. However, these critical physiological signals are obscured in fMRI data due to slow sampling rates (typical repetition time (TR) > 0.8 s), which cause cardiac signal to alias into lower frequencies. To resolve physiological signals in fMRI datasets, we leveraged fast cross-slice sampling within each TR to hypersample the fMRI signal. A key novelty of this study is the development of a region-specific hypersampling approach, called HyPER (Hypersampling for Physiological signal Extraction in a Region-specific manner). HyPER enhances temporal resolution within coherently pulsating vascular and tissue compartments, including the major cerebral arteries, the superior sagittal sinus (SSS), gray matter (GM), and white matter (WM). This study is structured in three parts: (1) We developed and validated the HyPER approach using fast fMRI from a local dataset in four regions of interest: the major cerebral arteries, SSS, GM, and WM. (2) We applied this approach to the publicly available Human Connectome Project-Aging (HCP-A) dataset (ages 36-90 years), increasing the resolvable frequency by ninefold-from 0.625 Hz to 5.625 Hz-enabling clear separation of cardiac, respiration, and LFO oscillations. (3) We investigated how brain physiological pulsations change with age. Our findings revealed an age-related increase in cardiac and respiratory pulsations across all brain regions, likely reflecting an increased vessel stiffness and reduced dampening of high-frequency pulsations along the vascular network. In contrast, LFO pulsations generally declined with age, suggesting reduced vasomotion in the older brain. In summary, we demonstrated the feasibility and reliability of a region-specific hypersampling technique to resolve physiological pulsations in fMRI. This method can be broadly applied to existing fMRI datasets to uncover hidden physiological pulsations and advance our understanding of brain physiology and disease-related alterations.

Indexed as

AgingBrainImage Processing, Computer-AssistedMagnetic Resonance ImagingRespirationAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedYoung AdultAgingBrain physiological oscillationsCardiac pulsationHypersampled fMRILow-frequency oscillationRespiratory oscillation

Identifiers

PMID41043798
PMCPMC13157684

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.