Evidence map›Paper›PMID 37851793›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2023

Multifractal long-range dependence pattern of functional magnetic resonance imaging in the human brain at rest.

Sihai Guan, Runzhou Jiang, Donna Y Chen, Andrew Michael, Chun Meng, Bharat Biswal

Open access · bronzeAbstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
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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

6 authors at 4 institutions in 2 countries.

Sihai GuanCollege of Electronic and Information, Southwest Minzu University, Chengdu 610041, China.
Runzhou JiangSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
Donna Y ChenDepartment of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Andrew MichaelDuke Institute for Brain Sciences, Duke University, Durham, NC 27708, United States.
Chun MengSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
Bharat BiswalSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
New Jersey Institute of Technology · USUniversity of Electronic Science and Technology of China · CNDuke University · USSouthwest Minzu University · CN

Funding

Functional Connectivity and Baseline Networks of the White Matter Brain: Development and Dissemination of Algorithms and ToolsR01MH131335 · NIMH · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI BISWAL, BHARAT BHUSAN · 2022 to 2025
$2.1M
Fundamental Research Funds for the Central Universities, Southwest Minzu University ZYN2023100, 2021XJTD01Introduction of Talent, Southwest Minzu University RQD2021064Key Research and Development Program of Guangxi 2021AB05083National Key Research and Development Program of China 2022YFE0134600, 2021YFA0715404National Natural Science Foundation of China 62171101, 82250410380NIMH NIH HHS R01 MH131335Sichuan Science and Technology Program 23NSFSC2916
6 · The paper itself

Abstract

Long-range dependence is a prevalent phenomenon in various biological systems that characterizes the long-memory effect of temporal fluctuations. While recent research suggests that functional magnetic resonance imaging signal has fractal property, it remains unknown about the multifractal long-range dependence pattern of resting-state functional magnetic resonance imaging signals. The current study adopted the multifractal detrended fluctuation analysis on highly sampled resting-state functional magnetic resonance imaging scans to investigate long-range dependence profile associated with the whole-brain voxels as specific functional networks. Our findings revealed the long-range dependence's multifractal properties. Moreover, long-term persistent fluctuations are found for all stations with stronger persistency in whole-brain regions. Subsets with large fluctuations contribute more to the multifractal spectrum in the whole brain. Additionally, we found that the preprocessing with band-pass filtering provided significantly higher reliability for estimating long-range dependence. Our validation analysis confirmed that the optimal pipeline of long-range dependence analysis should include band-pass filtering and removal of daily temporal dependence. Furthermore, multifractal long-range dependence characteristics in healthy control and schizophrenia are different significantly. This work has provided an analytical pipeline for the multifractal long-range dependence in the resting-state functional magnetic resonance imaging signal. The findings suggest differential long-memory effects in the intrinsic functional networks, which may offer a neural marker finding for understanding brain function and pathology.

Indexed as

BrainBrain MappingHumansMagnetic Resonance ImagingReproducibility of ResultsDTDhealthy control and schizophreniamultifractal LRDrs-fMRItest–retest reliability

Identifiers

PMID37851793
PMCPMC13370252
OpenAlexW4387729940

What OpenQuestion holds

Textmetadata
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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.