Evidence map›Paper›PMID 41601563›Full record

ArticleIBRO neuroscience reports2025

Mapping longitudinally consistent intrinsic connectivity networks in macaque brain via longitudinal sparse dictionary learning.

Arif Hassan Zidan, Afrar Jahin, Yu Bao, Wei Zhang

Abstract read
In one paragraph

Article in IBRO neuroscience 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

4 authors.

Arif Hassan ZidanSchool of Computer and Cyber Sciences, Augusta University, United States.
Afrar JahinSchool of Computer and Cyber Sciences, Augusta University, United States.
Yu BaoDepartment of Graduate Psychology, James Madison University, United States.
Wei ZhangSchool of Computer and Cyber Sciences, Augusta University, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mapping consistent longitudinal intrinsic connectivity networks (ICNs) is crucial for understanding brain functional development over various life stages. However, achieving consistent longitudinal ICNs has been challenging due to the lack of methodologies that maintain temporal consistency. To address this gap, we introduce an innovative approach named Longitudinal Sparse Dictionary Learning (LSDL). This method utilizes an additional Frobenius norm to bridge gaps between consecutive ICNs, facilitating the continuous transfer of the learned feature matrix to subsequent stages. Moreover, Matrix Backpropagation (MBP) is employed to effectively mitigate potential accumulative errors. Our validation results demonstrate that

Indexed as

connectome scaleintrinsic connectivity networkLongitudinal consistencymacaqueresting-state fMRIsparse dictionary learning

Identifiers

PMID41601563
PMCPMC12834029

What OpenQuestion holds

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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.