Evidence map›Paper›PMID 36565381›Full record

ArticleNeuroscience bulletin2023

Interaction Between Memory Load and Experimental Design on Brain Connectivity and Network Topology.

Heming Zhang, Xin Di, Bart Rypma, Hang Yang, Chun Meng, Bharat Biswal

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuroscience bulletin, 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
0.6field-weighted citation impact, top 35% 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, 6 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 3 institutions in 2 countries.

Heming ZhangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Xin DiDepartment of Biomedical Engineering, New Jersey Institute of Technology, Newark, 07102, USA.ORCID http://orcid.org/0000-0002-2422-9016
Bart RypmaDepartment of Psychology, University of Texas at Dallas, Dallas, 75390, USA.
Hang YangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Chun MengThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China. chunmeng@uestc.edu.cn.ORCID http://orcid.org/0000-0003-0145-6627
Bharat BiswalThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China. bbiswal@gmail.com.ORCID https://orcid.org/0000-0002-3710-3500
University of Electronic Science and Technology of China · CNNew Jersey Institute of Technology · USThe University of Texas at Dallas · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The conventional approach to investigating functional connectivity in the block-designed study usually concatenates task blocks or employs residuals of task activation. While providing many insights into brain functions, the block design adds more manipulation in functional network analysis that may reduce the purity of the blood oxygenation level-dependent signal. Recent studies utilized one single long run for task trials of the same condition, the so-called continuous design, to investigate functional connectivity based on task functional magnetic resonance imaging. Continuous brain activities associated with the single-task condition can be directly utilized for task-related functional connectivity assessment, which has been examined for working memory, sensory, motor, and semantic task experiments in previous research. But it remains unclear how the block and continuous design influence the assessment of task-related functional connectivity networks. This study aimed to disentangle the separable effects of block/continuous design and working memory load on task-related functional connectivity networks, by using repeated-measures analysis of variance. Across 50 young healthy adults, behavioral results of accuracy and reaction time showed a significant main effect of design as well as interaction between design and load. Imaging results revealed that the cingulo-opercular, fronto-parietal, and default model networks were associated with not only task activation, but significant main effects of design and load as well as their interaction on intra- and inter-network functional connectivity and global network topology. Moreover, a significant behavior-brain association was identified for the continuous design. This work has extended the evidence that continuous design can be used to study task-related functional connectivity and subtle brain-behavioral relationships.

Indexed as

BrainBrain MappingMemory, Short-TermNerve NetNeural PathwaysResearch DesignAnalysis of VarianceFemaleHumansMagnetic Resonance ImagingMaleReproducibility of ResultsYoung AdultBlock designContinuous designFunctional connectivityMemory loadNetwork topologyWorking memory

Identifiers

PMID36565381
PMCPMC10073362
OpenAlexW4312130087

What OpenQuestion holds

Textmetadata
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.