Evidence map›Paper›PMID 34390416›Full record

ArticleBrain structure & function2021

Dissecting whole-brain conduction delays through MRI microstructural measures.

Matteo Mancini, Qiyuan Tian, Qiuyun Fan, Mara Cercignani, Susie Y Huang

Abstract read
In one paragraph

Article in Brain structure & function, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

5 authors.

Matteo ManciniDepartment of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK. ingmatteomancini@gmail.com.ORCID http://orcid.org/0000-0001-7194-4568
Qiyuan TianAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.
Qiuyun FanAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.
Mara CercignaniCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK.
Susie Y HuangAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.

Funding

CONNECTOME 2.0: DEVELOPING THE NEXT GENERATION HUMAN MRI SCANNER FOR BRIDGING STUDIES OF THE MICRO-, MESO- AND MACRO-CONNECTOMEU01EB026996 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI BASSER, PETER J., HUANG, SUSIE YI · 2018 to 2022
$14.2M
Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI BRUCE R ROSEN · 2020 to 2026
$10.9M
Project 4P41EB015896 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2012 to 2018
$9.8M
Toward a Validated in Vivo Imaging Marker of Axonal Damage Predictive of Progressive Disability in Multiple SclerosisR01NS118187 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI HUANG, SUSIE YI · 2021 to 2025
$2.8M
Characterizing axonal damage in multiple sclerosis using TractCaliber MRIK23NS096056 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI HUANG, SUSIE YI · 2016 to 2020
$877k
NIBIB NIH HHS P41 EB015896NIBIB NIH HHS P41 EB030006NIBIB NIH HHS U01 EB026996NIH HHS K23-NS096056NIH HHS P41-EB015896NIH HHS P41-EB030006NIH HHS R01-NS118187NIH HHS U01-EB026996NINDS NIH HHS K23 NS096056NINDS NIH HHS R01 NS118187Wellcome TrustWellcome Trust 213722/Z/18/Z
6 · The paper itself

Abstract

Network models based on structural connectivity have been increasingly used as the blueprint for large-scale simulations of the human brain. As the nodes of this network are distributed through the cortex and interconnected by white matter pathways with different characteristics, modeling the associated conduction delays becomes important. The goal of this study is to estimate and characterize these delays directly from the brain structure. To achieve this, we leveraged microstructural measures from a combination of advanced magnetic resonance imaging acquisitions and computed the main determinants of conduction velocity, namely axonal diameter and myelin content. Using the model proposed by Rushton, we used these measures to calculate the conduction velocity and estimated the associated delays using tractography. We observed that both the axonal diameter and conduction velocity distributions presented a rather constant trend across different connection lengths, with resulting delays that scale linearly with the connection length. Relying on insights from graph theory and Kuramoto simulations, our results support the approximation of constant conduction velocity but also show path- and region-specific differences.

Indexed as

BrainWhite MatterAxonsHumansMagnetic Resonance ImagingBrain networksConduction delaysMicrostructureMRIWhite matter

Identifiers

PMID34390416
PMCPMC8448685

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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.