Evidence map›Paper›PMID 37060936›Full record

ArticleNeuroImage2023

Towards reliable reconstruction of the mouse brain corticothalamic connectivity using diffusion MRI.

Tanzil Mahmud Arefin, Choong Heon Lee, Zifei Liang, Harikrishna Rallapalli, Youssef Z Wadghiri, Daniel H Turnbull, Jiangyang Zhang

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

12 citing papers in PubMed, 15 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Tanzil Mahmud ArefinBernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States; Center for Neurotechnology in Mental Health Research, Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, United States.
Choong Heon LeeBernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States.
Zifei LiangBernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States.
Harikrishna RallapalliBernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States.
Youssef Z WadghiriBernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States.
Daniel H TurnbullBernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States.
Jiangyang ZhangBernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States. Electronic address: Jiangyang.zhang@nyulangone.org.
New York University · USAdvanced Imaging Research (United States) · USPennsylvania State University · US

Funding

Vaccine FacilityP30CA016087 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ANIRBAN MAITRA · 1985 to 2026
$83.1M
TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Christopher M Collins · 2014 to 2026
$19.3M
Institutional Clinical and Translational Science AwardUL1TR000038 · NCATS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CRONSTEIN, BRUCE NEIL · 2012 to 2014
$16.8M
Imaging Neonatal Hypoxic Ischemic InjuryR01HD074593 · NICHD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FRANCES J NORTHINGTON, JIANGYANG ZHANG · 2013 to 2026
$6.8M
Establishing Common Coordinate Framework for Quantitative Cell Census in Developing Mouse BrainsRF1MH124605 · NIMH · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI GEE, JAMES C, KIM, YONGSOO · 2020 to 2020
$3.8M
Quantitative Imaging of Mouse Brain DevelopmentR01NS102904 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ZHANG, JIANGYANG · 2018 to 2022
$3.1M
7T Small Animal MRI Scanner Replacement for Translational Imaging ResourceS10OD018337 · OD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BOADA, FERNANDO E · 2014 to 2014
$2.0M
NCATS NIH HHS UL1 TR000038NCI NIH HHS P30 CA016087NIBIB NIH HHS P41 EB017183NICHD NIH HHS R01 HD074593NIH HHS S10 OD018337NIMH NIH HHS RF1 MH124605NINDS NIH HHS R01 NS102904
6 · The paper itself

Abstract

Diffusion magnetic resonance imaging (dMRI) tractography has yielded intriguing insights into brain circuits and their relationship to behavior in response to gene mutations or neurological diseases across a number of species. Still, existing tractography approaches suffer from limited sensitivity and specificity, leading to uncertain interpretation of the reconstructed connections. Hence, in this study, we aimed to optimize the imaging and computational pipeline to achieve the best possible spatial overlaps between the tractography and tracer-based axonal projection maps within the mouse brain corticothalamic network. We developed a dMRI-based atlas of the mouse forebrain with structural labels imported from the Allen Mouse Brain Atlas (AMBA). Using the atlas and dMRI tractography, we first reconstructed detailed node-to-node mouse brain corticothalamic structural connectivity matrices using different imaging and tractography parameters. We then investigated the effects of each condition for accurate reconstruction of the corticothalamic projections by quantifying the similarities between the tractography and the tracer data from the Allen Mouse Brain Connectivity Atlas (AMBCA). Our results suggest that these parameters significantly affect tractography outcomes and our atlas can be used to investigate macroscopic structural connectivity in the mouse brain. Furthermore, tractography in mouse brain gray matter still face challenges and need improved imaging and tractography methods.

Indexed as

Diffusion Tensor ImagingWhite MatterAnimalsAxonsBrainDiffusion Magnetic Resonance ImagingGray MatterMiceSensitivity and SpecificityAnatomically constrained tractographyC57BL/6J mouse brainCorticothalamic networkDiffusion MRIStructural connectivityTractography

Identifiers

PMID37060936
PMCPMC10149621
OpenAlexW4365458813

What OpenQuestion holds

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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.