Evidence map›Paper›PMID 37953850›Full record

ArticleBrain communications2023

Mapping the individual human cortex using multidimensional MRI and unsupervised learning.

Shinjini Kundu, Stephanie Barsoum, Jeanelle Ariza, Amber L Nolan, Caitlin S Latimer, C Dirk Keene, Peter J Basser, Dan Benjamini

Open access · goldAbstract read
In one paragraph

Article in Brain communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

17 citing papers in PubMed, 17 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

8 authors at 3 institutions in 1 country.

Shinjini KunduDepartment of Radiology, The Johns Hopkins Hospital, Baltimore, MD 21287, USA.ORCID https://orcid.org/0000-0003-4930-1851
Stephanie BarsoumMultiscale Imaging and Integrative Biophysics Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD 21224, USA.ORCID https://orcid.org/0009-0003-8135-5590
Jeanelle ArizaDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA.
Amber L NolanDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA.
Caitlin S LatimerDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA.
C Dirk KeeneDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA.
Peter J BasserSection on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD 20892, USA.
Dan BenjaminiMultiscale Imaging and Integrative Biophysics Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD 21224, USA.
University of Washington · USEunice Kennedy Shriver National Institute of Child Health and Human Development · USNational Institute on Aging · US

Funding

University of Washington Alzheimer's Disease Research CenterP30AG066509 · NIA · UNIVERSITY OF WASHINGTON · PI Thomas J. Grabowski · 2020 to 2026
$29.0M
Cortical Somatostatin Interneuron Dysfunction after Trauma: Role in Cognitive FlexibilityK08NS114170 · NINDS · UNIVERSITY OF WASHINGTON · PI NOLAN, AMBER L · 2019 to 2023
$1.0M
NIA NIH HHS P30 AG066509NINDS NIH HHS K08 NS114170
6 · The paper itself

Abstract

Human evolution has seen the development of higher-order cognitive and social capabilities in conjunction with the unique laminar cytoarchitecture of the human cortex. Moreover, early-life cortical maldevelopment has been associated with various neurodevelopmental diseases. Despite these connections, there is currently no noninvasive technique available for imaging the detailed cortical laminar structure. This study aims to address this scientific and clinical gap by introducing an approach for imaging human cortical lamina. This method combines diffusion-relaxation multidimensional MRI with a tailored unsupervised machine learning approach that introduces enhanced microstructural sensitivity. This new imaging method simultaneously encodes the microstructure, the local chemical composition and importantly their correlation within complex and heterogenous tissue. To validate our approach, we compared the intra-cortical layers obtained using our

Indexed as

cortical parcellationdiffusion–relaxationmachine learningmicrostructure imagingmultidimensional MRI

Identifiers

PMID37953850
PMCPMC10638106
OpenAlexW4387420276

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.