Evidence map›Paper›PMID 42681303›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

A Multiscale Methodology for Mapping Human Neuroanatomy.

Trang Cao, James C Pang, Alex Fornito

Abstract read
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Article in Methods in molecular biology (Clifton, N.J.), 2026. 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

3 authors.

Trang CaoSchool of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne, 3168, Australia. trang.cao@monash.edu.
James C PangSchool of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne, 3168, Australia.
Alex FornitoSchool of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne, 3168, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This chapter describes how to use Mode-based Morphometry (MBM) as a new approach to map anatomical variations in the human brain at multiple spatial scales. This approach overcomes the limitations of conventional approaches, such as surface-based morphometry or voxel-based morphometry, which only consider localized and independent effects at specific brain locations. In contrast, MBM analyzes anatomical group differences of a brain structure as a linear combination of its geometric eigenmodes, which represent intrinsic resonant patterns spanning multiple spatial frequencies that are determined by the geometry of the cortex. Assessing the contributions that each mode makes to the pattern of anatomical differences sheds light on the spatial scales at which such differences are preferentially expressed. MBM can reveal the underlying spatial pattern of group differences, enhance reproducibility, and offer insights into the generative mechanisms that shape the observed differences. Here, we provide step-by-step guideline for conducting an MBM analysis with example data. The approach can be applied to a wide range of anatomical data, given a geometric surface or volume of the structure to derive the geometric eigenmodes.

Indexed as

BrainBrain MappingImage Processing, Computer-AssistedNeuroanatomyAlgorithmsHumansMagnetic Resonance ImagingBrain mappingDisorderGeometric eigenmodesMorphometryMRI

Identifiers

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.