Evidence map›Paper›PMID 29860082›Full record

ArticleNeuroImage2018

On testing for spatial correspondence between maps of human brain structure and function.

Aaron F Alexander-Bloch, Haochang Shou, Siyuan Liu, Theodore D Satterthwaite, David C Glahn, Russell T Shinohara, Simon N Vandekar, Armin Raznahan

Abstract read
In one paragraph

Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 497 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
497citing papers in PubMed, 7 pooled it
–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

497 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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437 more citing papers are in PubMed but not listed here.

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.

Aaron F Alexander-BlochYale University School of Medicine, Department of Psychiatry, USA. Electronic address: aaron.alexander-bloch@yale.edu.
Haochang ShouUniversity of Pennsylvania Perelman School of Medicine, Department of Biostatistics, Epidemiology, and Informatics, USA.
Siyuan LiuDevelopmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Intramural Program, USA.
Theodore D SatterthwaiteUniversity of Pennsylvania School of Medicine, Department of Psychiatry, USA.
David C GlahnYale University School of Medicine, Department of Psychiatry, USA; Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital, USA.
Russell T ShinoharaUniversity of Pennsylvania Perelman School of Medicine, Department of Biostatistics, Epidemiology, and Informatics, USA.
Simon N VandekarUniversity of Pennsylvania Perelman School of Medicine, Department of Biostatistics, Epidemiology, and Informatics, USA.
Armin RaznahanDevelopmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Intramural Program, USA.

Funding

Section on Developmental NeurogenomicsZIAMH002949 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI RAZNAHAN, ARMIN · 2016 to 2025
$30.0M
Statistical Methods for Multilevel Multivariate Functional StudiesR01NS060910 · NINDS · JOHNS HOPKINS UNIVERSITY · PI Ciprian M Crainiceanu · 2009 to 2026
$8.3M
Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Clinical Neuroscience Research Training Program in PsychiatryT32MH019961 · NIMH · YALE UNIVERSITY · PI Christopher John Pittenger · 1996 to 2026
$5.9M
Longitudinal multi-modal neuroimaging of irritability in youthR01MH107703 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI SATTERTHWAITE, THEODORE · 2015 to 2018
$2.6M
Statistical methods for large and complex databases of ultra-high-dimensionalR01NS085211 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2013 to 2017
$1.8M
Mental Health Biostatistics Training ProgramT32MH065218 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI BILKER, WARREN B. · 2003 to 2018
$1.3M
Intramural NIH HHS ZIA MH002949NIMH NIH HHS R01 MH107703NIMH NIH HHS R01 MH112847NIMH NIH HHS T32 MH019961NIMH NIH HHS T32 MH065218NINDS NIH HHS R01 NS060910NINDS NIH HHS R01 NS085211
6 · The paper itself

Abstract

A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data.

Indexed as

Models, NeurologicalBrainBrain MappingHumansImage Processing, Computer-AssistedNeural Pathways

Identifiers

PMID29860082
PMCPMC6095687

What OpenQuestion holds

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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.