Evidence map›Paper›PMID 24203652›Full record

ArticleBrain imaging and behavior2014

Graphical neuroimaging informatics: application to Alzheimer's disease.

John Darrell Van Horn, Ian Bowman, Shantanu H Joshi, Vaughan Greer

Abstract read
In one paragraph

Article in Brain imaging and behavior, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

John Darrell Van HornThe Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 North Soto Street - SSB1-102, Los Angeles, CA, 90032, USA, jvanhorn@usc.edu.
Ian Bowman
Shantanu H Joshi
Vaughan Greer

Funding

Multimodal Developmental Neurogenetics of Females with ASDR01MH100028 · NIMH · YALE UNIVERSITY · PI Allison Elizabeth Jack, LAUREN KENWORTHY · 2012 to 2026
$37.8M
TR&D3: Intrinsic Surface MappingP41EB015922 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI VAN HORN, JOHN DARRELL · 2012 to 2022
$14.1M
Informatics Meta-Spaces for the Exploration of Human NeuroanatomyRC1MH088194 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI VAN HORN, JOHN DARRELL · 2009 to 2010
$1000k
NIBIB NIH HHS P41 EB015922NIMH NIH HHS R01 MH100028NIMH NIH HHS RC1 MH088194NIMH NIH HHS RC1MH088194
6 · The paper itself

Abstract

The Informatics Visualization for Neuroimaging (INVIZIAN) framework allows one to graphically display image and meta-data information from sizeable collections of neuroimaging data as a whole using a dynamic and compelling user interface. Users can fluidly interact with an entire collection of cortical surfaces using only their mouse. In addition, users can cluster and group brains according in multiple ways for subsequent comparison using graphical data mining tools. In this article, we illustrate the utility of INVIZIAN for simultaneous exploration and mining a large collection of extracted cortical surface data arising in clinical neuroimaging studies of patients with Alzheimer's Disease, mild cognitive impairment, as well as healthy control subjects. Alzheimer's Disease is particularly interesting due to the wide-spread effects on cortical architecture and alterations of volume in specific brain areas associated with memory. We demonstrate INVIZIAN's ability to render multiple brain surfaces from multiple diagnostic groups of subjects, showcase the interactivity of the system, and showcase how INVIZIAN can be employed to generate hypotheses about the collection of data which would be suitable for direct access to the underlying raw data and subsequent formal statistical analysis. Specifically, we use INVIZIAN show how cortical thickness and hippocampal volume differences between group are evident even in the absence of more formal hypothesis testing. In the context of neurological diseases linked to brain aging such as AD, INVIZIAN provides a unique means for considering the entirety of whole brain datasets, look for interesting relationships among them, and thereby derive new ideas for further research and study.

Indexed as

AgedAgingAlzheimer DiseaseBrainCerebral CortexCognitive DysfunctionDatabases, FactualData MiningGray MatterHippocampusHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingNeuroimagingOrgan SizeUser-Computer Interface

Identifiers

PMID24203652
PMCPMC4012008

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.