Evidence map›Paper›PMID 31295567›Full record

ArticleNeuroImage2019

Using machine learning-based lesion behavior mapping to identify anatomical networks of cognitive dysfunction: Spatial neglect and attention.

Daniel Wiesen, Christoph Sperber, Grigori Yourganov, Christopher Rorden, Hans-Otto Karnath

Open access · greenAbstract read
In one paragraph

Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

29 citing papers in PubMed, 49 citations in OpenAlex.

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  18. Indirect structural disconnection-symptom mapping.Brain structure & function · 2022
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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

5 authors at 2 institutions in 2 countries.

Daniel WiesenCenter of Neurology, Division of Neuropsychology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, 72076, Germany.
Christoph SperberCenter of Neurology, Division of Neuropsychology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, 72076, Germany.
Grigori YourganovDepartment of Psychology, University of South Carolina, Columbia, 29208, USA.
Christopher RordenDepartment of Psychology, University of South Carolina, Columbia, 29208, USA.
Hans-Otto KarnathCenter of Neurology, Division of Neuropsychology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, 72076, Germany; Department of Psychology, University of South Carolina, Columbia, 29208, USA. Electronic address: karnath@uni-tuebingen.de.
Hertie Institute for Clinical Brain Research · DEUniversity of South Carolina · US

Funding

Telerehab for Aphasia (TERRA)P50DC014664 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FRIDRIKSSON, JULIUS · 2016 to 2025
$25.0M
A Unified Neuroanatomical Model of Speech Production and Perception: ImplicationsR01DC009571 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FRIDRIKSSON, JULIUS, RORDEN, CHRISTOPHER · 2009 to 2013
$1.6M
Dissociating Components of the Attentional Network in NeglectR01NS054266 · NINDS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI RORDEN, CHRISTOPHER · 2006 to 2010
$1.4M
NIDCD NIH HHS P50 DC014664NIDCD NIH HHS R01 DC009571NINDS NIH HHS R01 NS054266
6 · The paper itself

Abstract

Previous lesion behavior studies primarily used univariate lesion behavior mapping techniques to map the anatomical basis of spatial neglect after right brain damage. These studies led to inconsistent results and lively controversies. Given these inconsistencies, the idea of a wide-spread network that might underlie spatial orientation and neglect has been pushed forward. In such case, univariate lesion behavior mapping methods might have been inherently limited in detecting the presumed network due to limited statistical power. By comparing various univariate analyses with multivariate lesion-mapping based on support vector regression, we aimed to validate the network hypothesis directly in a large sample of 203 newly recruited right brain damaged patients. If the exact same correction factors and parameter combinations (FDR correction and dTLVC for lesion size control) were used, both univariate as well as multivariate approaches uncovered the same complex network pattern underlying spatial neglect. At the cortical level, lesion location dominantly affected the temporal cortex and its borders into inferior parietal and occipital cortices. Beyond, frontal and subcortical gray matter regions as well as white matter tracts connecting these regions were affected. Our findings underline the importance of a right network in spatial exploration and attention and specifically in the emergence of the core symptoms of spatial neglect.

Indexed as

Machine LearningAgedAttentionBrainBrain MappingCognitive DysfunctionFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedPerceptual DisordersStrokeSupport Vector MachineMultivariateSpatial attentionStrokeSupport vector regressionVLSMVoxel-based lesion behavior mapping

Identifiers

PMID31295567
PMCPMC6765420
OpenAlexW2956734430

What OpenQuestion holds

Textmetadata
LicenceTDM
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.