A multivariate lesion symptom mapping toolbox and examination of lesion-volume biases and correction methods in lesion-symptom mapping. (Record no. 3598)

MARC details
000 -LEADER
fixed length control field 03111nam a22004097a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180730s20182018 xxu||||| |||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 1065-9471
024 ## - OTHER STANDARD IDENTIFIER
Standard number or code 10.1002/hbm.24289 [doi]
040 ## - CATALOGING SOURCE
Original cataloging agency Ovid MEDLINE(R)
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
PMID 29972618
245 ## - TITLE STATEMENT
Title A multivariate lesion symptom mapping toolbox and examination of lesion-volume biases and correction methods in lesion-symptom mapping.
251 ## - Source
Source Human Brain Mapping. 39(11):4169-4182, 2018 11.
252 ## - Abbreviated Source
Abbreviated source Hum Brain Mapp. 39(11):4169-4182, 2018 11.
253 ## - Journal Name
Journal name Human brain mapping
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Year 2018
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Manufacturer FY2019
266 ## - Date added to catalog
Date added to catalog 2018-07-30
520 ## - SUMMARY, ETC.
Abstract Copyright (c) 2018 Wiley Periodicals, Inc.
520 ## - SUMMARY, ETC.
Abstract Lesion-symptom mapping has become a cornerstone of neuroscience research seeking to localize cognitive function in the brain by examining the sequelae of brain lesions. Recently, multivariate lesion-symptom mapping methods have emerged, such as support vector regression, which simultaneously consider many voxels at once when determining whether damaged regions contribute to behavioral deficits (Zhang, Kimberg, Coslett, Schwartz, & Wang, ). Such multivariate approaches are capable of identifying complex dependences that traditional mass-univariate approach cannot. Here, we provide a new toolbox for support vector regression lesion-symptom mapping (SVR-LSM) that provides a graphical interface and enhances the flexibility and rigor of analyses that can be conducted using this method. Specifically, the toolbox provides cluster-level family-wise error correction via permutation testing, the capacity to incorporate arbitrary nuisance models for behavioral data and lesion data and makes available a range of lesion volume correction methods including a new approach that regresses lesion volume out of each voxel in the lesion maps. We demonstrate these new tools in a cohort of chronic left-hemisphere stroke survivors and examine the difference between results achieved with various lesion volume control methods. A strong bias was found toward brain wide lesion-deficit associations in both SVR-LSM and traditional mass-univariate voxel-based lesion symptom mapping when lesion volume was not adequately controlled. This bias was corrected using three different regression approaches; among these, regressing lesion volume out of both the behavioral score and the lesion maps provided the greatest sensitivity in analyses.
546 ## - LANGUAGE NOTE
Language note English
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element *Brain Mapping/mt [Methods]
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element *Brain/dg [Diagnostic Imaging]
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Topical term or geographic name entry element Brain/pp [Physiopathology]
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Topical term or geographic name entry element Humans
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Multivariate Analysis
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Neuropsychological Tests
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Regression Analysis
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Support Vector Machine
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Time Factors
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element User-Computer Interface
651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME
Institution MedStar National Rehabilitation Network
657 ## - INDEX TERM--FUNCTION
Medline publication type Journal Article
700 ## - ADDED ENTRY--PERSONAL NAME
Local Authors Turkeltaub, Peter E
790 ## - Authors
All authors DeMarco AT, Turkeltaub PE
856 ## - ELECTRONIC LOCATION AND ACCESS
DOI <a href="https://dx.doi.org/10.1002/hbm.24289">https://dx.doi.org/10.1002/hbm.24289</a>
Public note https://dx.doi.org/10.1002/hbm.24289
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Journal Article
Item type description Article
Holdings
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          MedStar Authors Catalog MedStar Authors Catalog 07/30/2018   29972618 29972618 07/30/2018 07/30/2018 Journal Article

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