MARC details
000 -LEADER |
fixed length control field |
03728nam a22005297a 4500 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
200709s20202020 xxu||||| |||| 00| 0 eng d |
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
International Standard Serial Number |
1053-8119 |
024 ## - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1016/j.neuroimage.2020.116806 [doi] |
024 ## - OTHER STANDARD IDENTIFIER |
Standard number or code |
S1053-8119(20)30293-7 [pii] |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
Ovid MEDLINE(R) |
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
PMID |
32278896 |
245 ## - TITLE STATEMENT |
Title |
Functional anomaly mapping reveals local and distant dysfunction caused by brain lesions. |
251 ## - Source |
Source |
Neuroimage. 215:116806, 2020 07 15. |
252 ## - Abbreviated Source |
Abbreviated source |
Neuroimage. 215:116806, 2020 07 15. |
252 ## - Abbreviated Source |
Former abbreviated source |
Neuroimage. 215:116806, 2020 Apr 10. |
253 ## - Journal Name |
Journal name |
NeuroImage |
260 ## - PUBLICATION, DISTRIBUTION, ETC. |
Year |
2020 |
260 ## - PUBLICATION, DISTRIBUTION, ETC. |
Manufacturer |
FY2021 |
265 ## - SOURCE FOR ACQUISITION/SUBSCRIPTION ADDRESS [OBSOLETE] |
Publication status |
aheadofprint |
265 ## - SOURCE FOR ACQUISITION/SUBSCRIPTION ADDRESS [OBSOLETE] |
Publication status |
ppublish |
266 ## - Date added to catalog |
Date added to catalog |
2020-07-09 |
268 ## - Previous citation |
-- |
Neuroimage. 215:116806, 2020 Apr 10. |
520 ## - SUMMARY, ETC. |
Abstract |
The lesion method has been important for understanding brain-behavior relationships in humans, but has previously used maps based on structural damage. Lesion measurement based on structural damage may label partly damaged but functional tissue as abnormal, and moreover, ignores distant dysfunction in structurally intact tissue caused by deafferentation, diaschisis, and other processes. A reliable method to map functional integrity of tissue throughout the brain would provide a valuable new approach to measuring lesions. Here, we use machine learning on four dimensional resting state fMRI data obtained from left-hemisphere stroke survivors in the chronic period of recovery and control subjects to generate graded maps of functional anomaly throughout the brain in individual patients. These functional anomaly maps identify areas of obvious structural lesions and are stable across multiple measurements taken months and even years apart. Moreover, the maps identify functionally anomalous regions in structurally intact tissue, providing a direct measure of remote effects of lesions on the function of distant brain structures. Multivariate lesion-behavior mapping using functional anomaly maps replicates classic behavioral localization, identifying inferior frontal regions related to speech fluency, lateral temporal regions related to auditory comprehension, parietal regions related to phonology, and the hand area of motor cortex and descending corticospinal pathways for hand motor function. Further, this approach identifies relationships between tissue function and behavior distant from the structural lesions, including right premotor dysfunction related to ipsilateral hand movement, and right cerebellar regions known to contribute to speech fluency. Brain-wide maps of the functional effects of focal lesions could have wide implications for lesion-behavior association studies and studies of recovery after brain injury. Copyright (c) 2020 The Author(s). Published by Elsevier Inc. All rights reserved. |
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] |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
*Magnetic Resonance Imaging/mt [Methods] |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
*Stroke/dg [Diagnostic Imaging] |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Adult |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Brain/pa [Pathology] |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Brain/pp [Physiopathology] |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Female |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Humans |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Image Processing, Computer-Assisted |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Machine Learning |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Male |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Middle Aged |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
ROC Curve |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Stroke/pa [Pathology] |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Stroke/pp [Physiopathology] |
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/10.1016/j.neuroimage.2020.116806">https://dx.doi.org/10.1016/j.neuroimage.2020.116806</a> |
Public note |
https://dx.doi.org/10.1016/j.neuroimage.2020.116806 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Koha item type |
Journal Article |
Item type description |
Article |