matlab based lesion segmentation toolbox Search Results


lesion symptom mapping svr lsm toolbox in matlab  (MathWorks Inc)
96
MathWorks Inc lesion symptom mapping svr lsm toolbox in matlab
A. Lesion overlay map (N=36). B. <t>SVR-LSM</t> results showing lesion locations associated with higher reports of sIS, IwW, and ToT (p < .01, see figure legend for color representations). C. SVR-LSM results at p < .10 to illustrate the minimal overlap between lesions associated with sIS and IwW. Total lesion volume was controlled in both maps, using the direct lesion volume control method.
Lesion Symptom Mapping Svr Lsm Toolbox In Matlab, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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matlab-based toolbox  (MathWorks Inc)
90
MathWorks Inc matlab-based toolbox
A. Lesion overlay map (N=36). B. <t>SVR-LSM</t> results showing lesion locations associated with higher reports of sIS, IwW, and ToT (p < .01, see figure legend for color representations). C. SVR-LSM results at p < .10 to illustrate the minimal overlap between lesions associated with sIS and IwW. Total lesion volume was controlled in both maps, using the direct lesion volume control method.
Matlab Based Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/matlab-based toolbox/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
matlab-based toolbox - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier

Image Search Results


A. Lesion overlay map (N=36). B. SVR-LSM results showing lesion locations associated with higher reports of sIS, IwW, and ToT (p < .01, see figure legend for color representations). C. SVR-LSM results at p < .10 to illustrate the minimal overlap between lesions associated with sIS and IwW. Total lesion volume was controlled in both maps, using the direct lesion volume control method.

Journal: Brain and language

Article Title: Subjective experience of inner speech in aphasia: Preliminary behavioral relationships and neural correlates

doi: 10.1016/j.bandl.2016.09.009

Figure Lengend Snippet: A. Lesion overlay map (N=36). B. SVR-LSM results showing lesion locations associated with higher reports of sIS, IwW, and ToT (p < .01, see figure legend for color representations). C. SVR-LSM results at p < .10 to illustrate the minimal overlap between lesions associated with sIS and IwW. Total lesion volume was controlled in both maps, using the direct lesion volume control method.

Article Snippet: This was performed using the support vector regression-based lesion-symptom mapping (SVR-LSM) toolbox in MATLAB ( https://cfn.upenn.edu/~zewang/ ), which is more resistant than voxel-based lesion-symptom mapping to theoretical bias in localization due to lesion covariance, especially when behaviors rely on multiple distinct brain regions ( Herbet, Lafargue, & Duffau, 2015 ; Mah, Husain, Rees, & Nachev, 2014 ).

Techniques:

SVR-LSM results showing significant clusters (threshold = 200 mm 3 ) at a threshold of P <.01.

Journal: Brain and language

Article Title: Subjective experience of inner speech in aphasia: Preliminary behavioral relationships and neural correlates

doi: 10.1016/j.bandl.2016.09.009

Figure Lengend Snippet: SVR-LSM results showing significant clusters (threshold = 200 mm 3 ) at a threshold of P <.01.

Article Snippet: This was performed using the support vector regression-based lesion-symptom mapping (SVR-LSM) toolbox in MATLAB ( https://cfn.upenn.edu/~zewang/ ), which is more resistant than voxel-based lesion-symptom mapping to theoretical bias in localization due to lesion covariance, especially when behaviors rely on multiple distinct brain regions ( Herbet, Lafargue, & Duffau, 2015 ; Mah, Husain, Rees, & Nachev, 2014 ).

Techniques: