31.1668, FYI: Online 5/21: Maria Ivanova, lesion symptom mapping

[The LINGUIST List]

LINGUIST List: Vol-31-1668. Mon May 18 2020. ISSN: 1069 - 4875.

Subject: 31.1668, FYI:  Online 5/21: Maria Ivanova, lesion symptom mapping

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Date: Mon, 18 May 2020 14:08:14
From: Dirk Den Ouden [denouden at sc.edu]
Subject: Online 5/21: Maria Ivanova, lesion symptom mapping

 
Thursday, May 21st, 2020, 2pm ET
http://cstar.sc.edu/lecture-series/

Advancing our understanding of lesion symptom mapping tools:  An empirical
comparison of univariate versus multivariate methods

Maria Ivanova, Ph.D
University of California Berkeley

Lesion-symptom mapping tools are widely used to identify the neural structures
critical for a given behavior.  Some studies have claimed that novel
multivariate lesion-symptom mapping methods, that consider the effects of all
lesioned voxels on behavior in one model simultaneously, should be superior to
traditional univariate approaches, that compare performance serially on a
voxel by voxel basis.  However, many of these arguments have been presented
theoretically without rigorously comparing the two approaches.  In my talk I
will discuss our current work that aimed to address these knowledge gaps and
provide a comprehensive empirical appraisal of several univariate and
multivariate methods with a large stroke lesion dataset, using both synthetic
and real behavioral data, across a range of relevant parameters.  Our results
showed no clear superiority of either univariate or multivariate methods
overall, as accuracy of methods varied differentially depending on specific
conditions.  I will conclude by outlining limitations and advantages of
different approaches and highlighting methodological implications of our
findings for enhancing accuracy and robustness of future lesion-symptom
mapping work.

This lecture can be followed online from your computer, tablet or smartphone,
via a link that will be provided on the C-STAR website:
http://cstar.sc.edu/lecture-series/
 



Linguistic Field(s): Clinical Linguistics
                     Cognitive Science
                     Neurolinguistics





 



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