Skip to main content

How distributed processing produces false negatives in voxel-based lesion-deficit analyses

Gajardo-Vidal, Andrea, Lorca-Puls, Diego L., Crinion, Jennifer T., White, Jitrachote, Seghier, Mohamed L., Leff, Alex P., Hope, Thomas M.H., Ludersdorfer, Philipp, Green, David W., Bowman, Howard, and others. (2018) How distributed processing produces false negatives in voxel-based lesion-deficit analyses. Neuropsychologia, . ISSN 0028-3932. (doi:10.1016/j.neuropsychologia.2018.02.025) (KAR id:66586)

PDF Publisher pdf
Language: English


Download (1MB) Preview
[thumbnail of Gajardo-Vidal false-negatives stroke.pdf]
Preview
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL
https://doi.org/10.1016/j.neuropsychologia.2018.02...

Abstract

In this study, we hypothesized that if the same deficit can be caused by damage to one or another part of a

site will not be consistently associated with preserved function. The first part of our investigation used voxelbased

where lesion load is associated with picture naming abilities after factoring out variance related to object recognition,

significant lesion-deficit relationship was identified in left temporal and frontal/premotor regions. Post-hoc

patients (76/162 = 47%). After excluding all patients with damage to one or both of the identified regions, our

detected because many patients had the deficit of interest after temporal or frontal damage that preserved the

different lesion sites; (ii) some of the missed effects can be unveiled by adopting an iterative approach that

voxel-based lesion-deficit mappings can be driven by a subset of patients; (iv) focal lesions to the

much more extensive damage that includes the identified region; and, finally, (v) univariate voxel-based lesiondeficit

mappings cannot, in isolation, be used to predict outcome in other patients.

Item Type: Article
DOI/Identification number: 10.1016/j.neuropsychologia.2018.02.025
Uncontrolled keywords: Voxel-based lesion-deficit mapping, Voxel-based morphometry, Voxel-based lesion-symptom mapping, stroke, Anomia, Word-finding difficulties
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Howard Bowman
Date Deposited: 29 Mar 2018 11:07 UTC
Last Modified: 16 Feb 2021 13:53 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/66586 (The current URI for this page, for reference purposes)
Bowman, Howard: https://orcid.org/0000-0003-4736-1869
  • Depositors only (login required):

Downloads

Downloads per month over past year