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

Show simple item record Gajardo Vidal, Andrea Lorca-Puls, Diego L. Crinion, Jennifer White, Jitrachote Seghier, Mohamed L. Leff, Alex P. Hope, Thomas M.H. Ludersdorfer, Philipp Green, David W. Bowman, Howard Price, Cathy J. 2018-07-18T15:48:15Z 2018-07-18T15:48:15Z 2018-06
dc.identifier.citation Neuropsychologia, 2018, 115, pp.124-133 es_CL
dc.identifier.issn 0028-3932
dc.description.abstract In this study, we hypothesized that if the same deficit can be caused by damage to one or another part of a distributed neural system, then voxel-based analyses might miss critical lesion sites because preservation of each site will not be consistently associated with preserved function. The first part of our investigation used voxelbased multiple regression analyses of data from 359 right-handed stroke survivors to identify brain regions where lesion load is associated with picture naming abilities after factoring out variance related to object recognition, semantics and speech articulation so as to focus on deficits arising at the word retrieval level. A highly significant lesion-deficit relationship was identified in left temporal and frontal/premotor regions. Post-hoc analyses showed that damage to either of these sites caused the deficit of interest in less than half the affected patients (76/162=47%). After excluding all patients with damage to one or both of the identified regions, our second analysis revealed a new region, in the anterior part of the left putamen, which had not been previously detected because many patients had the deficit of interest after temporal or frontal damage that preserved the left putamen. The results illustrate how (i) false negative results arise when the same deficit can be caused by different lesion sites; (ii) some of the missed effects can be unveiled by adopting an iterative approach that systematically excludes patients with lesions to the areas identified in previous analyses, (iii) statistically significant voxel-based lesion-deficit mappings can be driven by a subset of patients; (iv) focal lesions to the identified regions are needed to determine whether the deficit of interest is the consequence of focal damage or 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. es_CL
dc.language.iso en es_CL
dc.subject Anomia es_CL
dc.subject Voxel based lesion-deficit mapping es_CL
dc.subject Voxel-based lesion-symptom mapping es_CL
dc.subject Voxel-based morphometry es_CL
dc.subject Stroke es_CL
dc.subject Word-finding difficulties es_CL
dc.title How distributed processing produces false negatives in voxel-based lesion deficit analyses es_CL
dc.type Article es_CL

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