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

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.