Distinguishing the effect of lesion load from tract disconnection in the arcuate and uncinate fasciculi
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Brain imaging studies of functional outcomes after white matter damage have quantified the severity of white matter damage in different ways. Here we compared how the outcome of such studies depends on two different types of measurements: the proportion of the target tract that has been destroyed ('lesion load') and tract disconnection. We demonstrate that conclusions from analyses based on two examples of these measures diverge and that conclusions based solely on lesion load may be misleading. First, we reproduce a recent lesion-load-only analysis which suggests that damage to the arcuate fasciculus, and not to the uncinate fasciculus, is significantly associated with deficits in fluency and naming skills. Next, we repeat the analysis after replacing the measures of lesion load with measures of tract disconnection for both tracts, and observe significant associations between both tracts and both language skills: i.e. the change increases the apparent relevance of the uncinate fasciculus to fluency and naming skills. Finally we show that, in this dataset, disconnection data explains significant variance in both language skills that is not accounted for by lesion load or volume, but lesion load data explains no unique variance in those skills, once disconnection and lesion volume are taken into account.
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Tract disconnection metrics are generally more sensitive than tract lesion load per se.
“demonstrated that tract disconnection metrics were generally more sensitive than tract lesion load per se.”
From Damage to Broca’s area does not contribute to long-term speech production outcome after stroke (2021) · cites this paper as Hope et al., 2016
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- Authors
- Hope, T. M. H., Seghier, M. L., Prejawa, S., Leff, A. P., & Price, C. J.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Corresponding author
- Hope, Thomas M.H.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 125
- Pages
- 1169-1173
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4692449
- OpenAlex
- W2201479508
- Cited by
- 64
- References
- 15
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 8 · 2023: 6 · 2022: 9 · 2021: 6 · 2020: 4 · 2019: 8 · 2018: 4 · 2017: 4 · 2016: 3
- FWCI
- 2.97
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- NeuroImage (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Funders
- Wellcome Trust
- Stroke Association
- James S. MacDonnell Foundation
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- arcuate fasciculus, uncinate fasciculus, white matter injury, lesion load, language fluency, word naming, white matter lesions
- MeSH terms
- Brain, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Models, Neurological, Neural Pathways, Stroke, White Matter
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