Lesion-symptom mapping corroborates lateralization of verbal and nonverbal memory processes and identifies distributed brain networks responsible for memory dysfunction

Mock, Nadia; Balzer, Christian; Gutbrod, Klemens; Haan, Bianca de; Jäncke, Lutz; Ettlin, Thierry; Trost, Wiebke

doi:10.1016/j.cortex.2022.04.017

Cited by 8 publications

(2 citation statements)

References 136 publications

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“…One pivotal technique is voxel‐based lesion‐symptom mapping (VLSM), initially introduced by (Bates et al, 2003). VLSM serves as the foundational method for mapping lesions in diverse cognitive domains (Mock et al, 2022; Moore & Demeyere, 2022; Weaver et al, 2021). It offers advantages over overlap‐subtraction approaches by generating statistical maps that facilitate the inference of brain‐behaviour relationships in stroke patients based on lesioned voxels and functional scores (Arnoux et al, 2018; Bates et al, 2003; Karnath et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Predicting functional impairments with lesion‐derived disconnectome mapping: Validation in stroke patients with motor deficits

Khalilian,

Roussel,

Godefroy

et al. 2024

Eur J of Neuroscience

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Focal structural damage to white matter tracts can result in functional deficits in stroke patients. Traditional voxel‐based lesion‐symptom mapping is commonly used to localize brain structures linked to neurological deficits. Emerging evidence suggests that the impact of structural focal damage may extend beyond immediate lesion sites. In this study, we present a disconnectome mapping approach based on support vector regression (SVR) to identify brain structures and white matter pathways associated with functional deficits in stroke patients. For clinical validation, we utilized imaging data from 340 stroke patients exhibiting motor deficits. A disconnectome map was initially derived from lesions for each patient. Bootstrap sampling was then employed to balance the sample size between a minority group of patients exhibiting right or left motor deficits and those without deficits. Subsequently, SVR analysis was used to identify voxels associated with motor deficits (p < .005). Our disconnectome‐based analysis significantly outperformed alternative lesion‐symptom approaches in identifying major white matter pathways within the corticospinal tracts associated with upper–lower limb motor deficits. Bootstrapping significantly increased the sensitivity (80%–87%) for identifying patients with motor deficits, with a minimum lesion size of 32 and 235 mm3 for the right and left motor deficit, respectively. Overall, the lesion‐based methods achieved lower sensitivities compared with those based on disconnection maps. The primary contribution of our approach lies in introducing a bootstrapped disconnectome‐based mapping approach to identify lesion‐derived white matter disconnections associated with functional deficits, particularly efficient in handling imbalanced data.

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Section: Introductionmentioning

confidence: 99%

Predicting functional impairments with lesion‐derived disconnectome mapping: Validation in stroke patients with motor deficits

Khalilian,

Roussel,

Godefroy

et al. 2024

Eur J of Neuroscience

View full text Add to dashboard Cite

show abstract

“…Generally, these studies are conducted for either of two goals: to identify structural correlates underlying a function of interest, or to predict stroke outcome or recovery ( Price et al, 2017 ). Previous studies identified cortical areas critically involved in, for example, spoken language ( Mirman et al, 2015 ), visuospatial processing ( Baier et al, 2012 , Biesbroek et al, 2014 ) and memory ( Lugtmeijer et al, 2021 , Mock et al, 2022 ). In addition, prediction studies showed relative contributions of lesion location and volume to, for example, post-stroke aphasia ( Forkel and Catani, 2018 , Fridriksson et al, 2015 , Schumacher et al, 2019 ) and neglect recovery ( Karnath et al, 2011 ).…”

Section: Introductionmentioning

confidence: 99%