Voxel-based lesion–symptom mapping

By E. Bates, Stephen M. Wilson, Ayse Pinar Saygin, F. Dick, Martin I. Sereno, Robert T. Knight, Nina F. Dronkers. Nature Neuroscience, 2003

1,404 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/bc690f553f329b497307f309738c6671ce25e733

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In Cognitive Neuroscience

Citations in the corpus

The Neural Architecture of the Language Comprehension Network: Converging Evidence from Lesion and Connectivity Analyses (2011, methodology): “Lesions that significantly alter sentence comprehension performance were mapped on a standard template using voxel-based lesion-symptom mapping (VLSM, Bates et al., 2003).”
Training-induced structural changes in the adult human brain. (2008, background): “Furthermore, subsequent lesion studies confirmed the notion that neuroimaging techniques adopting cross-sectional or prospective experimental design can even provide a biomarker of outcome after brain injury [7,24].”
Cognitive processing speed and the structure of white matter pathways: Convergent evidence from normal variation and lesion studies (2008, positive): “Voxel-based lesion-symptom mapping (VLSM), a statistical technique for quantitative assessment of the relation between damage to brain regions and continuous behavioral measures (Baldo and Dronkers, 2007; Bates et al., 2003; Dronkers et al., 2004), was employed.”
Is relational reasoning dependent on language? A voxel-based lesion symptom mapping study. (2010, methodology): “The current study used voxel-based lesion symptom mapping (VLSM; Bates et al., 2003), which allows for a voxel by voxel analysis of the relationship between lesion site and performance on a given behavioral measure.”
Age of acquisition: its neural and computational mechanisms. (2007, background): “and articulation (Ackermann & Riecker, 2004; Bates et al., 2003; Dronkers, 1996; Shuster & Lemieux, 2005).”
Is problem solving dependent on language? (2005, methodology): “To investigate the brain basis of impaired problem solving in this patient group, lesion data were analyzed using Voxel-based Lesion Symptom Mapping (VLSM; version 1.3, see Bates et al., 2003).”
Age-specific CT and MRI templates for spatial normalization (2012, positive): “This application is common for functional neuroimaging studies (e.g. functional magnetic resonance imaging; fMRI) and lesion mapping studies (e.g. voxelwise lesion symptom mapping [VLSM, Bates et al. 2003; Rorden et al. 2007]).”
Why use a connectivity-based approach to study stroke and recovery of function? (2012, positive): “Several studies have used this approach to map language (Bates et al., 2003; Borovsky et al., 2007), attention (Committeri et al.”
Improving Lesion-Symptom Mapping (2007, methodology): “The t test and analysis of variance (ANOVA) are popular tests for analyzing lesion data when the symptoms can be represented as continuous data (Bates et al., 2003; Frank, Damasio, & Grabowski, 1997).”
Power in Voxel-based Lesion-Symptom Mapping (2007, methodology): “…it may sometimes be useful in the context of specific hypotheses to examine the predictive value of a given voxel or region above and beyond that of another voxel or region, in which case the latter could be included as a covariate in the model, an approach described by Bates et al. (2003).”
The neural architecture of language: Integrative modeling converges on predictive processing (2020, background): “Language processing is known to depend causally on a left-lateralized fronto-temporal brain network (Bates et al., 2003; Binder et al., 1997; Fedorenko & Thompson-Schill, 2014; Friederici, 2012; Gorno-Tempini et al., 2004; Hagoort, 2019; Price, 2010) (Fig.”
Learning and Consolidation of Novel Spoken Words (2009, background): “…(Gooding, Mayes, & van Eijk, 2000; Verfaellie, Croce, & Milberg, 1995; Gabrieli, Cohen, & Corkin, 1988), whereas long-term knowledge of spoken words is supported by cortical systems (Tyler, Marslen-Wilson, & Stamatakis, 2005; Bates et al., 2003; Tranel, Adolphs, Damasio, & Damasio, 2001).”
The neural mechanisms of speech comprehension: fMRI studies of semantic ambiguity. (2005, background): “Keywords: frontal cortex, semantics, sentences, spoken language, temporal lobe”