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Neural predictors of narrative-discourse outcomes after naming intervention in aphasia
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Poster B53 in Poster Session B, Tuesday, October 24, 3:30 - 5:15 pm CEST, Espace Vieux-Port
Dirk Den Ouden1, Sigfus Kristinsson1, Leonardo Bonilha2, Greg Hickok3, Argye Hillis4, Chris Rorden1, Brielle Stark5, Julius Fridriksson1; 1University of South Carolina, 2Emory University, 3University of California Irvine, 4Johns Hopkins University, 5Indiana University
Introduction We previously reported on variables that predict response to sequential phonological and semantic naming treatment in aphasia (Kristinsson et al., 2023). Based on data from the same trial, we now turn our attention to narrative-discourse measures and their neural substrates. To what extent do lesion characteristics predict discourse measures at baseline, and do lesion characteristics have prognostic value for discourse outcomes after naming treatment? Method 96 Participants with chronic aphasia (41.7% female; mean age 60.6) received six weeks naming therapy, half starting with three weeks phonologically-focused, and the other half starting with semantically-focused treatment, in a cross-over design. Change in naming accuracy was the primary outcome measure, assessed after the first treatment phase, immediately before the second phase, one-week after the second phase as well as one and six months post-treatment. At the same time points, participants were asked to (re)tell the Cinderella story. As potential predictors among the many variables that can be distilled from narrative discourse, we selected Words-per-Minute (WpM), Verbs-per-Utterance (VpU), Propositional Density (PD), Mean-Length-of-Utterance in Words (MLU), Type-Token Ratio, Word-Error ratio, Noun-Verb ratio (NV), Open-Closed-class ratio (OC), and the ratios of phonological errors, semantic errors and unrelated errors. As discourse outcome measures, we focused on WpM, VpU, and PD, as proxies for speech rate, syntactic complexity, and content richness. MRI data were collected at baseline. Lesions were manually drawn based on visual examination of structural T1 and T2 images. For the current study, we performed voxel-based and JHU-region-based univariate lesion-symptom mapping, as well as univariate JHU-region-based mapping analyses between behavioral measures and white-matter integrity, as reflected in fractional anisotropy (FA). Linear regression with permutation thresholding (3000 permutations) was performed with a one-tailed alpha level of .05 and lesion size as a covariate. Results Lower MLU, WpM, VpU and PD were all correlated with partly overlapping damage to left-hemisphere pre and post-central gyri, as well as white-matter (corona radiata, fronto-occipital fasciculus) and other subcortical structures (thalamus, capsula interna). Lower NV was associated with cortical and medial temporo-occipital damage, including posterior middle and inferior-temporal gyri, while lower OC was associated with subcortical frontal damage, medial to precentral and middle-frontal gyri. Increased VpU after phonological treatment was predicted by hippocampal integrity at baseline, and increased PD after semantic treatment was predicted by baseline integrity of parahippocampal gyrus, amygdala and inferior temporal gyrus. Conclusion In line with earlier work (Fridriksson et al., 2018), dorsal-stream damage was associated with lower performance on narrative-discourse measures at baseline. Interestingly, integrity of limbic structures involved in memory consolidation was predictive of discourse outcomes in terms of syntax (VpU) and content (PD) after phonological and semantic treatment phases, respectively. These results provide further evidence that structural stroke characteristics contribute to specific predictions of treatment response in aphasia. References Fridriksson, et al. (2018). Anatomy of aphasia revisited. Brain, 141(3), 848-862. Kristinsson, et al. (2023). Predicting Outcomes of Language Rehabilitation: Prognostic Factors for Immediate and Long-Term Outcomes After Aphasia Therapy. J Speech Lang Hear Res, 66(3), 1068-1084.
Topic Areas: Disorders: Acquired, Language Production