White-Matter Neuroanatomical Predictors of Aphasic Verb Retrieval

Dresang, Haley C.; Hula, William D.; Yeh, Fang‐Cheng; Warren, Tessa; Dickey, Michael Walsh

doi:10.1089/brain.2020.0921

Cited by 15 publications

(18 citation statements)

References 59 publications

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“…Our findings are the first to consider the contribution of all right hemisphere WM tracts across the recovery profile. Previous research has investigated these contributions cross‐sectionally, in the early subacute phase (Forkel et al, 2014 ) or in the chronic phase of recovery (Dresang et al, 2021 ; Fleming et al, 2020 ; Fridriksson et al, 2013 ; Hula et al, 2020 ; Kourtidou et al, 2021 ; Marchina et al, 2011 ). Keser et al ( 2020 ) investigated the longitudinal contribution of two right hemisphere WM tracts to language recovery after stroke in 10 stroke patients.…”

Section: Discussionmentioning

confidence: 99%

“…Using this methodology, the discordant results observed in studies to date (Fridriksson et al, 2013 ; Keser et al, 2020 ; Marchina et al, 2011 ), which have used mean FA to investigate the contribution of a single tract associated with language production, may be explained by a combination of (a) the aspect of language being assessed, (b) the recovery phase being investigated, and (c) the task used to assess language. By adopting a connectometry approach, we have added to the growing evidence of the contribution of WM tracts outside the homologous language pathways to predicting better language outcome in aphasia (Dresang et al, 2021 ; Hula et al, 2020 ; Pani et al, 2016 ). It must be acknowledged that recovery among individuals with aphasia remains highly variable, depending on the site and volume of stroke as well as brain reserve and other variables (Kiran & Thompson, 2019 ), and therefore, given that the sample sizes remain modest in both the present and previously published studies focusing on right hemispheric structural connectivity in aphasia recovery (Forkel et al, 2014 ; Keser et al, 2020 ; Pani et al, 2016 ), future larger‐scale studies are required to assess the out‐of‐sample predictive value of the current results and enable generalization to the wider aphasic population.…”

Section: Discussionmentioning

confidence: 99%

“…In contrast, greater right arcuate fasciculus volume in the acute stage has been shown to be an independent predictor of less severe chronic aphasia, together with age, sex, and lesion size, explaining 57% of the variance in chronic poststroke language outcomes (Forkel et al, 2014 ). Recent aphasia studies have also identified white matter (WM) tracts outside the homologous language pathways, including right cingulum and cortico‐subcortical projection pathways as well as corpus callosum, positively predicting verb retrieval (Dresang et al, 2021 ), semantic and phonological processing abilities (Hula et al, 2020 ), and speech fluency (Pani et al, 2016 ) in aphasia. Moreover, volume within contralesional frontotemporal WM structures has been shown to predict treatment response to a high dose auditory comprehension therapy (Fleming et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

“…Due to there being less susceptibility to the partial volume effects of free water, crossing fibers, and nondiffusive materials, this approach has been shown to be more sensitive than conventional voxel‐based or track‐based analyses utilizing FA (Jin et al, 2019 ; Yeh et al, 2013 ). QA‐based connectometry has recently been used to uncover WM tracts supporting word production (Hula et al, 2020 ) and verb retrieval (Dresang et al, 2021 ) in aphasia. Based on the previous dMRI evidence (Forkel et al, 2014 ; Keser et al, 2020 ; Kourtidou et al, 2021 ; Pani et al, 2016 ), and data suggesting that the corpus callosum mediates speech perception in the brain (Steinmann & Mulert, 2012 ), we hypothesized that (i) language production and comprehension outcomes would be associated with greater QA in the corpus callosum, (ii) language production outcomes would be associated with both negative and positive QA, and (iii) language comprehension outcomes would be associated with different WM factors to production.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Right hemispheric structural connectivity and poststroke language recovery

Sihvonen

Vadinova

Garden

et al. 2023

Human Brain Mapping

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Poststroke aphasia typically results from brain damage to the left‐lateralized language network. The contribution of the right‐lateralized homologues in aphasia recovery remains equivocal. In this longitudinal observational study, we specifically investigated the role of right hemisphere structural connectome in aphasia recovery. Twenty‐two patients with aphasia after a left hemispheric stroke underwent comprehensive language assessment at the early subacute and chronic stages. A novel structural connectometry approach, using multi‐shell diffusion‐weighted MRI data collected at the early subacute stage, was used to evaluate the relationship between right hemisphere white matter connectome and language production and comprehension abilities at early subacute stage. Moreover, we evaluated the relationship between early subacute right hemisphere white matter connectome and longitudinal change in language production and comprehension abilities. All results were corrected for multiple comparisons. Connectometry analyses revealed negative associations between early subacute stage right hemisphere structural connectivity and language production, both cross‐sectionally and longitudinally (pFDR < .0125). In turn, only positive associations between right hemisphere structural connectivity and language comprehension were observed, both cross‐sectionally and longitudinally (pFDR < .0125). Interhemispheric connectivity was highly associated with comprehension scores. Our results shed light on the discordant interpretations of previous findings, by providing evidence that while some right hemisphere white matter pathways may make a maladaptive contribution to the recovery of language, other pathways support the recovery of language, especially comprehension abilities.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Right hemispheric structural connectivity and poststroke language recovery

Sihvonen

Vadinova

Garden

et al. 2023

Human Brain Mapping

View full text Add to dashboard Cite

show abstract

“…More specifically, we carried out connectometry analysis utilizing quantitative anisotropy (QA), which has shown greater sensitivity than conventional single-tensor based or tract-based analysis (Yeh, Badre et al, 2016 ). Connectometry uses permutation testing to identify group differences in white matter tracts, and has recently been used to uncover white matter connectometry of word production (Hula et al, 2020 ) and verb retrieval (Dresang et al, 2021 ) in post-stroke aphasia. Based on the previous functional MRI results from the baseline (pre-intervention) stage of our trial, which showed that music listening activates bilateral frontotemporal, parietal, and subcortical regions in early subacute stage stroke patients (Sihvonen et al, 2017b ), we hypothesized that vocal music listening would induce longitudinal (baseline to 3-month stage) structural connectivity changes bilaterally in frontotemporal and parietal regions.…”

Section: Introductionmentioning

confidence: 99%

Post-stroke enriched auditory environment induces structural connectome plasticity: secondary analysis from a randomized controlled trial

Sihvonen

Soinila

Särkämö

2022

Brain Imaging and Behavior

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Post-stroke neuroplasticity and cognitive recovery can be enhanced by multimodal stimulation via environmental enrichment. In this vein, recent studies have shown that enriched sound environment (i.e., listening to music) during the subacute post-stroke stage improves cognitive outcomes compared to standard care. The beneficial effects of post-stroke music listening are further pronounced when listening to music containing singing, which enhances language recovery coupled with structural and functional connectivity changes within the language network. However, outside the language network, virtually nothing is known about the effects of enriched sound environment on the structural connectome of the recovering post-stroke brain. Here, we report secondary outcomes from a single-blind randomized controlled trial (NCT01749709) in patients with ischaemic or haemorrhagic stroke (N = 38) who were randomly assigned to listen to vocal music, instrumental music, or audiobooks during the first 3 post-stroke months. Utilizing the longitudinal diffusion-weighted MRI data of the trial, the present study aimed to determine whether the music listening interventions induce changes on structural white matter connectome compared to the control audiobook intervention. Both vocal and instrumental music groups increased quantitative anisotropy longitudinally in multiple left dorsal and ventral tracts as well as in the corpus callosum, and also in the right hemisphere compared to the audiobook group. Audiobook group did not show increased structural connectivity changes compared to both vocal and instrumental music groups. This study shows that listening to music, either vocal or instrumental promotes wide-spread structural connectivity changes in the post-stroke brain, providing a fertile ground for functional restoration.

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Alterations of the cerebral microstructure in patients with noise‐induced hearing loss: A diffusion tensor imaging study

Huang,

Wang,

Zhang

et al. 2024

Brain and Behavior

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ObjectiveTo explore the changes in the cerebral microstructure of patients with noise‐induced hearing loss (NIHL) using diffusion tensor imaging (DTI).MethodOverall, 122 patients with NIHL (mild [MP, n = 79], relatively severe patients [including moderate and severe; RSP, n = 32], and undetermined [lost to follow‐up, n = 11]) and 84 healthy controls (HCs) were enrolled. All clinical data, including age, education level, hearing threshold, occupation type, noise exposure time, and some scale scores (including the Mini‐Mental State Examination [MMSE], tinnitus handicap inventory [THI], and Hamilton Anxiety Scale [HAMA]), were collected and analyzed. All participants underwent T1WI3DFSPGR and DTI, and tract‐based spatial statistics and region of interest (ROI) analysis were used for assessment.ResultsThe final sample included 71 MP, 28 RSP, and 75 HCs. The HAMA scores of the three groups were significantly different (p < .05). The noise exposure times, hearing thresholds, and HAMA scores of the MP and RSP were significantly different (p < .05). The noise exposure time was positively correlated with the hearing threshold and negatively correlated with the HAMA scores (p < .05), whereas the THI scores were positively correlated with the hearing threshold (p < .05). DTI analysis showed that all DTI parameters (fractional anisotropy [FA], axial diffusivity [AD], mean diffusivity [MD], and radial diffusivity [RD]) were significantly different in the left inferior longitudinal fasciculus (ILF) and left inferior fronto‐occipital fasciculus (IFOF) for the three groups (p < .05). In addition, the FA values were significantly lower in the bilateral corticospinal tract (CST), right fronto‐pontine tract (FPT), right forceps major, left superior longitudinal fasciculus (temporal part) (SLF), and left cingulum (hippocampus) (C‐H) of the MP and RSP than in those of the HCs (p < .05); the AD values showed diverse changes in the bilateral CST, left IFOF, right anterior thalamic radiation, right external capsule (EC), right SLF, and right superior cerebellar peduncle (SCP) of the MP and RSP relative to those of the HC (p < .05). However, there were no significant differences among the bilateral auditory cortex ROIs of the three groups (p > .05). There was a significant negative correlation between the FA and HAMA scores for the left IFOF/ILF, right FPT, left SLF, and left C‐H for the three groups (p < .05). There was a significant positive correlation between the AD and HAMA scores for the left IFOF/ILF and right EC of the three groups (p < .05). There were significantly positive correlations between the RD/MD and HAMA scores in the left IFOF/ILF of the three groups (p < .05). There was a significant negative correlation between the AD in the right SCP and noise exposure time of the MP and RSP groups (p < .05). The AD, MD, and RD in the left ROI were significantly positively correlated with hearing threshold in the MP and RSP groups (p < .05), whereas FA in the right ROI was significantly positively correlated with the HAMA scores for the three groups (p < .05).ConclusionThe changes in the white matter (WM) microstructure may be related to hearing loss caused by noise exposure, and the WM structural abnormalities in patients with NIHL were mainly located in the syndesmotic fibers of the temporooccipital region, which affected the auditory and language pathways. This confirmed that the auditory pathways have abnormal structural connectivity in patients with NIHL.

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White-Matter Neuroanatomical Predictors of Aphasic Verb Retrieval

Cited by 15 publications

References 59 publications

Right hemispheric structural connectivity and poststroke language recovery

Right hemispheric structural connectivity and poststroke language recovery

Post-stroke enriched auditory environment induces structural connectome plasticity: secondary analysis from a randomized controlled trial

Alterations of the cerebral microstructure in patients with noise‐induced hearing loss: A diffusion tensor imaging study

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