Functional relevance of interhemispheric fiber tracts in speech processing

Steinmann, Saskia; Mulert, Christoph

doi:10.1016/j.jneuroling.2011.07.003

Cited by 29 publications

(4 citation statements)

References 59 publications

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“…The present data, however, indicated that both regions are an important part of the vocalization network. The STG subregions showed a close intra-hemispheric and bilateral coupling probably for the purpose of exchanging, monitoring, and online adjusting important acoustic information during vocal productions (Steinmann and Mulert, 2012 ; Parkinson et al, 2013 ; Kort et al, 2014 ). A more extended left-right STG coupling was found for the condition of repeating affective prosody, which involves both higher vocal control demands as well as short-term memory storage of vocal patterns.…”

Section: Discussionmentioning

confidence: 99%

Aggressive vocal expressionsâ€”an investigation of their underlying neural network

Klaas

Frühholz

Grandjean

2015

Front. Behav. Neurosci.

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Recent neural network models for the production of primate vocalizations are largely based on research in nonhuman primates. These models seem yet not fully capable of explaining the neural network dynamics especially underlying different types of human vocalizations. Unlike animal vocalizations, human affective vocalizations might involve higher levels of vocal control and monitoring demands, especially in case of more complex vocal expressions of emotions superimposed on speech. Here we therefore investigated the functional cortico-subcortical network underlying different types (evoked vs. repetition) of producing human affective vocalizations in terms of affective prosody, especially examining the aggressive tone of a voice while producing meaningless speech-like utterances. Functional magnetic resonance imaging revealed, first, that bilateral auditory cortices showed a close functional interconnectivity during affective vocalizations pointing to a bilateral exchange of relevant acoustic information of produced vocalizations. Second, bilateral motor cortices (MC) that directly control vocal motor behavior showed functional connectivity to the right inferior frontal gyrus (IFG) and the right superior temporal gyrus (STG). Thus, vocal motor behavior during affective vocalizations seems to be controlled by a right lateralized network that provides vocal monitoring (IFG), probably based on auditory feedback processing (STG). Third, the basal ganglia (BG) showed both positive and negative modulatory connectivity with several frontal (ACC, IFG) and temporal brain regions (STG). Finally, the repetition of affective prosody compared to evoked vocalizations revealed a more extended neural network probably based on higher control and vocal monitoring demands. Taken together, the functional brain network underlying human affective vocalizations revealed several features that have been so far neglected in models of primate vocalizations.

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Section: Discussionmentioning

confidence: 99%

Aggressive vocal expressionsâ€”an investigation of their underlying neural network

Klaas

Frühholz

Grandjean

2015

Front. Behav. Neurosci.

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“…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%

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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“…On the subcortical level, differences in connectivity profiles between areas depending on language involvement seem likely. Besides major language-related white matter tracts known to be involved in language processing, various short or long interconnecting fibers, such as short association fibers (commonly referred to as arcuate fibers or U-fibers), interhemispheric transcallosal fibers, and fibers projecting to the cerebellum play a role [28,29,33,34].…”

Section: Introductionmentioning

confidence: 99%

Function-Based Tractography of the Language Network Correlates with Aphasia in Patients with Language-Eloquent Glioblastoma

et al. 2020

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To date, the structural characteristics that distinguish language-involved from non-involved cortical areas are largely unclear. Particularly in patients suffering from language-eloquent brain tumors, reliable mapping of the cortico-subcortical language network is of high clinical importance to prepare and guide safe tumor resection. To investigate differences in structural characteristics between language-positive and language-negative areas, 20 patients (mean age: 63.2 ± 12.9 years, 16 males) diagnosed with language-eloquent left-hemispheric glioblastoma multiforme (GBM) underwent preoperative language mapping by navigated transcranial magnetic stimulation (nTMS) and nTMS-based diffusion tensor imaging fiber tracking (DTI FT). The number of language-positive and language-negative points as well as the gray matter intensity (GMI), normalized volumes of U-fibers, interhemispheric fibers, and fibers projecting to the cerebellum were assessed and compared between language-positive and language-negative nTMS mappings and set in correlation with aphasia grades. We found significantly lower GMI for language-positive nTMS points (5.7 ± 1.7 versus 7.1 ± 1.6, p = 0.0121). Furthermore, language-positive nTMS points were characterized by an enhanced connectivity profile, i.e., these points showed a significantly higher ratio in volumes for U-fibers (p ≤ 0.0056), interhemispheric fibers (p = 0.0494), and fibers projecting to the cerebellum (p = 0.0094). The number of language-positive nTMS points (R ≥ 0.4854, p ≤ 0.0300) as well as the ratio in volumes for U-fibers (R ≤ −0.4899, p ≤ 0.0283) were significantly associated with aphasia grades, as assessed pre- or postoperatively and during follow-up examinations. In conclusion, this study provides evidence for structural differences on cortical and subcortical levels between language-positive and language-negative areas, as detected by nTMS language mapping. The results may further increase confidence in the technique of nTMS language mapping and nTMS-based tractography in the direct clinical setting. Future studies may confirm our results in larger cohorts and may expand the findings to patients with other tumor entities than GBM.

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Functional relevance of interhemispheric fiber tracts in speech processing

Cited by 29 publications

References 59 publications

Aggressive vocal expressionsâ€”an investigation of their underlying neural network

Aggressive vocal expressionsâ€”an investigation of their underlying neural network

Right hemispheric structural connectivity and poststroke language recovery

Function-Based Tractography of the Language Network Correlates with Aphasia in Patients with Language-Eloquent Glioblastoma

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