Language systems from lesion-symptom mapping in aphasia: A meta-analysis of voxel-based lesion mapping studies

Na, Yoonhye; Jung, JeYoung; Tench, Christopher R.; Auer, Dorothee P.; Pyun, Sung Bom

doi:10.1016/j.nicl.2022.103038

Cited by 10 publications

(8 citation statements)

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“…There is abundant evidence in the literature that self-generated speech activates the SN, and the SN had been provided to have a directly correlated with residual language performance in patients with PSA ( 49 ). The AG is a region associated with phonological deficits ( 50 ). The fact that only individuals with motor aphasia were included may help to explain this.…”

Section: Discussionmentioning

confidence: 99%

Modulations of static and dynamic functional connectivity among brain networks by electroacupuncture in post-stroke aphasia

Gao

Zhang

et al. 2022

Front. Neurol.

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IntroductionPost-stroke aphasia (PSA) is a language disorder caused by left hemisphere stroke. Electroacupuncture (EA) is a minimally invasive therapeutic option for PSA treatment. Tongli (HT5) and Xuanzhong (GB39), two important language-associated acupoints, are frequently used in the rehabilitation of patients with PSA. Preliminary evidence indicated functional activation in distributed cortical areas upon HT5 and GB39 stimulation. However, research on the modulation of dynamic and static functional connectivity (FC) in the brain by EA in PSA is lacking.MethodThis study aimed to investigate the PSA-related effects of EA stimulation at HT5 and GB39 on neural processing. Thirty-five participants were recruited, including 19 patients with PSA and 16 healthy controls (HCs). The BOLD signal was analyzed by static independent component analysis, generalized psychophysiological interactions, and dynamic independent component analysis, considering variables such as age, sex, and years of education.ResultsThe results revealed that PSA showed activated clusters in the left putamen, left postcentral gyrus (PostCG), and left angular gyrus in the salience network (SN) compared to the HC group. The interaction effect on temporal properties of networks showed higher variability of SN (F = 2.23, positive false discovery rate [pFDR] = 0.017). The interaction effect on static FC showed increased functional coupling between the right calcarine and right lingual gyrus (F = 3.16, pFDR = 0.043). For the dynamic FC, at the region level, the interaction effect showed lower variability and higher frequencies of circuit 3, with the strongest connections between the supramarginal gyrus and posterior cingulum (F = 5.42, pFDR = 0.03), middle cingulum and PostCG (F = 5.27, pFDR = 0.036), and triangle inferior frontal and lingual gyrus (F = 5.57, pFDR = 0.026). At the network level, the interaction effect showed higher variability in occipital network–language network (LN) and cerebellar network (CN) coupling, with stronger connections between the LN and CN (F = 4.29, pFDR = 0.042). Dynamic FC values between the triangle inferior frontal and lingual gyri were anticorrelated with transcribing, describing, and dictating scores in the Chinese Rehabilitation Research Center for Chinese Standard Aphasia Examination.DiscussionThese findings suggest that EA stimulation may improve language function, as it significantly modulated the nodes of regions/networks involved in the LN, SN, CN, occipital cortex, somatosensory regions, and cerebral limbic system.

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Section: Discussionmentioning

confidence: 99%

Modulations of static and dynamic functional connectivity among brain networks by electroacupuncture in post-stroke aphasia

Gao

Zhang

et al. 2022

Front. Neurol.

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“…In the course of publishing this work, another meta-analysis of lesion-symptom mapping studies was published focusing on various language tasks ( Na et al, 2022 ). For naming, the authors found a cluster in the left parahippocampal gyrus and left mid STG (MNI −59, −11, 7, Brodman Area 22, Talairach y = −12).…”

Section: Discussionmentioning

confidence: 99%

“…ALE meta-analysis was performed using the revised version implemented in BrainMap GingerALE 3.0 software following the MNI152 template ( Eickhoff et al, 2009 , 2012 ; Turkeltaub et al, 2012 ), in conjunction with anatomical data (rather than using functional neuroimaging data for activation likelihood estimation meta-analyses, see for a similar approach Na et al, 2022 ; Urgesi et al, 2014 ). These data concerned peak coordinates of significant clusters associated with naming task performance as a result of LSM.…”

Section: Methodsmentioning

confidence: 99%

Brain Areas Critical for Picture Naming: A Systematic Review and Meta-Analysis of Lesion-Symptom Mapping Studies

Piai

Eikelboom

2023

Neurobiology of Language

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Lesion-symptom mapping (LSM) studies have revealed brain areas critical for naming, typically finding significant associations between damage to left temporal, inferior parietal and inferior fontal regions and impoverished naming performance. However, specific subregions found in the available literature vary. Hence, the aim of this study was to perform a systematic review and meta-analysis of published lesion-based findings, obtained from studies with unique cohorts investigating brain areas critical for accuracy in naming in stroke patients at least 1 month post-onset. An anatomic likelihood estimation (ALE) meta-analysis of these LSM studies was performed. Ten papers entered the ALE meta-analysis, with similar lesion coverage over left temporal and left inferior frontal areas. This small number is a major limitation of the present study. Clusters were found in left anterior temporal lobe, posterior temporal lobe extending into inferior parietal areas, in line with the arcuate fasciculus, and in pre- and postcentral gyri and middle frontal gyrus. No clusters were found in left inferior frontal gyrus. These results were further substantiated by examining five naming studies that investigated performance beyond global accuracy, corroborating the ALE meta-analysis results. The present review and meta-analysis highlight the involvement of left temporal and inferior parietal cortices in naming, and of mid to posterior portions of the temporal lobe in particular in conceptual-lexical retrieval for speaking.

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“…Language production involves a series of complex psycholinguistic processes that result from the orchestrated interplay of activity within large-scale networks (Hickok & Poeppel, 2007; Indefrey & Levelt, 2004; Price, 2012). Commonly assessed using picture naming, gross language impairment as a result of stroke has been associated with a frontotemporal network (Stark et al, 2019; Tochadse et al, 2018; Dell et al, 2013; Na et al, 2022). Here, we found that perfusion in left inferior frontal gyrus (pars triangularis), left posterior insula, and left superior temporal gyrus had the largest impact on model predictions of any regions in cortex.…”

Section: Discussionmentioning

confidence: 99%

Excellence is a habit: Enhancing predictions of language impairment by identifying stable features in clinical perfusion scans

Teghipco,

Kim,

Rorden

et al. 2023

Preprint

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Perfusion images guide acute stroke management, yet few studies have been able to systematically investigate CT perfusion collected during routine care because the measures are stored in proprietary formats incompatible with conventional research analysis pipelines. We illustrate the potential of harnessing granular data from these routine scans by using them to identify the association between specific areas of hypoperfusion and severity of object naming impairment in 43 acute stroke patients. Traditionally, similar analyses in such sample sizes face a dilemma:simple models risk being too constrained to make accurate predictions, while complex models risk overfitting and producing poor out-of-sample predictions. We demonstrate that evaluating the stability rather than out-of-sample predictive capacity of features in a nested cross-validation scheme can be an effective way of controlling model complexity and stabilizing model estimates across a variety of different regression techniques. Specifically, we show that introducing this step can determine model significance, even when the regression model already contains an embedded feature selection or dimensionality reduction step, or if a subset of features is manually selected prior to training based on expert knowledge. After improving model performance using more complex regression techniques, we discover that object naming performance relies on an extended language network encompassing regions thought to play a larger role in different naming tasks, right hemisphere regions distal to the site of injury, and regions and tracts that are less typically associated with language function. Our findings especially emphasize the role of the left superior temporal gyrus, uncinate fasciculus, and posterior insula in successful prediction of object naming impairment. Collectively, these results highlight the untapped potential of clinical CT perfusion images and demonstrate a flexible framework for enabling prediction in the limited sample sizes that currently dominate clinical neuroimaging.

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Language systems from lesion-symptom mapping in aphasia: A meta-analysis of voxel-based lesion mapping studies

Cited by 10 publications

References 85 publications

Modulations of static and dynamic functional connectivity among brain networks by electroacupuncture in post-stroke aphasia

Modulations of static and dynamic functional connectivity among brain networks by electroacupuncture in post-stroke aphasia

Brain Areas Critical for Picture Naming: A Systematic Review and Meta-Analysis of Lesion-Symptom Mapping Studies

Excellence is a habit: Enhancing predictions of language impairment by identifying stable features in clinical perfusion scans

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