Efficacy of repetitive transcranial magnetic stimulation in treating stroke aphasia: Systematic review and meta-analysis.

OBJECTIVE: This meta-analysis examined the effectiveness of repetitive Transcranial Magnetic Stimulation (rTMS) in treating post-stroke aphasia with a goal to identify parameters that are associated with successful treatment outcomes. METHODS: Following PRISMA guidelines, ten electronic databases were searched from inception till June 4th 2020. A total of 24 studies (out of 1971 records) with 567 participants met selection criteria and were included in the meta-analysis. RESULTS: The overall pooled meta-analysis revealed a significant medium effect size in favor of rTMS treatment: Standard mean difference (SMD) of 0.655 (95% CI = [0.481, 0.830], z = 7.369, p < 0.001). Moderator subgroup analyses indicated that participants' clinical characteristics and rTMS parameters moderated treatment effects. The strongest effects were observed for naming, followed by speech production, repetition and comprehension. The results indicate that with 10 to 15 sessions of 1-Hz rTMS administered 20-40 min per day over right BA45 (Brodmann's area 45), significant language improvements can be observed for up to 12 months. CONCLUSIONS: Our findings suggest that the rTMS technique can enhance rehabilitation of language skills in post-stroke aphasia when administered according to the established safety parameters. SIGNIFICANCE: Our results have implications for treatment of post-stroke aphasia. In subacute aphasia, low frequency rTMS over right BA45 improved naming, repetition, speech fluency and writing but not comprehension, whereas in chronic aphasia naming and speech production improved, but repetition and comprehension showed smaller gains.

Electrophysiological abnormalities as indicators of early-stage pathology in Primary Progressive Aphasia (PPA): A case study in semantic variant PPA.

Language induced and spontaneous oscillatory activity was measured using MEG in a patient with the semantic variant of Primary Progressive Aphasia (svPPA) and 15 healthy controls.The patient showed oscillatory slowing in the left anterior temporal lobe (ATL) that extended into non-atrophied brain tissue in left and right frontal areas. The white matter connections were reduced to the left and right ATL and left frontal regions, exhibiting electrophysiological abnormalities. Altered diffusion metrics in all four language tracts, indicted compromised white matter integrity. Task-related and spontaneous oscillatory abnormalities can indicate early neurodegeneration in svPPA, providing promising targets for intervention.

Neural Correlates of Morphology Acquisition through a Statistical Learning Paradigm.

The neural basis of statistical learning as it occurs over time was explored with stimuli drawn from a natural language (Russian nouns). The input reflected the "rules" for marking categories of gendered nouns, without making participants explicitly aware of the nature of what they were to learn. Participants were scanned while listening to a series of gender-marked nouns during four sequential scans, and were tested for their learning immediately after each scan. Although participants were not told the nature of the learning task, they exhibited learning after their initial exposure to the stimuli. Independent component analysis of the brain data revealed five task-related sub-networks. Unlike prior statistical learning studies of word segmentation, this morphological learning task robustly activated the inferior frontal gyrus during the learning period. This region was represented in multiple independent components, suggesting it functions as a network hub for this type of learning. Moreover, the results suggest that subnetworks activated by statistical learning are driven by the nature of the input, rather than reflecting a general statistical learning system.

An fMRI study of implicit language learning in developmental language impairment.

Individuals with developmental language impairment can show deficits into adulthood. This suggests that neural networks related to their language do not normalize with time. We examined the ability of 16 adults with and without impaired language to learn individual words in an unfamiliar language. Adults with impaired language were able to segment individual words from running speech, but needed more time to do so than their normal-language peers. ICA analysis of fMRI data indicated that adults with language impairment activate a neural network that is comparable to that of adults with normal language. However, a regional analysis indicated relative hyperactivation of a collection of regions associated with language processing. These results are discussed with reference to the Statistical Learning Framework and the sub-skills thought to relate to word segmentation.

Dynamic Data Visualization with Weave and Brain Choropleths.

This article introduces the neuroimaging community to the dynamic visualization workbench, Weave (https://www.oicweave.org/), and a set of enhancements to allow the visualization of brain maps. The enhancements comprise a set of brain choropleths and the ability to display these as stacked slices, accessible with a slider. For the first time, this allows the neuroimaging community to take advantage of the advanced tools already available for exploring geographic data. Our brain choropleths are modeled after widely used geographic maps but this mashup of brain choropleths with extant visualization software fills an important neuroinformatic niche. To date, most neuroinformatic tools have provided online databases and atlases of the brain, but not good ways to display the related data (e.g., behavioral, genetic, medical, etc). The extension of the choropleth to brain maps allows us to leverage general-purpose visualization tools for concurrent exploration of brain images and related data. Related data can be represented as a variety of tables, charts and graphs that are dynamically linked to each other and to the brain choropleths. We demonstrate that the simplified region-based analyses that underlay choropleths can provide insights into neuroimaging data comparable to those achieved by using more conventional methods. In addition, the interactive interface facilitates additional insights by allowing the user to filter, compare, and drill down into the visual representations of the data. This enhanced data visualization capability is useful during the initial phases of data analysis and the resulting visualizations provide a compelling way to publish data as an online supplement to journal articles.

The nature of the language input affects brain activation during learning from a natural language.

Artificial language studies have demonstrated that learners are able to segment individual word-like units from running speech using the transitional probability information. However, this skill has rarely been examined in the context of natural languages, where stimulus parameters can be quite different. In this study, two groups of English-speaking learners were exposed to Norwegian sentences over the course of three fMRI scans. One group was provided with input in which transitional probabilities predicted the presence of target words in the sentences. This group quickly learned to identify the target words and fMRI data revealed an extensive and highly dynamic learning network. These results were markedly different from activation seen for a second group of participants. This group was provided with highly similar input that was modified so that word learning based on syllable co-occurrences was not possible. These participants showed a much more restricted network. The results demonstrate that the nature of the input strongly influenced the nature of the network that learners employ to learn the properties of words in a natural language.

Language lateralization shifts with learning by adults.

For the majority of the population, language is a left-hemisphere lateralized function. During childhood, a pattern of increasing left lateralization for language has been described in brain imaging studies, suggesting that this trait develops. This development could reflect change due to brain maturation or change due to skill acquisition, given that children acquire and refine language skills as they mature. We test the possibility that skill acquisition, independent of age-associated maturation can result in shifts in language lateralization in classic language cortex. We imaged adults exposed to an unfamiliar language during three successive fMRI scans. Participants were then asked to identify specific words embedded in Norwegian sentences. Exposure to these sentences, relative to complex tones, resulted in consistent activation in the left and right superior temporal gyrus. Activation in this region became increasingly left-lateralized with repeated exposure to the unfamiliar language. These results demonstrate that shifts in lateralization can be produced in the short term within a learning context, independent of maturation.

Bidirectional iterative parcellation of diffusion weighted imaging data: separating cortical regions connected by the arcuate fasciculus and extreme capsule.

This paper introduces a Bidirectional Iterative Parcellation (BIP) procedure designed to identify the location and size of connected cortical regions (parcellations) at both ends of a white matter tract in diffusion weighted images. The procedure applies the FSL option "probabilistic tracking with classification targets" in a bidirectional and iterative manner. To assess the utility of BIP, we applied the procedure to the problem of parcellating a limited set of well-established gray matter seed regions associated with the dorsal (arcuate fasciculus/superior longitudinal fasciculus) and ventral (extreme capsule fiber system) white matter tracts in the language networks of 97 participants. These left hemisphere seed regions and the two white matter tracts, along with their right hemisphere homologues, provided an excellent test case for BIP because the resulting parcellations overlap and their connectivity via the arcuate fasciculi and extreme capsule fiber systems are well studied. The procedure yielded both confirmatory and novel findings. Specifically, BIP confirmed that each tract connects within the seed regions in unique, but expected ways. Novel findings included increasingly left-lateralized parcellations associated with the arcuate fasciculus/superior longitudinal fasciculus as a function of age and education. These results demonstrate that BIP is an easily implemented technique that successfully confirmed cortical connectivity patterns predicted in the literature, and has the potential to provide new insights regarding the architecture of the brain.

Dynamic changes in network activations characterize early learning of a natural language.

Those who are initially exposed to an unfamiliar language have difficulty separating running speech into individual words, but over time will recognize both words and the grammatical structure of the language. Behavioral studies have used artificial languages to demonstrate that humans are sensitive to distributional information in language input, and can use this information to discover the structure of that language. This is done without direct instruction and learning occurs over the course of minutes rather than days or months. Moreover, learners may attend to different aspects of the language input as their own learning progresses. Here, we examine processing associated with the early stages of exposure to a natural language, using fMRI. Listeners were exposed to an unfamiliar language (Icelandic) while undergoing four consecutive fMRI scans. The Icelandic stimuli were constrained in ways known to produce rapid learning of aspects of language structure. After approximately 4 min of exposure to the Icelandic stimuli, participants began to differentiate between correct and incorrect sentences at above chance levels, with significant improvement between the first and last scan. An independent component analysis of the imaging data revealed four task-related components, two of which were associated with behavioral performance early in the experiment, and two with performance later in the experiment. This outcome suggests dynamic changes occur in the recruitment of neural resources even within the initial period of exposure to an unfamiliar natural language.

Syntactic processing depends on dorsal language tracts.

Frontal and temporal language areas involved in syntactic processing are connected by several dorsal and ventral tracts, but the functional roles of the different tracts are not well understood. To identify which white matter tract(s) are important for syntactic processing, we examined the relationship between white matter damage and syntactic deficits in patients with primary progressive aphasia, using multimodal neuroimaging and neurolinguistic assessment. Diffusion tensor imaging showed that microstructural damage to left hemisphere dorsal tracts--the superior longitudinal fasciculus including its arcuate component--was strongly associated with deficits in comprehension and production of syntax. Damage to these dorsal tracts predicted syntactic deficits after gray matter atrophy was taken into account, and fMRI confirmed that these tracts connect regions modulated by syntactic processing. In contrast, damage to ventral tracts--the extreme capsule fiber system or the uncinate fasciculus--was not associated with syntactic deficits. Our findings show that syntactic processing depends primarily on dorsal language tracts.

Measurement of grey parrot (Psittacus erithacus) trachea via magnetic resonance imaging, dissection, and electron beam computed tomography.

To produce a model to explain the acoustic properties of human speech sounds produced by Grey parrots (Psittacus erithacus) and to compare these properties across species (e.g., with humans, other psittacine and nonpsittacine mimics), researchers need adequate measurements of the chambers that constitute the parrot vocal tract. Various methods can provide such data. Here we compare results for tracheal measurements provided by a) magnetic resonance imaging (MRI) of a live bird, b) caliper measurements of four preserved specimens, and c) electron beam computed tomography (EBCT) of three of these preserved specimens. We find that EBCT scans provide data that correspond to the inner area of the dissected trachea, whereas MRI results correspond to area measurements that include tracheal ring thickness. We briefly discuss how these data may predict formant values for Grey parrot reproduction of human vowels. Our results suggest how noninvasive techniques can be used for cross-species comparisons, including the coevolution of structure and function in avian mimicry. J. Morphol. 238:81-91, 1998. © 1998 Wiley-Liss, Inc.