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Purpose: Despite a tremendous amount of research in this topic, the precise neural mechanisms underlying language recovery remain unclear. Much of the evidence suggests that activation of remaining left-hemisphere tissue, including perilesional areas, is linked to the best treatment outcomes, yet recruitment of the right hemisphere for various language tasks has also been linked to favorable behavioral outcomes. In this review article, we propose a framework of language recovery that incorporates a network-based view of the brain regions involved in recovery. Method: We review evidence from the extant literature and work from our own laboratory to identify findings consistent with our proposed framework and identify gaps in our current knowledge. Results: Expanding on Heiss and Thiel's (2006) hierarchy of language recovery, we identify 4 emerging themes: (a) Several bilateral regions constitute a network engaged in language recovery; (b) spared left-hemisphere regions are important components of the network engaged in language recovery; (c) as damage increases in the left hemisphere, activation expands to the right hemisphere and domain-general regions; and (d) patients with efficient, control-like network topology show greater improvement than patients with abnormal topology. We propose a mechanistic model of language recovery that accounts for individual differences in behavior, network topology, and treatment responsiveness. Conclusion: Continued work in this topic will lead us to a better understanding of the mechanisms underlying language recovery, biomarkers that influence recovery, and, consequently, more personalized treatment options for individual patients.

The locus and extent of brain damage in the event of vascular insult can be quantitatively established quickly and easily with vascular atlases. Although highly anticipated by clinicians and clinical researchers, no digital MRI arterial atlas is readily available for automated data analyses. We created a digital arterial territory atlas based on lesion distributions in 1,298 patients with acute stroke. The lesions were manually traced in the diffusion-weighted MRIs, binary stroke masks were mapped to a common space, probability maps of lesions were generated and the boundaries for each arterial territory was defined based on the ratio between probabilistic maps. The atlas contains the definition of four major supra- and infra-tentorial arterial territories: Anterior, Middle, Posterior Cerebral Arteries and Vertebro-Basilar, and sub-territories (thalamoperforating, lenticulostriate, basilar and cerebellar arterial territories), in two hierarchical levels. This study provides the first publicly-available, digital, 3D deformable atlas of arterial brain territories, which may serve as a valuable resource for large-scale, reproducible processing and analysis of brain MRIs of patients with stroke and other conditions. Measurement(s) brain arterial territories Technology Type(s) Magnetic Resonance Imaging Factor Type(s) location Sample Characteristic - Organism Homo sapiens Sample Characteristic - Location United States of America

Aphasia, the loss of language ability following damage to the brain, is among the most disabling and common consequences of stroke. Subcortical stroke, occurring in the basal ganglia, thalamus, and/or deep white matter can result in aphasia, often characterized by word fluency, motor speech output, or sentence generation impairments. The link between greater lesion volume and acute aphasia is well documented, but the independent contributions of lesion location, cortical hypoperfusion, prior stroke, and white matter degeneration (leukoaraiosis) remain unclear, particularly in subcortical aphasia. Thus, we aimed to disentangle the contributions of each factor on language impairments in left hemisphere acute subcortical stroke survivors. Eighty patients with acute ischemic left hemisphere subcortical stroke (less than 10 days post-onset) participated. We manually traced acute lesions on diffusion-weighted scans and prior lesions on T2-weighted scans. Leukoaraiosis was rated on T2-weighted scans using the Fazekas et al. (1987) scale. Fluid-attenuated inversion recovery (FLAIR) scans were evaluated for hyperintense vessels in each vascular territory, providing an indirect measure of hypoperfusion in lieu of perfusion-weighted imaging. We found that language performance was negatively correlated with acute/total lesion volumes and greater damage to substructures of the deep white matter and basal ganglia. We conducted a LASSO regression that included all variables for which we found significant univariate relationships to language performance, plus nuisance regressors. Only total lesion volume was a significant predictor of global language impairment severity. Further examination of three participants with severe language impairments suggests that their deficits result from impairment in domain-general, rather than linguistic, processes. Given the variability in language deficits and imaging markers associated with such deficits, it seems likely that subcortical aphasia is a heterogeneous clinical syndrome with distinct causes across individuals.

In this study, we examined regions in the left and right hemisphere language network that were altered in terms of the underlying neural activation and effective connectivity subsequent to language rehabilitation. Eight persons with chronic post-stroke aphasia and eight normal controls participated in the current study. Patients received a 10 week semantic feature-based rehabilitation program to improve their skills. Therapy was provided on atypical examples of one trained category while two control categories were monitored; the categories were counterbalanced across patients. In each fMRI session, two experimental tasks were conducted: (a) picture naming and (b) semantic feature verification of trained and untrained categories. Analysis of treatment effect sizes revealed that all patients showed greater improvements on the trained category relative to untrained categories. Results from this study show remarkable patterns of consistency despite the inherent variability in lesion size and activation patterns across patients. Across patients, activation that emerged as a function of rehabilitation on the trained category included bilateral IFG, bilateral SFG, LMFG, and LPCG for picture naming; and bilateral IFG, bilateral MFG, LSFG, and bilateral MTG for semantic feature verification. Analysis of effective connectivity using Dynamic Causal Modeling (DCM) indicated that LIFG was the consistently significantly modulated region after rehabilitation across participants. These results indicate that language networks in patients with aphasia resemble normal language control networks and that this similarity is accentuated by rehabilitation.

While several studies of task-based effective connectivity of normal language processing exist, little is known about the functional reorganization of language networks in patients with stroke-induced chronic aphasia. During oral picture naming, activation in neurologically intact individuals is found in \"classic\" language regions involved with retrieval of lexical concepts [e.g., left middle temporal gyrus (LMTG)], word form encoding [e.g., left posterior superior temporal gyrus, (LpSTG)], and controlled retrieval of semantic and phonological information [e.g., left inferior frontal gyrus (LIFG)] as well as domain-general regions within the multiple demands network [e.g., left middle frontal gyrus (LMFG)]. After stroke, lesions to specific parts of the left hemisphere language network force reorganization of this system. While individuals with aphasia have been found to recruit similar regions for language tasks as healthy controls, the relationship between the dynamic functioning of the language network and individual differences in underlying neural structure and behavioral performance is still unknown. Therefore, in the present study, we used dynamic causal modeling (DCM) to investigate differences between individuals with aphasia and healthy controls in terms of task-induced regional interactions between three regions (i.e., LIFG, LMFG, and LMTG) vital for picture naming. The DCM model space was organized according to exogenous input to these regions and partitioned into separate families. At the model level, random effects family wise Bayesian Model Selection revealed that models with driving input to LIFG best fit the control data whereas models with driving input to LMFG best fit the patient data. At the parameter level, a significant between-group difference in the connection strength from LMTG to LIFG was seen. Within the patient group, several significant relationships between network connectivity parameters, spared cortical tissue, and behavior were observed. Overall, this study provides some preliminary findings regarding how neural networks for language reorganize for individuals with aphasia and how brain connectivity relates to underlying structural integrity and task performance.

Linguistic aspects of narration have been investigated in healthy populations, in a wide variety of languages and speech genres with very different results. There is some evidence indicating that linguistic elements, such as speech rate (i.e., the measure indicating the amount of speech produced in a certain time period), mean length of utterance (MLU) (i.e., the index reflecting sentence grammatical structure), frequency of nouns and verbs, might be affected by non-linguistic factors such as sex. On the other hand, despite the existence of neuroimaging evidence of structural differences between males and females, it is yet unknown how such differences could explain between-sex disparities in linguistic abilities in natural speech contexts. To date, no study has evaluated discourse production elements in relation to sex differences and their neural correlates in terms of brain structure, a topic that could provide unique insights on the relationship between language and the brain. The aim of the present study was to determine sex differences in narrative skills in healthy adults and to investigate white and gray matter structural correlates of linguistic skills in each group. Twenty-seven male and 30 female ( = 57) right-handed, neurologically intact, monolingual Greek speakers, matched for age and years of education, participated. Narrations of a personal medical event were elicited. Linguistic elements of speech rate (words per minute), MLUs, frequency of nouns and verbs were calculated for each speech sample, by two independent raters. Structural 3D T1 images were segmented and parcellated using FreeSurfer and whole-brain between-sex differences in cortical thickness, cortical volume and surface area, were obtained. Between-group differences in white matter diffusion tensor scalars were examined via Tract-Based Spatial-Statistics and whole-brain tractography and automated tract delineation using Automated Fiber Quantification. Speech rate and noun frequency were significantly lower for men, while verb frequency was significantly higher for women, but no differences were identified for MLU. Regarding cortical measures, males demonstrated increased volume, surface area and cortical thickness in several bilateral regions, while no voxel-wise or tractography-based between-group differences in white matter metrics were observed. Regarding the relationship between sex and speech variables, hierarchical regression analyses showed that the superior/middle frontal cluster in surface area may serve as a significant predictor of speech rate variance, but only in females. We discuss several possible interpretations of how sex-related speech abilities could be represented differently in men and women in gray matter structures within the broad language network.

Studies have shown that the integrity of white matter tracts connecting different regions in the left cerebral hemisphere is important for aphasia recovery after stroke. However, the impact of the underlying structural connection between the cortex and the cerebellum in post-stroke aphasia is poorly understood. We studied the microstructural integrity of the cerebellum and the corticocerebellar connections and their role in picture naming. Fifty-six patients with left cerebral infarcts (sparing the cerebellum) underwent diffusion tensor imaging (DTI) and Boston Naming Test. We compared the fractional anisotropy (FA) and mean diffusivity (MD) values of the right and the left cerebellum (lobular gray and white matter structures) and cerebellocortical connections. Recursive feature elimination and Spearman correlation analyses were performed to evaluate the relationship between naming performance and the corticocerebellar connections. We found that the right, relative to left, cerebellar structures and their connections with the left cerebrum showed lower FA and higher MD values, both reflecting lower microstructural integrity. This trend was not observed in the healthy controls. Higher MD values of the right major cerebellar outflow tract were associated with poorer picture naming performance. Our study provides the first DTI data demonstrating the critical importance of ascending and descending corticocerebellar connections for naming outcomes after stroke.

Difficulty recognizing affective prosody (receptive aprosodia) can occur following right hemisphere damage (RHD). Not all individuals spontaneously recover their ability to recognize affective prosody, warranting behavioral intervention. However, there is a dearth of evidence-based receptive aprosodia treatment research in this clinical population. The purpose of the current study was to investigate an explicit training protocol targeting affective prosody recognition in adults with RHD and receptive aprosodia. Eighteen adults with receptive aprosodia due to acute RHD completed affective prosody recognition before and after a short training session that targeted proposed underlying perceptual and conceptual processes. Behavioral impairment and lesion characteristics were investigated as possible influences on training effectiveness. Affective prosody recognition improved following training, and recognition accuracy was higher for pseudo- vs. real-word sentences. Perceptual deficits were associated with the most posterior infarcts, conceptual deficits were associated with frontal infarcts, and a combination of perceptual-conceptual deficits were related to temporoparietal and subcortical infarcts. Several right hemisphere ventral stream regions and pathways along with frontal and parietal hypoperfusion predicted training effectiveness. Explicit acoustic-prosodic-emotion training improves affective prosody recognition, but it may not be appropriate for everyone. Factors such as linguistic context and lesion location should be considered when planning prosody training.

Stroke recovery models can improve prognostication of therapy response in patients with chronic aphasia, yet quantifying the effect of lesion on recovery is challenging. This study aimed to evaluate the utility of lesion classification via gray matter (GM)-only versus combined GM plus white matter (WM) metrics and to determine structural measures associated with aphasia severity, naming skills, and treatment outcomes. Thirty-four patients with chronic aphasia due to left hemisphere infarct completed T1-weighted and DTI scans and language assessments prior to receiving a 12-week naming treatment. GM metrics included the amount of spared tissue within five cortical masks. WM integrity was indexed by spared tissue and fractional anisotropy (FA) from four homologous left and right association tracts. Clustering of GM-only and GM + WM metrics via k-medoids yielded four patient clusters that captured two lesion characteristics, size and location. Linear regression models revealed that both GM-only and GM + WM clustering predicted baseline aphasia severity and naming skills, but only GM + WM clustering predicted treatment outcomes. Spearman correlations revealed that without controlling for lesion volume, the majority of left hemisphere metrics were related to language measures. However, adjusting for lesion volume, no relationships with aphasia severity remained significant. FA from two ventral left WM tracts was related to naming and treatment success, independent of lesion size. In sum, lesion volume and GM metrics are sufficient predictors of overall aphasia severity in patients with chronic stroke, whereas diffusion metrics reflecting WM tract integrity may add predictive power to language recovery outcomes after rehabilitation.

There are few evidence-based treatments for language deficits in primary progressive aphasia (PPA). PPA treatments are often adopted from the poststroke aphasia literature. The poststroke aphasia literature has shown promising results using Verb Network Strengthening Treatment (VNeST), a behavioral therapy that focuses on improving naming by producing verbs and their arguments in phrases and sentences. Emerging research in poststroke aphasia and PPA has shown promising results pairing behavioral language therapy with transcranial direct current stimulation (tDCS). This study used a double-blind, within-subjects, sham-controlled crossover design to study the effect of anodal tDCS applied to left inferior frontal gyrus (IFG) plus VNeST versus VNeST plus sham stimulation in two individuals with nonfluent variant PPA and one individual with logopenic variant PPA. Participants received two phases of treatment, each with 15 1-hr sessions of VNeST. One phase paired VNeST with tDCS stimulation, and one with sham. For each phase, language testing was conducted at baseline, and at 1 week and 8 weeks posttreatment conclusion. For each participant, treatment efficacy was evaluated for each treatment phase by comparing the mean change in accuracy between baseline and the follow-up time points for naming trained verbs (primary outcome measure), untrained verbs, and nouns on the Object and Action Naming Battery. Mean change from baseline was also directly compared between tDCS and sham phases at each time point. Results revealed a different pattern of outcomes for each of the participants. A tDCS advantage was not found for trained verbs for any participant. Two participants with nonfluent variant PPA had a tDCS advantage for generalization to naming of untrained verbs, which was apparent at 1 week and 8 weeks posttreatment. One participant with nonfluent variant also showed evidence of generalization to sentence production in the tDCS phase. VNeST plus anodal tDCS stimulation of left IFG shows promising results for improving naming in PPA.