Neuroplasticity in Aphasia: A Proposed Framework of Language Recovery

Microstructural properties in subacute aphasia: concurrent and prospective relationships underpinning recovery

BACKGROUND

Few investigations examined the relationship between microstructural white matter integrity and subacute post-stroke linguistic performance or the relationship between microstructural integrity and the recovery of language function. We examined two key questions: (1) How does subacute language performance, measured in single words and discourse, relate to the microstructural integrity of key white matter regions of interest in the language network? and (2) Does the integrity of these regions before treatment predict the improvement or resolution of linguistic symptoms immediately and chronically following treatment?

METHODS

58 participants within the first three months of stroke were enrolled in a randomized, single-center, double-blind, sham-controlled, study of anodal transcranial direct current stimulation combined with a computer-delivered speech and language naming therapy for subacute aphasia and were asked to complete magnetic resonance imaging at enrollment. Microstructural integrity was evaluated using diffusion tensor imaging processed with atlas-based segmentation. Regression and correlation analyses were conducted.

RESULTS

A subset of 22 participants received diffusion tensor imaging. Picture naming accuracy significantly correlated with lower mean diffusivity (higher microstructural integrity) in the left posterior inferior temporal gyrus. Recovery of naming performance was predicted by days since stroke and baseline microstructural integrity of the left posterior middle temporal gyrus, arcuate fasciculus, and superior longitudinal fasciculus. Recovery of discourse efficiency was significantly predicted by the same model.

CONCLUSIONS

This study demonstrates an association between picture naming and discourse and microstructural integrity of the key regions in the language network for patients with subacute post-stroke aphasia. Baseline microstructural integrity significantly predicts language recovery.

Distinct brain morphometry patterns revealed by deep learning improve prediction of post-stroke aphasia severity

BACKGROUND

Emerging evidence suggests that post-stroke aphasia severity depends on the integrity of the brain beyond the lesion. While measures of lesion anatomy and brain integrity combine synergistically to explain aphasic symptoms, substantial interindividual variability remains unaccounted. One explanatory factor may be the spatial distribution of morphometry beyond the lesion (e.g., atrophy), including not just specific brain areas, but distinct three-dimensional patterns.

METHODS

Here, we test whether deep learning with Convolutional Neural Networks (CNNs) on whole brain morphometry (i.e., segmented tissue volumes) and lesion anatomy better predicts chronic stroke individuals with severe aphasia (N = 231) than classical machine learning (Support Vector Machines; SVMs), evaluating whether encoding spatial dependencies identifies uniquely predictive patterns.

RESULTS

CNNs achieve higher balanced accuracy and F1 scores, even when SVMs are nonlinear or integrate linear or nonlinear dimensionality reduction. Parity only occurs when SVMs access features learned by CNNs. Saliency maps demonstrate that CNNs leverage distributed morphometry patterns, whereas SVMs focus on the area around the lesion. Ensemble clustering of CNN saliencies reveals distinct morphometry patterns unrelated to lesion size, consistent across individuals, and which implicate unique networks associated with different cognitive processes as measured by the wider neuroimaging literature. Individualized predictions depend on both ipsilateral and contralateral features outside the lesion.

CONCLUSIONS

Three-dimensional network distributions of morphometry are directly associated with aphasia severity, underscoring the potential for CNNs to improve outcome prognostication from neuroimaging data, and highlighting the prospective benefits of interrogating spatial dependence at different scales in multivariate feature space.

Structural Neuroplasticity Effects of Singing in Chronic Aphasia

Singing-based treatments of aphasia can improve language outcomes, but the neural benefits of group-based singing in aphasia are unknown. Here, we set out to determine the structural neuroplasticity changes underpinning group-based singing-induced treatment effects in chronic aphasia. Twenty-eight patients with at least mild nonfluent poststroke aphasia were randomized into two groups that received a 4-month multicomponent singing intervention (singing group) or standard care (control group). High-resolution T1 images and multishell diffusion-weighted MRI data were collected in two time points (baseline/5 months). Structural gray matter (GM) and white matter (WM) neuroplasticity changes were assessed using language network region of interest-based voxel-based morphometry (VBM) and quantitative anisotropy-based connectometry, and their associations to improved language outcomes (Western Aphasia Battery Naming and Repetition) were evaluated. Connectometry analyses showed that the singing group enhanced structural WM connectivity in the left arcuate fasciculus (AF) and corpus callosum as well as in the frontal aslant tract (FAT), superior longitudinal fasciculus, and corticostriatal tract bilaterally compared with the control group. Moreover, in VBM, the singing group showed GM volume increase in the left inferior frontal cortex (Brodmann area 44) compared with the control group. The neuroplasticity effects in the left BA44, AF, and FAT correlated with improved naming abilities after the intervention. These findings suggest that in the poststroke aphasia group, singing can bring about structural neuroplasticity changes in left frontal language areas and in bilateral language pathways, which underpin treatment-induced improvement in speech production.

Remapping and Reconnecting the Language Network after Stroke

Here, we review the literature on neurotypical individuals and individuals with post-stroke aphasia showing that right-hemisphere regions homologous to language network and other regions, like the right cerebellum, are activated in language tasks and support language even in healthy people. We propose that language recovery in post-stroke aphasia occurs largely by potentiating the right hemisphere network homologous to the language network and other networks that previously supported language to a lesser degree and by modulating connection strength between nodes of the right-hemisphere language network and undamaged nodes of the left-hemisphere language network. Based on this premise (supported by evidence we review), we propose that interventions should be aimed at potentiating the right-hemisphere language network through Hebbian learning or by augmenting connections between network nodes through neuroplasticity, such as non-invasive brain stimulation and perhaps modulation of neurotransmitters involved in neuroplasticity. We review aphasia treatment studies that have taken this approach. We conclude that further aphasia rehabilitation with this aim is justified.

Resting-state brain network connectivity is an independent predictor of responsiveness to language therapy in chronic post-stroke aphasia

Post-stroke aphasia recovery, especially in the chronic phase, is challenging to predict. Functional integrity of the brain and brain network topology have been suggested as biomarkers of language recovery. This study sought to investigate functional connectivity in four predefined brain networks (i.e., language, default mode, dorsal attention, and salience networks), in relation to aphasia severity and response to language therapy. Thirty patients with chronic post-stroke aphasia were recruited and received a treatment targeting word finding. Structural and functional brain scans were acquired at baseline and resting state functional connectivity for each network was calculated. Additionally, graph measures quantifying network properties were calculated for each network. These included global efficiency for all networks and average strength and clustering coefficient for the language network. Linear mixed effects models showed that mean functional connectivity in the default mode, dorsal attention, and salience networks as well as graph measures of all four networks are independent predictors of response to therapy. While greater mean functional connectivity and global efficiency of the dorsal attention and salience networks predicted greater treatment response, greater mean functional connectivity and global efficiency in the default mode network predicted poorer treatment response. Results for the language network were more nuanced with more efficient network configurations (as reflected in graph measures), but not mean functional connectivity, predicting greater treatment response. These findings highlight the prognostic value of resting-state functional connectivity in chronic treatment-induced aphasia recovery.

Disentangling neuroplasticity mechanisms in post-stroke language recovery

A major objective in post-stroke aphasia research is to gain a deeper understanding of neuroplastic mechanisms that drive language recovery, with the ultimate goal of enhancing treatment outcomes. Subsequent to recent advances in neuroimaging techniques, we now have the ability to examine more closely how neural activity patterns change after a stroke. However, the way these neural activity changes relate to language impairments and language recovery is still debated. The aim of this review is to provide a theoretical framework to better investigate and interpret neuroplasticity mechanisms underlying language recovery in post-stroke aphasia. We detail two sets of neuroplasticity mechanisms observed at the synaptic level that may explain functional neuroimaging findings in post-stroke aphasia recovery at the network level: feedback-based homeostatic plasticity and associative Hebbian plasticity. In conjunction with these plasticity mechanisms, higher-order cognitive control processes dynamically modulate neural activity in other regions to meet communication demands, despite reduced neural resources. This work provides a network-level neurobiological framework for understanding neural changes observed in post-stroke aphasia and can be used to define guidelines for personalized treatment development.

Improved naming in patients with Broca's aphasia with tDCS

BACKGROUND

Language impairment (aphasia) is a common neurological deficit after strokes. For individuals with chronic aphasia (beyond 6 months after the stroke), language improvements with speech therapy (ST) are often limited. Transcranial direct current stimulation (tDCS) is a promising approach to complement language recovery but interindividual variability in treatment response is common after tDCS, suggesting a possible relationship between tDCS and type of linguistic impairment (aphasia type).

METHODS

This current study is a subgroup analysis of a randomised controlled phase II futility design clinical trial on tDCS in chronic post-stroke aphasia. All participants received ST coupled with tDCS (n=31) vs sham tDCS (n=39). Confrontation naming was tested at baseline, and 1, 4, and 24 weeks post-treatment.

RESULTS

Broca's aphasia was associated with maximal adjunctive benefit of tDCS, with an average improvement of 10 additional named items with tDCS+ST compared with ST alone at 4 weeks post-treatment. In comparison, tDCS was not associated with significant benefits for other aphasia types F(1)=4.23, p=0.04. Among participants with Broca's aphasia, preservation of the perilesional posterior inferior temporal cortex was associated with higher treatment benefit (R=0.35, p=0.03).

CONCLUSIONS

These results indicate that adjuvant tDCS can enhance ST to treat naming in Broca's aphasia, and this may guide intervention approaches in future studies.

Insights gained over 60 years on factors shaping post-stroke aphasia recovery: A commentary on Vignolo (1964)

Aphasia is an acquired language disorder resulting from brain injury, including strokes which is the most common etiology, neurodegenerative diseases, tumors, traumatic brain injury, and resective surgery. Aphasia affects a significant portion of stroke survivors, with approximately one third experiencing its debilitating effects in the long term. Despite its challenges, there is growing evidence that recovery from aphasia is possible, even in the chronic phase of stroke. Sixty years ago, Vignolo (1964) outlined the primary challenges confronted by researchers in this field. These challenges encompassed the absence of an objective evaluation of language difficulties, the scarcity of evidence regarding spontaneous aphasia recovery, and the presence of numerous variables that could potentially influence the process of aphasia recovery. In this paper, we discuss the remarkable progress that has been made in the assessment of language and communication in aphasia as well as in understanding the factors influencing post-stroke aphasia recovery.

Impaired discourse content in aphasia is associated with frontal white matter damage

Aphasia is a common consequence of stroke with severe impacts on employability, social interactions and quality of life. Producing discourse-relevant information in a real-world setting is the most important aspect of recovery because it is critical to successful communication. This study sought to identify the lesion correlates of impaired production of relevant information in spoken discourse in a large, unselected sample of participants with post-stroke aphasia. Spoken discourse (n = 80) and structural brain scans (n = 66) from participants with aphasia following left hemisphere stroke were analysed. Each participant provided 10 samples of spoken discourse elicited in three different genres, and 'correct information unit' analysis was used to quantify the informativeness of speech samples. The lesion correlates were identified using multivariate lesion-symptom mapping, voxel-wise disconnection and tract-wise analyses. Amount and speed of relevant information were highly correlated across different genres and with total lesion size. The analyses of lesion correlates converged on the same pattern: impaired production of relevant information was associated with damage to anterior dorsal white matter pathways, specifically the arcuate fasciculus, frontal aslant tract and superior longitudinal fasciculus. Damage to these pathways may be a useful biomarker for impaired informative spoken discourse and informs development of neurorehabilitation strategies.

Patient With Crossed Aphasia Undergoing Long-Term Speech Therapy: A Case Report

Crossed aphasia (CA) is a type of aphasia caused by cerebral hemispheric lesions on the same side of the dominant hand. The prevalence of CA is extremely rare. To the best of our knowledge, this is the first case report in Korea to conduct 6 years of long-term speech therapy in a case of a patient with CA. The patient was a 57-year-old right-handed man with aphasia caused by extensive acute infarction in the right middle cerebral artery territory. He presented with global aphasia, right-left disorientation, and agraphia. Language function recovered in the first 6 months and then plateaued.

Cerebral Small Vessel Disease Burden: An Independent Biomarker for Anomia Treatment Responsiveness in Chronic Stroke Patients With Aphasia

OBJECTIVE

To determine whether MRI-based cerebral small vessel disease (cSVD) burden predicts treatment-induced aphasia recovery in chronic stroke patients above and beyond initial aphasia severity and stroke-lesion volume.

DESIGN

Retrospective. Four cSVD neuroimaging markers were rated using validated visual scales: white matter hyperintensities, enlarged perivascular spaces, lacunes, and global cortical atrophy. We also calculated a cSVD total score. We employed linear regression models to model treatment response as a function of cSVD burden. We also ran correlation analyses to determine the association among cSVD burden and pre-treatment linguistic and non-linguistic cognition.

SETTING

Research clinic.

PARTICIPANTS

The study includes data from 30 chronic stroke patients with aphasia who received treatment for word finding difficulties and completed additional pre-treatment neuroimaging and behavioral assessments (N=30).

INTERVENTIONS

120-minute sessions of anomia treatment 2 times per week for up to 12 weeks.

MAIN OUTCOME MEASURES

Change in accuracy on the treatment probes measured as a percentage (ie, change in accuracy percentage score=post-treatment accuracy percentage minus pre-treatment accuracy percentage).

RESULTS

Baseline cSVD burden predicted response to anomia treatment independently from demographic and stroke-related factors. Patients with lower cSVD burden exhibited enhanced rehabilitation response compared with those with higher cSVD burden (β=-6.816e-02, P=.019). cSVD burden was highly associated with nonverbal executive function at baseline (r=-0.49, P=.005): patients with lower cSVD burden exhibited higher performance on nonverbal executive function tasks compared with participants with higher cSVD burden. No association was observed among cSVD burden and performance on language tasks at the baseline.

CONCLUSIONS

cSVD, a marker of brain reserve and a robust risk factor for post-stroke dementia, may be used as a biomarker for distinguishing patients who are more likely to respond to anomia therapy from those who are less likely to do so and for individualizing treatment parameters (eg, targeting both linguistic and nonlinguistic cognition in severe cSVD).

The right hemisphere's capacity for language: evidence from primary progressive aphasia

The role of the right hemisphere (RH) in core language processes is still a matter of intense debate. Most of the relevant evidence has come from studies of gray matter, with relatively little research on RH white matter (WM) connectivity. Using Diffusion Tensor Imaging-based tractography, the current work examined the role of the two hemispheres in language processing in 33 individuals with Primary Progressive Aphasia (PPA), aiming to better characterize the contribution of the RH to language processing in the context of left hemisphere (LH) damage. The findings confirm the impact of PPA on the integrity of the WM language tracts in the LH. Additionally, an examination of the relationship between tract integrity and language behaviors provides robust evidence of the involvement of the WM language tracts of both hemispheres in language processing in PPA. Importantly, this study provides novel evidence of a unique contribution of the RH to language processing (i.e. a contribution independent from that of the language-dominant LH). Finally, we provide evidence that the RH contribution is specific to language processing rather than being domain general. These findings allow us to better characterize the role of RH in language processing, particularly in the context of LH damage.

Treatment-induced neuroplasticity after anomia therapy in post-stroke aphasia: A systematic review of neuroimaging studies

We systematically reviewed the literature on neural changes following anomia treatment post-stroke. We conducted electronic searches of CINAHL, Cochrane Trials, Embase, Ovid MEDLINE, MEDLINE-in-Process and PsycINFO databases; two independent raters assessed all abstracts and full texts. Accepted studies reported original data on adults with post-stroke aphasia, who received behavioural treatment for anomia, and magnetic resonance brain imaging (MRI) pre- and post-treatment. Search results yielded 2481 citations; 33 studies were accepted. Most studies employed functional MRI and the quality of reporting neuroimaging methodology was variable, particularly for pre-processing steps and statistical analyses. The most methodologically robust data were synthesized, focusing on pre- versus post-treatment contrasts. Studies more commonly reported increases (versus decreases) in activation following naming therapy, primarily in the left supramarginal gyrus, and left/bilateral precunei. Our findings highlight the methodological heterogeneity across MRI studies, and the paucity of robust evidence demonstrating direct links between brain and behaviour in anomia rehabilitation.

Brain health imaging markers, post-stroke aphasia and Cognition: A scoping review

For the past decade, brain health has been an emerging line of scientific inquiry assessing the impact of age-related neurostructural changes on cognitive decline and recovery from brain injury. Typically, compromised brain health is attributed to the presence of small vessel disease (SVD) and brain tissue atrophy, which are represented by various neuroimaging features. However, to date, the relationship between brain health markers and chronic aphasia severity remains unclear. Thus, the goal of this scoping review was to assess the current body of evidence regarding the relationship between SVD-related brain health biomarkers and post-stroke aphasia and cognition. In all, 187 articles were identified from 3 databases, of which 16 articles met the criteria for inclusion. Among these studies, 11 focused on cognition rather than aphasia, while 2 investigated both. Of the 10 studies that used white matter hyperintensities (WMHs) as an indicator of SVD severity, 8 studies (80%) demonstrated a relationship between WMH load and worse cognition in stroke patients. Interestingly, among the studies that specifically investigated aphasia, all 5 studies (100%) demonstrated a relationship between SVD and worse language performance. They also indicated that factors other than brain health (e.g., lesion, age, time post onset) played an important role in determining aphasia severity at a single timepoint. These findings suggest that brain health is likely a crucial factor in the context of aphasia recovery, possibly indicating the necessity of cognitive reserve thresholds for the multimodal cognitive demands associated with language recovery. While SVD and structural brain health are not commonly considered as predictors of aphasia severity, more comprehensive models incorporating brain health have the potential to improve prognosis of post-stroke cognitive and language deficits. Given the variability in the existing literature, a uniform grading system for overall SVD would be beneficial for future research on the mechanisms related to brain networks and neuroplasticity, and their translational impact.

Distinct brain morphometry patterns revealed by deep learning improve prediction of aphasia severity

Emerging evidence suggests that post-stroke aphasia severity depends on the integrity of the brain beyond the stroke lesion. While measures of lesion anatomy and brain integrity combine synergistically to explain aphasic symptoms, significant interindividual variability remains unaccounted for. A possible explanatory factor may be the spatial distribution of brain atrophy beyond the lesion. This includes not just the specific brain areas showing atrophy, but also distinct three-dimensional patterns of atrophy. Here, we tested whether deep learning with Convolutional Neural Networks (CNN) on whole brain morphometry (i.e., segmented tissue volumes) and lesion anatomy can better predict which individuals with chronic stroke (N=231) have severe aphasia, and whether encoding spatial dependencies in the data might be capable of improving predictions by identifying unique individualized spatial patterns. We observed that CNN achieves significantly higher accuracy and F1 scores than Support Vector Machine (SVM), even when the SVM is nonlinear or integrates linear and nonlinear dimensionality reduction techniques. Performance parity was only achieved when the SVM was directly trained on the latent features learned by the CNN. Saliency maps demonstrated that the CNN leveraged widely distributed patterns of brain atrophy predictive of aphasia severity, whereas the SVM focused almost exclusively on the area around the lesion. Ensemble clustering of CNN saliency maps revealed distinct morphometry patterns that were unrelated to lesion size, highly consistent across individuals, and implicated unique brain networks associated with different cognitive processes as measured by the wider neuroimaging literature. Individualized predictions of severity depended on both ipsilateral and contralateral features outside of the location of stroke. Our findings illustrate that three-dimensional network distributions of atrophy in individuals with aphasia are directly associated with aphasia severity, underscoring the potential for deep learning to improve prognostication of behavioral outcomes from neuroimaging data, and highlighting the prospective benefits of interrogating spatial dependence at different scales in multivariate feature space.

Effect and safety of C7 neurotomy at the intervertebral foramen in patients with chronic poststroke aphasia: a multicentre, randomised, controlled study protocol

INTRODUCTION

Aphasia affects many stroke survivors; therefore, effective treatments are urgently needed. Preliminary clinical findings have suggested an association between contralateral C7-C7 cross nerve transfer and recovery from chronic aphasia. Randomised controlled trials supporting the efficacy of C7 neurotomy (NC7) are lacking. This study will explore the efficacy of NC7 at the intervertebral foramen for improving chronic poststroke aphasia.

METHODS AND ANALYSIS

This study protocol reports a multicentre, randomised, assessor-blinded active-controlled trial. A total of 50 patients with chronic poststroke aphasia for over 1 year and with a aphasia quotient calculated by Western Aphasia Battery Aphasia Quotient (WAB-AQ) score below 93.8 will be recruited. Participants will be randomly assigned to 1 of 2 groups (25 individuals each) to receive NC7 plus intensive speech and language therapy (iSLT), or iSLT alone programme. The primary outcome is the change in Boston Naming Test score from baseline to the first follow-up after NC7 plus 3 weeks of iSLT or iSLT alone. The secondary outcomes include the changes in the WAB-AQ, Communication Activities of Daily Living-3, International Classification of Functioning, Disability and Health (ICF) speech language function, Barthel Index, Stroke Aphasic Depression Questionnaire-hospital version and sensorimotor assessments. The study will also collect functional imaging outcomes of naming and semantic violation tasks through functional MRI and electroencephalogram to evaluate the intervention-induced neuroplasticity.

ETHICS AND DISSEMINATION

This study was approved by the institutional review boards of Huashan Hospital, Fudan University, and all participating institutions. The study findings will be disseminated through peer-reviewed publications and conference presentations.

TRIAL REGISTRATION NUMBER

ChiCTR2200057180.

Behavioural and neural structure of fluent speech production deficits in aphasia

Deficits in fluent speech production following left hemisphere stroke are a central concern because of their impact on patients' lives and the insight they provide about the neural organization of language processing. Fluent speech production requires the rapid coordination of phonological, semantic, and syntactic processing, so this study examined how deficits in connected speech relate to these language sub-systems. Behavioural data (N = 69 participants with aphasia following left hemisphere stroke) consisted of a diverse and comprehensive set of narrative speech production measures and measures of overall severity, semantic deficits, and phonological deficits. These measures were entered into a principal component analysis with bifactor rotation-a latent structure model where each item loads on a general factor that reflects what is common among the items, and orthogonal factors that explain variance not accounted for by the general factor. Lesion data were available for 58 of the participants, and each factor score was analysed with multivariate lesion-symptom mapping. Effects of connectivity disruption were evaluated using robust regression with tract disconnection or graph theoretic measures of connectivity as predictors. The principal component analysis produced a four-factor solution that accounted for 70.6% of the variance in the data, with a general factor corresponding to the overall severity and length and complexity of speech output (complexity factor), a lexical syntax factor, and independent factors for Semantics and Phonology. Deficits in the complexity of speech output were associated with a large temporo-parietal region, similar to overall aphasia severity. The lexical syntax factor was associated with damage in a relatively small set of fronto-parietal regions which may reflect the recruitment of control systems to support retrieval and correct usage of lexical items that primarily serve a syntactic rather than semantic function. Tract-based measures of connectivity disruption were not statistically associated with the deficit scores after controlling for overall lesion volume. Language network efficiency and average clustering coefficient within the language network were significantly associated with deficit scores after controlling for overall lesion volume. These results highlight overall severity as the critical contributor to fluent speech in post-stroke aphasia, with a dissociable factor corresponding to lexical syntax.

Early white matter connectivity and plasticity in post stroke aphasia recovery

A disruption of white matter connectivity is negatively associated with language (recovery) in patients with aphasia after stroke, and behavioral gains have been shown to coincide with white matter neuroplasticity. However, most brain-behavior studies have been carried out in the chronic phase after stroke, with limited generalizability to earlier phases. Furthermore, few studies have investigated neuroplasticity patterns during spontaneous recovery (i.e., not related to a specific treatment) in the first months after stroke, hindering the investigation of potential early compensatory mechanisms. Finally, the majority of previous research has focused on damaged left hemisphere pathways, while neglecting the potential protective value of their right hemisphere counterparts for language recovery. To address these outstanding issues, we present a longitudinal study of thirty-two patients with aphasia (21 males and 11 females, M = 69.47 years, SD = 10.60 years) who were followed up for a period of 1 year with test moments in the acute (1-2 weeks), subacute (3-6 months) and chronic phase (9-12 months) after stroke. Constrained Spherical Deconvolution-based tractography was performed in the acute and subacute phase to measure Fiber Bundle Capacity (FBC), a quantitative connectivity measure that is valid in crossing fiber regions, in the bilateral dorsal arcuate fasciculus (AF) and the bilateral ventral inferior fronto-occipital fasciculus (IFOF). First, concurrent analyses revealed positive associations between the left AF and phonology, and between the bilateral IFOF and semantics in the acute - but not subacute - phase, supporting the dual-stream language model. Second, neuroplasticity analyses revealed a decrease in connection density of the bilateral AF - but not the IFOF - from the acute to the subacute phase, possibly reflecting post stroke white matter degeneration in areas adjacent to the lesion. Third, predictive analyses revealed no contribution of acute FBC measures to the prediction of later language outcomes over and above the initial language scores, suggesting no added value ofthe diffusion measures for languageprediction. Our study provides new insights on (changes in) connectivity of damaged and undamaged language pathways in patients with aphasia in the first months after stroke, as well as if/how such measures are related to language outcomes at different stages of recovery. Individual results are discussed in the light of current frameworks of language processing and aphasia recovery.

Couplet Analysis of Linguistic Topology Using Deep Neural Networks in Cognitive Linguistics

The work reported here primarily aims to realize the automatic generation of couplets using the linguistic topology of deep neural network (DNN). First, the symmetry, topology, and cognitive linguistics of language are explored to lay a theoretical foundation for subsequent model establishment and analysis. Then, the recurrent neural network (RNN) is employed to build the Seq2Seq model, and Liweng's Guide to Rhyme (an ancient Chinese enlightenment reading material to poetry creation) is imported into the Seq2Seq model as a basic corpus. Eventually, the entire system is implemented automatically on TensorFlow. The system undergoes tests of the five-character quatrain, the seven-character quatrain, the couplet, and the part-of-speech detection. Results demonstrate that both the first and the second lines of the couplet present an excellent correspondence regarding sentences and words. After some famous verses are entered, the second line of the couplet obtained is quite vivid and appropriate. Meanwhile, the results can be generated quickly and meet the requirements on rhyme and couplet matching. This model can input verses according to users' own needs and generate the second line of the couplet quickly, showing good correspondence in words, part-of-speech, and sentence pattern. Because the couplet belongs to Chinese traditional culture, it has a strong local Chinese cultural flavor. The system designed based on computer technology can help people learn and experience the charm of couplets.

Effects of a new speech support application on intensive speech therapy and changes in functional brain connectivity in patients with post-stroke aphasia

Aphasia is a language disorder that occurs after a stroke and impairs listening, speaking, reading, writing, and calculation skills. Patients with post-stroke aphasia in Japan are increasing due to population aging and the advancement of medical treatment. Opportunities for adequate speech therapy in chronic stroke are limited due to time constraints. Recent studies have reported that intensive speech therapy for a short period of time or continuous speech therapy using high-tech equipment, including speech applications (apps, can improve aphasia even in the chronic stage. However, its underlying mechanism for improving language function and its effect on other cognitive functions remains unclear. In the present study, we investigated whether intensive speech therapy using a newly developed speech support app could improve aphasia and other cognitive functions in patients with chronic stroke. Furthermore, we examined whether it can alter the brain network related to language and other cortical areas. Thus, we conducted a prospective, single-comparison study to examine the effects of a new speech support app on language and cognitive functions and used resting state functional MRI (rs-fMRI) regions of interest (ROI) to ROI analysis to determine changes in the related brain network. Two patients with chronic stroke participated in this study. They used the independent speech therapy system to perform eight sets of 20 randomly presented words/time (taking approximately 20 min), for 8 consecutive weeks. Their language, higher cognitive functions including attention function, and rs-fMRI, were evaluated before and after the rehabilitation intervention using the speech support app. Both patients had improved pronunciation, daily conversational situations, and attention. The rs-fMRI analysis showed increased functional connectivity of brain regions associated with language and attention related areas. Our results show that intensive speech therapy using this speech support app can improve language and attention functions even in the chronic stage of stroke, and may be a useful tool for patients with aphasia. In the future, we will conduct longitudinal studies with larger numbers of patients, which we hope will continue the trends seen in the current study, and provide even stronger evidence for the usefulness of this new speech support app.

Understanding, facilitating and predicting aphasia recovery after rehabilitation

Purpose: This paper reviews several studies whose aim was to understand the nature of language recovery in chronic aphasia and identify predictors of how people may recover their language functions after a brain injury.Method: Several studies that mostly draw from data collected within the Centre for Neurobiology of Language Recovery were reviewed and categorised in four aspects of language impairment and recovery in aphasia: (a) neural markers for language impairment and recovery, (b) language and cognitive markers for language impairment and recovery, (c) effective treatments and (d) predictive modelling of treatment-induced rehabilitation.Result: Language impairment and recovery in stroke-induced aphasia is multi-factorial, including patient-specific and treatment-specific factors. A combination of these factors may help us predict treatment responsiveness even before treatment begins.Conclusion: Continued work on this topic will lead to a better understanding of the mechanisms that underly language impairment and treatment-induced recovery in aphasia, and, consequently, use this information to predict each person's recovery profile trajectory and provide optimal prescriptions regarding the type and dosage of treatment.

Predictors of Therapy Response in Chronic Aphasia: Building a Foundation for Personalized Aphasia Therapy

Chronic aphasia, a devastating impairment of language, affects up to a third of stroke survivors. Speech and language therapy has consistently been shown to improve language function in prior clinical trials, but few clinicially applicable predictors of individual therapy response have been identified to date. Consequently, clinicians struggle substantially with prognostication in the clinical management of aphasia. A rising prevalence of aphasia, in particular in younger populations, has emphasized the increasing demand for a personalized approach to aphasia therapy, that is, therapy aimed at maximizing language recovery of each individual with reference to evidence-based clinical recommendations. In this narrative review, we discuss the current state of the literature with respect to commonly studied predictors of therapy response in aphasia. In particular, we focus our discussion on biographical, neuropsychological, and neurobiological predictors, and emphasize limitations of the literature, summarize consistent findings, and consider how the research field can better support the development of personalized aphasia therapy. In conclusion, a review of the literature indicates that future research efforts should aim to recruit larger samples of people with aphasia, including by establishing multisite aphasia research centers.

Lesion correlates of auditory sentence comprehension deficits in post-stroke aphasia

Auditory sentence comprehension requires coordination of multiple levels of processing: auditory-phonological perception, lexical-semantic comprehension, syntactic parsing and discourse construction, as well as executive functions such as verbal working memory (WM) and cognitive control. This study examined the lesion correlates of sentence comprehension deficits in post-stroke aphasia, building on prior work on this topic by using a different and clinically-relevant measure of sentence comprehension (the Token Test) and multivariate (SCCAN) and connectome-based lesion-symptom mapping methods. The key findings were that lesions in the posterior superior temporal lobe and inferior frontal gyrus (pars triangularis) were associated with sentence comprehension deficits, which was observed in both mass univariate and multivariate lesion-symptom mapping. Graph theoretic measures of connectome disruption were not statistically significantly associated with sentence comprehension deficits after accounting for overall lesion size.

Functional MRI evidence for reorganization of language networks after stroke

In this chapter, we review fMRI evidence for language reorganization in individuals with poststroke aphasia. Several studies in the current literature have utilized fMRI as a tool to understand patterns of functional reorganization in poststroke aphasia. Consistent with previous models that have been proposed to explain the trajectory of language recovery, differential patterns of language processing and language recovery have been identified across individuals with poststroke aphasia in different stages of recovery. Overall, a global network breakdown typically occurs in the early stages of aphasia recovery, followed by normalization in "traditional" left hemisphere language networks. Depending on individual characteristics, right hemisphere regions and bilateral domain-general regions may be further recruited. The main takeaway of this chapter is that poststroke aphasia recovery does not depend on individual neural regions, but rather involves a complex interaction among regions in larger networks. Many of the unresolved issues and contrastive findings in the literature warrant further research with larger groups of participants and standard protocols of fMRI implementation.

Multimodal Neural and Behavioral Data Predict Response to Rehabilitation in Chronic Poststroke Aphasia

BACKGROUND

Poststroke recovery depends on multiple factors and varies greatly across individuals. Using machine learning models, this study investigated the independent and complementary prognostic role of different patient-related factors in predicting response to language rehabilitation after a stroke.

METHODS

Fifty-five individuals with chronic poststroke aphasia underwent a battery of standardized assessments and structural and functional magnetic resonance imaging scans, and received 12 weeks of language treatment. Support vector machine and random forest models were constructed to predict responsiveness to treatment using pretreatment behavioral, demographic, and structural and functional neuroimaging data.

RESULTS

The best prediction performance was achieved by a support vector machine model trained on aphasia severity, demographics, measures of anatomic integrity and resting-state functional connectivity (F1=0.94). This model resulted in a significantly superior prediction performance compared with support vector machine models trained on all feature sets (F1=0.82, P<0.001) or a single feature set (F1 range=0.68-0.84, P<0.001). Across random forest models, training on resting-state functional magnetic resonance imaging connectivity data yielded the best F1 score (F1=0.87).

CONCLUSIONS

While behavioral, multimodal neuroimaging data and demographic information carry complementary information in predicting response to rehabilitation in chronic poststroke aphasia, functional connectivity of the brain at rest after stroke is a particularly important predictor of responsiveness to treatment, both alone and combined with other patient-related factors.

Resting-State Functional Connectivity following Phonological Component Analysis: The Combined Action of Phonology and Visual Orthographic Cues

Anomia is the most frequent and pervasive symptom for people with aphasia (PWA). Phonological component analysis (PCA) is a therapy incorporating phonological cues to treat anomia. Investigations of neural correlates supporting improvements following PCA remain scarce. Resting-state functional connectivity (rsFC) as a marker of therapy-induced neuroplasticity has been reported by our team. The present study explores the efficacy of PCA in French and associated therapy-induced neuroplasticity using whole-brain rsFC analysis. Ten PWA participated in a pre-/post-PCA fMRI study with cognitive linguistic assessments. PCA was delivered in French following the standard procedure. PCA led to significant improvement with trained and untrained items. PCA also led to changes in rsFC between distributed ROIs in the semantic network, visual network, and sub-cortical areas. Changes in rsFC can be interpreted within the frame of the visual and phonological nature of PCA. Behavioral and rsFC data changes associated with PCA in French highlight its efficacy and point to the importance of phonological and orthographic cues to consolidate the word-retrieval strategy, contributing to generalization to untrained words.

Simultaneous Normalization and Compensatory Changes in Right Hemisphere Connectivity during Aphasia Therapy

Changes in brain connectivity during language therapy were examined among participants with aphasia (PWA), aiming to shed light on neural reorganization in the language network. Four PWA with anomia following left hemisphere stroke and eight healthy controls (HC) participated in the study. Two fMRI scans were administered to all participants with a 3.5-month interval. The fMRI scans included phonological and semantic tasks, each consisting of linguistic and perceptual matching conditions. Between the two fMRI scans, PWA underwent Phonological Components Analysis treatment. Changes in effective connectivity during the treatment were examined within right hemisphere (RH) architecture. The results illustrate that following the treatment, the averaged connectivity of PWA across all perceptual and linguistic conditions in both tasks increased resemblance to HC, reflecting the normalization of neural processes associated with silent object name retrieval. In contrast, connections that were specifically enhanced by the phonological condition in PWA decreased in their resemblance to HC, reflecting emerging compensatory reorganization in RH connectivity to support phonological processing. These findings suggest that both normalization and compensation play a role in neural language reorganization at the chronic stage, occurring simultaneously in the same brain.

Investigating Language and Domain-General Processing in Neurotypicals and Individuals With Aphasia - A Functional Near-Infrared Spectroscopy Pilot Study

Brain reorganization patterns associated with language recovery after stroke have long been debated. Studying mechanisms of spontaneous and treatment-induced language recovery in post-stroke aphasia requires a network-based approach given the potential for recruitment of perilesional left hemisphere language regions, homologous right hemisphere language regions, and/or spared bilateral domain-general regions. Recent hardware, software, and methodological advances in functional near-infrared spectroscopy (fNIRS) make it well-suited to examine this question. fNIRS is cost-effective with minimal contraindications, making it a robust option to monitor treatment-related brain activation changes over time. Establishing clear activation patterns in neurotypical adults during language and domain-general cognitive processes via fNIRS is an important first step. Some fNIRS studies have investigated key language processes in healthy adults, yet findings are challenging to interpret in the context of methodological limitations. This pilot study used fNIRS to capture brain activation during language and domain-general processing in neurotypicals and individuals with aphasia. These findings will serve as a reference when interpreting treatment-related changes in brain activation patterns in post-stroke aphasia in the future. Twenty-four young healthy controls, seventeen older healthy controls, and six individuals with left hemisphere stroke-induced aphasia completed two language tasks (i.e., semantic feature, picture naming) and one domain-general cognitive task (i.e., arithmetic) twice during fNIRS. The probe covered bilateral frontal, parietal, and temporal lobes and included short-separation detectors for scalp signal nuisance regression. Younger and older healthy controls activated core language regions during semantic feature processing (e.g., left inferior frontal gyrus pars opercularis) and lexical retrieval (e.g., left inferior frontal gyrus pars triangularis) and domain-general regions (e.g., bilateral middle frontal gyri) during hard versus easy arithmetic as expected. Consistent with theories of post-stroke language recovery, individuals with aphasia activated areas outside the traditional networks: left superior frontal gyrus and left supramarginal gyrus during semantic feature judgment; left superior frontal gyrus and right precentral gyrus during picture naming; and left inferior frontal gyrus pars opercularis during arithmetic processing. The preliminary findings in the stroke group highlight the utility of using fNIRS to study language and domain-general processing in aphasia.

Vocal music listening enhances post-stroke language network reorganization

Listening to vocal music has been recently shown to improve language recovery in stroke survivors. The neuroplasticity mechanisms supporting this effect are, however, still unknown. Using data from a three-arm single-blind randomized controlled trial including acute stroke patients (N=38) and a 3-month follow-up, we set out to compare the neuroplasticity effects of daily listening to self-selected vocal music, instrumental music, and audiobooks on both brain activity and structural connectivity of the language network. Using deterministic tractography we show that the 3-month intervention induced an enhancement of the microstructural properties of the left frontal aslant tract (FAT) for the vocal music group as compared to the audiobook group. Importantly, this increase in the strength of the structural connectivity of the left FAT correlated with improved language skills. Analyses of stimulus-specific activation changes showed that the vocal music group exhibited increased activations in the frontal termination points of the left FAT during vocal music listening as compared to the audiobook group from acute to 3-month post-stroke stage. The increased activity correlated with the structural neuroplasticity changes in the left FAT. These results suggest that the beneficial effects of vocal music listening on post-stroke language recovery are underpinned by structural neuroplasticity changes within the language network and extend our understanding of music-based interventions in stroke rehabilitation.Significance statementPost-stroke language deficits have a devastating effect on patients and their families. Current treatments yield highly variable outcomes and the evidence for their long-term effects is limited. Patients often receive insufficient treatment that are predominantly given outside the optimal time window for brain plasticity. Post-stroke vocal music listening improves language outcome which is underpinned by neuroplasticity changes within the language network. Vocal music listening provides a complementary rehabilitation strategy which could be safely implemented in the early stages of stroke rehabilitation and seems to specifically target language symptoms and recovering language network.

Treatment of post-stroke aphasia: A narrative review for stroke neurologists

This review is intended to help physicians guide patients to optimal management of post-stroke aphasia. We review literature on post-stroke aphasia treatment, focusing on: (1) when and for whom language therapy is most effective, (2) the variety of approaches that can be effective for different individuals, and (3) the extent to which behavioral therapy might be augmented by non-invasive brain stimulation and/or medications.

Current Approaches to the Treatment of Post-Stroke Aphasia

Aphasia, impairment of language after stroke or other neurological insult, is a common and often devastating condition that affects nearly every social activity and interaction. Behavioral speech and language therapy is the mainstay of treatment, although other interventions have been introduced to augment the effects of the behavioral therapy. In this narrative review, we discuss advances in aphasia therapy in the last 5 years and focus primarily on properly powered, randomized, controlled trials of both behavioral therapies and interventions to augment therapy for post-stroke aphasia. These trials include evaluation of behavioral therapies and computer-delivered language therapies. We also discuss outcome prediction trials as well as interventional trials that have employed noninvasive brain stimulation, or medications to augment language therapy. Supported by evidence from Phase III trials and large meta-analyses, it is now generally accepted that aphasia therapy can improve language processing for many patients. Not all patients respond similarly to aphasia therapy with the most severe patients being the least likely responders. Nevertheless, it is imperative that all patients, regardless of severity, receive aphasia management focused on direct therapy of language deficits, counseling, or both. Emerging evidence from Phase II trials suggests transcranial brain stimulation is a promising method to boost aphasia therapy outcomes.

Extended fMRI-Guided Anodal and Cathodal Transcranial Direct Current Stimulation Targeting Perilesional Areas in Post-Stroke Aphasia: A Pilot Randomized Clinical Trial

Transcranial direct current stimulation (tDCS) may enhance speech and language treatment (SLT) for stroke survivors with aphasia; however, to date, there is no standard protocol for the application of tDCS in post-stroke aphasia. We explored the safety and efficacy of fMRI-guided tDCS on functional language and cortical activity when delivered to the lesioned left hemisphere concurrently with SLT across an extended, six-week treatment period. Twelve persons with chronic, nonfluent aphasia following a single left-hemisphere stroke participated in the three-arm (anodal vs. cathodal vs. sham) single-blind, parallel, pilot trial. No serious adverse events occurred during 30 treatment sessions or in the following six weeks. All groups demonstrated functional language gains following intensive treatment; however, active tDCS resulted in greater gains in standardized, probe, and caregiver-reported measures of functional language than sham. Evidence declaring one polarity as superior for inducing language recovery was mixed. However, cathodal stimulation to the lesioned left hemisphere, expected to have a down-regulating effect, resulted in increased areas of cortical activation across both hemispheres, and specifically perilesionally. Generalization of these preliminary findings is limited; however, results are nevertheless compelling that tDCS combined with SLT can be safely applied across extended durations, with the potential to enhance functional language and cortical activation for persons with aphasia.

Web-based Oral Reading for Language in Aphasia (Web ORLA®): A pilot randomized control trial

OBJECTIVE

To investigate an intensive asynchronous computer-based treatment delivered remotely with clinician oversight to people with aphasia.

DESIGN

Single-blind, randomized placebo-controlled trial.

SETTING

Free-standing urban rehabilitation hospital.

PARTICIPANTS

Adults with aphasia (at least six months post-onset).

INTERVENTIONS

Experimental treatment was Web ORLA^® (Oral Reading for Language in Aphasia) which provides repeated choral and independent reading aloud of sentences with a virtual therapist. Placebo was a commercially available computer game. Participants were instructed to practice 90 minutes/day, six days/week for six weeks.

MAIN MEASURES

Change in Language Quotient of the Western Aphasia Battery-Revised from pre-treatment to post-treatment and pre-treatment to six weeks following the end of treatment.

RESULTS

32 participants (19 Web ORLA^®, 13 Control) completed the intervention and post-treatment assessment; 27 participants (16 Web ORLA^®, 11 Control) completed the follow-up assessment six weeks after treatment had ended. Web ORLA^® treatment resulted in significant improvements in language performance from pre-treatment to immediately post-treatment (X = 2.96; SD = 4.32; P < 0.01; ES = 0.68) and from pre-treatment to six weeks following the end of treatment (X = 4.53; SD = 3.16; P < 0.001; ES = 1.43). There was no significant difference in the gain from pre-treatment to post-treatment for the Web ORLA^® versus Control groups. However, the Web ORLA^® group showed significantly greater gains at the six-week follow-up than the control group (X = 2.70; SD = 1.01; P = 0.013; ES = 1.92).

CONCLUSION

Results provide evidence for improved language outcomes following intensive, web-based delivery of ORLA^® to individuals with chronic aphasia. Findings underscore the value of combining clinician oversight with the flexibility of asynchronous practice.

An empirical comparison of univariate versus multivariate methods for the analysis of brain-behavior mapping

Lesion symptom mapping (LSM) tools are used on brain injury data to identify the neural structures critical for a given behavior or symptom. Univariate lesion symptom mapping (ULSM) methods provide statistical comparisons of behavioral test scores in patients with and without a lesion on a voxel by voxel basis. More recently, multivariate lesion symptom mapping (MLSM) methods have been developed that consider the effects of all lesioned voxels in one model simultaneously. In the current study, we provide a much-needed systematic comparison of several ULSM and MLSM methods, using both synthetic and real data to identify the potential strengths and weaknesses of both approaches. We tested the spatial precision of each LSM method for both single and dual (network type) anatomical target simulations across anatomical target location, sample size, noise level, and lesion smoothing. Additionally, we performed false positive simulations to identify the characteristics associated with each method's spurious findings. Simulations showed no clear superiority of either ULSM or MLSM methods overall, but rather highlighted specific advantages of different methods. No single method produced a thresholded LSM map that exclusively delineated brain regions associated with the target behavior. Thus, different LSM methods are indicated, depending on the particular study design, specific hypotheses, and sample size. Overall, we recommend the use of both ULSM and MLSM methods in tandem to enhance confidence in the results: Brain foci identified as significant across both types of methods are unlikely to be spurious and can be confidently reported as robust results.

Introduction to the 2018 Research Symposium Forum

Purpose The purpose of this introduction is to provide an overview of the articles contained within this forum of Journal of Speech, Language, and Hearing Research (JSLHR). Each of these articles is based upon presentations from the Research Symposium at the 2018 annual convention of the American Speech-Language-Hearing Association held in Boston, MA.