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.

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.

Exploring Pragmatic Deficits in Relation to Theory of Mind and Executive Functions: Evidence from Individuals with Right Hemisphere Stroke.

Research investigating pragmatic deficits in individuals with right hemisphere damage focuses on identifying the potential mechanisms responsible for the nature of these impairments. Nonetheless, the presumed shared cognitive mechanisms that could account for these deficits have not yet been established through data-based evidence from lesion studies. This study aimed to examine the co-occurrence of pragmatic language deficits, Theory of Mind impairments, and executive functions while also exploring their associations with brain lesion sites. Twenty-five patients suffering from unilateral right hemisphere stroke and thirty-seven healthy participants were recruited for this study. The two groups were tested in pragmatics, Theory of Mind, and executive function tasks. Structural imaging data were also obtained for the identification of the lesion sites. The findings of this study suggest a potential convergence among the three aforementioned cognitive mechanisms. Moreover, we postulate a hypothesis for a neural circuitry for communication impairments observed in individuals with right hemisphere damage.

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 (ß=-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).

How Much Attention Do We Pay to Attention Deficits in Poststroke Aphasia?

Although language deficits are the primary area of weakness, people with poststroke aphasia often experience challenges with nonlinguistic cognitive skills, including attention processing. The purpose of this review is to synthesize the evidence for the relationship between attention deficits and language deficits in people with poststroke aphasia. Three different types of studies are reviewed: (1) studies exploring whether people with poststroke aphasia exhibit concomitant attention and language deficits, (2) studies explicitly exploring the relationship between attention and language deficits in people with poststroke aphasia, and (3) either language or attention (or both) treatment studies exploring whether treatment gains in one domain generalize to the other. In the last section, we briefly review research evidence for the neural basis of the attention-language relationship in aphasia.

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.

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.

White Matter Hyperintensities Predict Response to Language Treatment in Poststroke Aphasia.

BACKGROUND: White matter hyperintensities (WMH) are a radiological marker of brain health that has been associated with language status in poststroke aphasia; however, its association with language treatment outcomes remains unknown. OBJECTIVE: To determine whether WMH in the right hemisphere (RH) predict response to language therapy independently from demographics and stroke lesion-related factors in poststroke aphasia. METHODS: We used the Fazekas scale to rate WMH in the RH in 30 patients with poststroke aphasia who received language treatment. We developed ordinal regression models to examine language treatment effects as a function of WMH severity after controlling for aphasia severity, stroke lesion volume, time post onset, age, and education level. We also evaluated associations between WMH severity and both pre-treatment naming ability and executive function. RESULTS: The severity of WMH in the RH predicted treatment response independently from demographic and stroke-related factors such that patients with less severe WMH exhibited better treatment outcome. WMH scores were not significantly correlated with pretreatment language scores, but they were significantly correlated with pretreatment scores of executive function. CONCLUSION: We suggest that the severity of WMH in the RH is a clinically relevant predictor of treatment response in this population.

Verbal memory and sentence comprehension in aphasia: A case series.

This case series explores the relationship between verbal memory capacity and sentence comprehension in four patients with aphasia. Two sentence comprehension tasks showed that two patients, P1 and P2, had impaired syntactic comprehension, whereas P3 and P4's sentence comprehension was intact. The memory assessment tasks showed that P1 and P2 had severely impaired short-term memory, whereas P3 and P4 performed within the normal range in the short-term memory tasks. This finding suggests an association between short-term memory deficit and sentence comprehension difficulties. P1 and P3 exhibited impaired comparable working memory deficits, suggesting a dissociation between working memory and sentence comprehension.

Silent pauses in aphasia.

Pauses may be studied as an aspect of the temporal organization of speech, as well as an index of internal cognitive processes, such as word access, selection and retrieval, monitoring, articulatory planning, and memory. Several studies have demonstrated specific distributional patterns of pauses in typical speech. However, evidence from patients with language impairment is sparse and restricted to small-scale studies. The aim of the present study is to investigate empty pause distribution and associations between pause variables and linguistic elements in aphasia. Eighteen patients with chronic aphasia following a left hemisphere stroke were recruited. The control group consisted of 19 healthy adults matched for age, gender, and years of formal schooling. Speech samples from both groups were transcribed, and silent pauses were annotated using ELAN. Our results indicate that in both groups, pause duration distribution follows a log-normal bimodal model with significantly different thresholds between the two populations, yet specific enough for each distribution to justify classification into two distinct groups of pauses for each population: short and long. Moreover, we found differences between the patient and control group, prominently with regard to long pause duration and rate. Long pause indices were also associated with fundamental linguistics elements, such as mean length of utterance. Overall, we argue that post-stroke aphasia may induce quantitative but not qualitative alterations of pause patterns during speech, and further suggest that long pauses may serve as an index of internal cognitive processes supporting sentence planning. Our findings are discussed within the context of pause pattern quantification strategies as potential markers of cognitive changes in aphasia, further stressing the importance of such measures as an integral part of language assessment in clinical populations.

Why is it difficult to predict language impairment and outcome in patients with aphasia after stroke?

One of the most devastating consequences of stroke is aphasia. Communication problems after stroke can severely impair the patient's quality of life and make even simple everyday tasks challenging. Despite intense research in the field of aphasiology, the type of language impairment has not yet been localized and correlated with brain damage, making it difficult to predict the language outcome for stroke patients with aphasia. Our primary objective is to present the available evidence that highlights the difficulties of predicting language impairment after stroke. The different levels of complexity involved in predicting the lesion site from language impairment and ultimately predicting the long-term outcome in stroke patients with aphasia were explored. Future directions and potential implications for research and clinical practice are highlighted.