Predicting language outcome and recovery after stroke: the PLORAS system

A preliminary study of white matter disconnections underlying deficits in praxis in left hemisphere stroke patients

Limb apraxia is a higher-order motor disorder often occurring post-stroke, which affects skilled actions. It is assessed through tasks involving gesture production or pantomime, recognition, meaningless gesture imitation, complex figure drawing, single and multi-object use. A two-system model for the organisation of actions hypothesizes distinct pathways mediating praxis deficits via conceptual, 'indirect', and perceptual 'direct' routes to action. Traditional lesion- symptom mapping techniques have failed to identify these distinct routes. We assessed 29 left hemisphere stroke patients to investigate white matter disconnections on deficits of praxis tasks from the Birmingham Cognitive Screening. White matter disconnection maps derived from patients' structural T1 lesions were created using a diffusion-weighted healthy participant dataset acquired from the human connectome project (HCP). Initial group-level regression analyses revealed significant disconnection between occipital lobes via the splenium of the corpus callosum and involvement of the inferior longitudinal fasciculus in meaningless gesture imitation deficits. There was a trend of left fornix disconnection in gesture production deficits. Further, voxel-wise Bayesian Crawford single-case analyses performed on two patients with the most severe meaningless gesture imitation and meaningful gesture production deficits, respectively, confirmed distinct posterior interhemispheric disconnection, for the former, and disconnections between temporal and frontal areas via the fornix, rostrum of the corpus callosum and anterior cingulum, for the latter. Our results suggest distinct pathways associated with perceptual and conceptual deficits akin to 'direct' and 'indirect' action routes, with some patients displaying both. Larger studies are needed to validate and elaborate on these findings, advancing our understanding of limb apraxia.

Situating word deafness within aphasia recovery: A case report

Word deafness is a rare neurological disorder often observed following bilateral damage to superior temporal cortex and canonically defined as an auditory modality-specific deficit in word comprehension. The extent to which word deafness is dissociable from aphasia remains unclear given its heterogeneous presentation, and some have consequently posited that word deafness instead represents a stage in recovery from aphasia, where auditory and linguistic processing are affected to varying degrees and improve at differing rates. Here, we report a case of an individual (Mr. C) with bilateral temporal lobe lesions whose presentation evolved from a severe aphasia to an atypical form of word deafness, where auditory linguistic processing was impaired at the sentence level and beyond. We first reconstructed in detail Mr. C's stroke recovery through medical record review and supplemental interviewing. Then, using behavioral testing and multimodal neuroimaging, we documented a predominant auditory linguistic deficit in sentence and narrative comprehension-with markedly reduced behavioral performance and absent brain activation in the language network in the spoken modality exclusively. In contrast, Mr. C displayed near-unimpaired behavioral performance and robust brain activations in the language network for the linguistic processing of words, irrespective of modality. We argue that these findings not only support the view of word deafness as a stage in aphasia recovery but also further instantiate the important role of left superior temporal cortex in auditory linguistic processing.

Efficacy of a gamified digital therapy for speech production in people with chronic aphasia (iTalkBetter): behavioural and imaging outcomes of a phase II item-randomised clinical trial

Background

Aphasia is among the most debilitating of symptoms affecting stroke survivors. Speech and language therapy (SLT) is effective, but many hours of practice are required to make clinically meaningful gains. One solution to this 'dosage' problem is to automate therapeutic approaches via self-supporting apps so people with aphasia (PWA) can amass practice as it suits them. However, response to therapy is variable and no clinical trial has yet identified the key brain regions required to engage with word-retrieval therapy.

Methods

Between Sep 7, 2020 and Mar 1, 2022 at University College London in the UK, we carried out a phase II, item-randomised clinical trial in 27 PWA using a novel, self-led app, 'iTalkBetter', which utilises confrontation naming therapy. Unlike previously reported apps, it has a real-time utterance verification system that drives its adaptive therapy algorithm. Therapy items were individually randomised to provide balanced lists of 'trained' and 'untrained' items matched on key psycholinguistic variables and baseline performance. PWA practised with iTalkBetter over a 6-week therapy block. Structural and functional MRI data were collected to identify therapy-related changes in brain states. A repeated-measures design was employed. The trial was registered at ClinicalTrials.gov (NCT04566081).

Findings

iTalkBetter significantly improved naming ability by 13% for trained items compared with no change for untrained items, an average increase of 29 words (SD = 26) per person; beneficial effects persisted at three months. PWA's propositional speech also significantly improved. iTalkBetter use was associated with brain volume increases in right auditory and left anterior prefrontal cortices. Task-based fMRI identified dose-related activity in the right temporoparietal junction.

Interpretation

Our findings suggested that iTalkBetter significantly improves PWAs' naming ability on trained items. The effect size is similar to a previous RCT of computerised therapy, but this is the first study to show transfer to a naturalistic speaking task. iTalkBetter usage and dose caused observable changes in brain structure and function to key parts of the surviving language perception, production and control networks. iTalkBetter is being rolled-out as an app for all PWA and anomia: https://www.ucl.ac.uk/icn/research/research-groups/neurotherapeutics/projects/digital-interventions-neuro-rehabilitation-0 so that they can increase their dosage of practice-based SLT.

Funding

National Institute for Health and Care Research, Wellcome Centre for Human Neuroimaging.

Mapping spoken language and cognitive deficits in post-stroke aphasia

Aphasia is an acquired disorder caused by damage, most commonly due to stroke, to brain regions involved in speech and language. While language impairment is the defining symptom of aphasia, the co-occurrence of non-language cognitive deficits and their importance in predicting rehabilitation and recovery outcomes is well documented. However, people with aphasia (PWA) are rarely tested on higher-order cognitive functions, making it difficult for studies to associate these functions with a consistent lesion correlate. Broca's area is a particular brain region of interest that has long been implicated in speech and language production. Contrary to classic models of speech and language, cumulative evidence shows that Broca's area and surrounding regions in the left inferior frontal cortex (LIFC) are involved in, but not specific to, speech production. In this study we aimed to explore the brain-behaviour relationships between tests of cognitive skill and language abilities in thirty-six adults with long-term speech production deficits caused by post-stroke aphasia. Our findings suggest that non-linguistic cognitive functions, namely executive functions and verbal working memory, explain more of the behavioural variance in PWA than classical language models imply. Additionally, lesions to the LIFC, including Broca's area, were associated with non-linguistic executive (dys)function, suggesting that lesions to this area are associated with non-language-specific higher-order cognitive deficits in aphasia. Whether executive (dys)function - and its neural correlate in Broca's area - contributes directly to PWA's language production deficits or simply co-occurs with it, adding to communication difficulties, remains unclear. These findings support contemporary models of speech production that place language processing within the context of domain-general perception, action and conceptual knowledge. An understanding of the covariance between language and non-language deficits and their underlying neural correlates will inform better targeted aphasia treatment and outcomes.

Using in vivo functional and structural connectivity to predict chronic stroke aphasia deficits

Focal brain damage caused by stroke can result in aphasia and advances in cognitive neuroscience suggest that impairment may be associated with network-level disorder rather than just circumscribed cortical damage. Several studies have shown meaningful relationships between brain-behaviour using lesions; however, only a handful of studies have incorporated in vivo structural and functional connectivity. Patients with chronic post-stroke aphasia were assessed with structural (n = 68) and functional (n = 39) MRI to assess whether predicting performance can be improved with multiple modalities and if additional variance can be explained compared to lesion models alone. These neural measurements were used to construct models to predict four key language-cognitive factors: (i) phonology; (ii) semantics; (iii) executive function; and (iv) fluency. Our results showed that each factor (except executive ability) could be significantly related to each neural measurement alone; however, structural and functional connectivity models did not explain additional variance above the lesion models. We did find evidence that the structural and functional predictors may be linked to the core lesion sites. First, the predictive functional connectivity features were found to be located within functional resting-state networks identified in healthy controls, suggesting that the result might reflect functionally specific reorganization (damage to a node within a network can result in disruption to the entire network). Second, predictive structural connectivity features were located within core lesion sites, suggesting that multimodal information may be redundant in prediction modelling. In addition, we observed that the optimum sparsity within the regularized regression models differed for each behavioural component and across different imaging features, suggesting that future studies should consider optimizing hyperparameters related to sparsity per target. Together, the results indicate that the observed network-level disruption was predicted by the lesion alone and does not significantly improve model performance in predicting the profile of language impairment.

Pharmacotherapy for post-stroke aphasia: what are the options?

INTRODUCTION

Aphasia is a common, long-lasting aftermath of stroke lesions. There is an increased integration of pharmacotherapy as an adjunctive strategy to speech and language therapy (SLT) for post-stroke aphasia (PSA). Nevertheless, more research in pharmacotherapy for acute and chronic PSA is necessary, including the election of drugs that target different neurotransmitter systems and deficits in specific language domains.

AREAS COVERED

This article updates the role of pharmacotherapy for PSA, focusing the spotlight on some already investigated drugs and candidate agents deserving of future research. Refining the precision of drug election would require using multimodal biomarkers to develop personalized treatment approaches. There is a solid need to devise feasible randomized controlled trials adapted to the particularities of the PSA population. The emergent role of multimodal interventions combining one or two drugs with noninvasive brain stimulation to augment SLT is emphasized.

EXPERT OPINION

Pharmacotherapy can improve language deficits not fully alleviated by SLT. In addition, the 'drug-only' approach can also be adopted when administering SLT is not possible. The primary goal of pharmacotherapy is reducing the overall aphasia severity, although targeting language-specific deficits (i.e. naming, spoken output) also contributes to improving functional communication. Unfortunately, there is still little information for recommending a drug for specific language deficits.

Acquired reading impairment following brain injury

This large-scale patient study investigated the rate, unique signatures associated with acquired reading impairments, its neurocognitive correlates, and long-term outcome in 731 acute stroke patients using the sentence and non-word reading subtests of Birmingham Cognitive Screen (BCoS). The objectives for the study were to explore the (i) potentially different error patterns among adult patients, (ii) associative relationship between the different subclasses of reading impairment and performance in other cognitive domains, and (iii) recovery rates in patients nine months post-lesion compared with their initial performance. The study revealed distinctive reading impairment profiles in patients with left hemisphere (LH) and right hemisphere (RH) lesions. Some interesting associations between reading disorder and other cognitive functions were observed. Nine months post-lesion, both groups showed some recovery in reading performance compared with their baseline performance, but the rate of improvement was higher for the LH group. The study reveals unique reading profiles and impairment patterns among left and right hemisphere lesions. The findings of the study provide a deeper understanding of reading deficits that will inform clinical practice, planning of rehabilitative interventions of brain injured patients, and the scientific community.

Risk factors of poor developmental outcome in children with tuberculous meningitis

BACKGROUND

Neurodevelopmental delay is a significant long-term complication of childhood tuberculous meningitis (TBM). The objective of this study was to assess risk factors for neurodevelopmental delay in children with TBM.

METHODS

We conducted a retrospective cohort study of children diagnosed with TBM at Tygerberg Hospital, Cape Town, South Africa, over a 30-year period between 1985 and 2015. We assessed the relationship between demographic, clinical, laboratory and neuro-imaging characteristics, and cognitive impairment at the conclusion of anti-tuberculous treatment. Poor outcome was defined as moderate-to severe cognitive impairment.

RESULTS

A total of 327 TBM patients were included, 71 (21.7%) suffered a poor outcome. Multivariate analysis revealed that decreased level of consciousness (adjusted OR (aOR): 4.68; 95%CI: 2.43-13.88; p = 0.005), brainstem dysfunction (aOR: 3.20; 95%CI: 1.70-6.00; p < 0.001), and radiological infarction (aOR: 3.47; 95%CI: 1.87-6.45; p < 0.001) were associated with a poor developmental outcome. Left hemispherical (single and multiple) stroke and bilateral stroke were associated with poor developmental outcomes.

CONCLUSION

Certain neurological signs as well as radiological infarct characteristics are important predictors of poor developmental outcome. Anticipation of the likely level of cognitive impairment at diagnosis allows more accurate prognostication and prompt institution of supportive and rehabilitative measures, after the acute illness.

Structural disconnections associated with language impairments in chronic post-stroke aphasia using disconnectome maps

Inconsistent findings have been reported about the impact of structural disconnections on language function in post-stroke aphasia. This study investigated patterns of structural disconnections associated with chronic language impairments using disconnectome maps. Seventy-six individuals with post-stroke aphasia underwent a battery of language assessments and a structural MRI scan. Support-vector regression disconnectome-symptom mapping analyses were performed to examine the correlations between disconnectome maps, representing the probability of disconnection at each white matter voxel and different language scores. To further understand whether significant disconnections were primarily representing focal damage or a more extended network of seemingly preserved but disconnected areas beyond the lesion site, results were qualitatively compared to support-vector regression lesion-symptom mapping analyses. Part of the left white matter perisylvian network was similarly disconnected in 90% of the individuals with aphasia. Surrounding this common left perisylvian disconnectome, specific structural disconnections in the left fronto-temporo-parietal network were significantly associated with aphasia severity and with lower performance in auditory comprehension, syntactic comprehension, syntactic production, repetition and naming tasks. Auditory comprehension, repetition and syntactic processing deficits were related to disconnections in areas that overlapped with and extended beyond lesion sites significant in SVR-LSM analyses. In contrast, overall language abilities as measured by aphasia severity and naming seemed to be mostly explained by focal damage at the level of the insular and central opercular cortices, given the high overlap between SVR-DSM and SVR-LSM results for these scores. While focal damage seems to be sufficient to explain broad measures of language performance, the structural disconnections between language areas provide additional information on the neural basis of specific and persistent language impairments at the chronic stage beyond lesion volume. Leveraging routinely available clinical data, disconnectome mapping furthers our understanding of anatomical connectivity constraints that may limit the recovery of some language abilities in chronic post-stroke aphasia.

Oscillatory beta/alpha band modulations: A potential biomarker of functional language and motor recovery in chronic stroke?

Stroke remains one of the leading causes of various disabilities, including debilitating motor and language impairments. Though various treatments exist, post-stroke impairments frequently become chronic, dramatically reducing daily life quality, and requiring specific rehabilitation. A critical goal of chronic stroke rehabilitation is to induce, usually through behavioral training, experience-dependent plasticity processes in order to promote functional recovery. However, the efficiency of such interventions is typically modest, and very little is known regarding the neural dynamics underpinning recovery processes and possible biomarkers of their efficiency. Some studies have emphasized specific alterations of excitatory–inhibitory balance within distributed neural networks as an important recovery correlate. Neural processes sensitive to these alterations, such as task-dependent oscillatory activity in beta as well as alpha bands, may be candidate biomarkers of chronic stroke functional recovery. In this review, we discuss the results of studies on motor and language recovery with a focus on oscillatory processes centered around the beta band and their modulations during functional recovery in chronic stroke. The discussion is based on a framework where task-dependent modulations of beta and alpha oscillatory activity, generated by the deep cortical excitatory–inhibitory microcircuits, serve as a neural mechanism of domain-general top-down control processes. We discuss the findings, their limitations, and possible directions for future research.

Converting sounds to meaning with ventral semantic language networks: integration of interdisciplinary data on brain connectivity, direct electrical stimulation and clinical disconnection syndromes

Numerous traditional linguistic theories propose that semantic language pathways convert sounds to meaningful concepts, generating interpretations ranging from simple object descriptions to communicating complex, analytical thinking. Although the dual-stream model of Hickok and Poeppel is widely employed, proposing a dorsal stream, mapping speech sounds to articulatory/phonological networks, and a ventral stream, mapping speech sounds to semantic representations, other language models have been proposed. Indeed, despite seemingly congruent models of semantic language pathways, research outputs from varied specialisms contain only partially congruent data, secondary to the diversity of applied disciplines, ranging from fibre dissection, tract tracing, and functional neuroimaging to neuropsychiatry, stroke neurology, and intraoperative direct electrical stimulation. The current review presents a comprehensive, interdisciplinary synthesis of the ventral, semantic connectivity pathways consisting of the uncinate, middle longitudinal, inferior longitudinal, and inferior fronto-occipital fasciculi, with special reference to areas of controversies or consensus. This is achieved by describing, for each tract, historical concept evolution, terminations, lateralisation, and segmentation models. Clinical implications are presented in three forms: (a) functional considerations derived from normal subject investigations, (b) outputs of direct electrical stimulation during awake brain surgery, and (c) results of disconnection syndromes following disease-related lesioning. The current review unifies interpretation of related specialisms and serves as a framework/thinking model for additional research on language data acquisition and integration.

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.

Biomarkers of plasticity for stroke recovery

Stroke is the commonest cause of physical disability in the world. Our understanding of the biologic mechanisms involved in recovery and repair has advanced to the point that therapeutic opportunities to promote recovery through manipulation of post-stroke plasticity have never been greater. This work has almost exclusively been carried out in rodent models of stroke with little translation into human studies. The challenge ahead is to develop a mechanistic understanding of recovery from stroke in humans. Advances in neuroimaging techniques can now provide the appropriate intermediate level of description to bridge the gap between a molecular and cellular account of recovery and a behavioral one. Clinical trials can then be designed in a stratified manner taking into account when an intervention should be delivered and who is most likely to benefit. This approach is most likely to lead to the step-change in how restorative therapeutic strategies are delivered in human stroke patients.

Tackling the Complexity of Lesion-Symptoms Mapping: How to Bridge the Gap Between Data Scientists and Clinicians?

Accurate and predictive lesion-symptoms mapping is a major goal in the field of clinical neurosciences. Recent studies have called for a reappraisal of the results given by the standard univariate voxel-based lesion-symptom mapping technique, emphasizing the need of developing multivariate methods. While the organization of large datasets and their analysis with machine learning (ML) approaches represents an opportunity to increase prediction accuracy, the complexity and dimensionality of the problem remain a major obstacle. Acknowledging the difficulty of inferring individual outcomes from the observation of spatial patterns of lesions, we propose here to base prediction on new individuals on models of brain connectivity, whereby the disruption of a given network predicts the occurrence of selective deficits. Well-suited ML tools are necessary to capture the relevant information from limited datasets and perform reliable inference.

Current and Future Challenges of Functional MRI and Diffusion Tractography in the Surgical Setting: From Eloquent Brain Mapping to Neural Plasticity

Decades ago, Spetzler (1986) and Sawaya (1998) provided a rough brain segmentation of the eloquent areas of the brain, aimed to help surgical decisions in cases of vascular malformations and tumors, respectively. Currently in clinical use, their criteria are in need of revision. Defining functions (eg, sensorimotor, language and visual) that should be preserved during surgery seems a straightforward task. In practice, locating the specific areas that could cause a permanent vs transient deficit is not an easy task. This is particularly true for the associative cortex and cognitive domains such as language. The old model, with Broca's and Wernicke's areas at the forefront, has been superseded by a dual-stream model of parallel language processing; named ventral and dorsal pathways. This complicated network of cortical hubs and subcortical white matter pathways needing preservation during surgery is a work in progress. Preserving not only cortical regions but most importantly preserving the connections, or white matter fiber bundles, of core regions in the brain is the new paradigm. For instance, the arcuate fascicululs and inferior fronto-occipital fasciculus are key components of the dorsal and ventral language pathways, respectively; and their damage result in permanent language deficits. Interestedly, the damage of the temporal portions of these bundles -where there is a crossroad with other multiple bundles-, appears to be more important (permanent) than the damage of the frontal portions - where plasticity and contralateral activation could help. Although intraoperative direct cortical and subcortical stimulation have contributed largely, advanced MR techniques such as functional MRI (fMRI) and diffusion tractography (DT), are at the epi-center of our current understanding. Nevertheless, these techniques posse important challenges: such as neurovascular uncoupling or venous bias on fMRI; and appropriate anatomical validation or accurate representation of crossing fibers on DT. These limitations should be well understood and taken into account in clinical practice. Unifying multidisciplinary research and clinical efforts is desirable, so these techniques could contribute more efficiently not only to locate eloquent areas but to improve outcomes and our understanding of neural plasticity. Finally, although there are constant anatomical and functional regions at the individual level, there is a known variability at the inter-individual level. This concept should strengthen the importance of a personalized approach when evaluating these regions on fMRI and DT. It should strengthen the importance of personalized treatments as well, aimed to meet tailored needs and expectations.

Characterising factors underlying praxis deficits in chronic left hemisphere stroke patients

Limb apraxia, a disorder of skilled action not consequent on primary motor or sensory deficits, has traditionally been defined according to errors patients make on neuropsychological tasks. Previous models of the disorder have failed to provide a unified account of patients' deficits, due to heterogeneity in the patients and tasks used. In this study we hypothesised that we may be able to map apraxic deficits onto principal components, some of which may be specific, whilst others may align with other cognitive disorders. We implemented principal component analysis (PCA) to elucidate core factors of the disorder in a preliminary cohort of 41 unselected left hemisphere chronic stroke patients who were tested on a comprehensive and validated apraxia screen. Three principal components were identified: posture selection, semantic control and multi-demand sequencing. These were submitted to a lesion symptom mapping (VBCM) analysis in a subset of 24 patients, controlled for lesion volume, age and time post-stroke. The first component revealed no significant structural correlates. The second component was related to regions in inferior frontal gyrus, primary motor area, and adjacent parietal opercular (including inferior parietal and supramarginal gyrus) areas. The third component was associated with lesions within the white matter underlying the left sensorimotor cortex, likely involving the 2nd branch of the left superior longitudinal fasciculus as well as the posterior orbitofrontal cortex (pOFC). These results highlight a significant role of common cognitive functions in apraxia, which include action selection, and sequencing, whilst more specific deficits may relate to semantic control. Moreover, they suggest that previously described 'ideomotor' and 'ideational' deficits may have a common neural basis within semantic control. Further research using this technique would help elucidate the cognitive processes underlying limb apraxia, its neural correlates and their relationship with other cognitive disorders.

Leveraging Spatial Information in Radiology Reports for Ischemic Stroke Phenotyping

Classifying fine-grained ischemic stroke phenotypes relies on identifying important clinical information. Radiology reports provide relevant information with context to determine such phenotype information. We focus on stroke phenotypes with location-specific information: brain region affected, laterality, stroke stage, and lacunarity. We use an existing fine-grained spatial information extraction system-Rad-SpatialNet-to identify clinically important information and apply simple domain rules on the extracted information to classify phenotypes. The performance of our proposed approach is promising (recall of 89.62% for classifying brain region and 74.11% for classifying brain region, side, and stroke stage together). Our work demonstrates that an information extraction system based on a fine-grained schema can be utilized to determine complex phenotypes with the inclusion of simple domain rules. These phenotypes have the potential to facilitate stroke research focusing on post-stroke outcome and treatment planning based on the stroke location.

A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients

Multivariate prediction of human behavior from resting state data is gaining increasing popularity in the neuroimaging community, with far-reaching translational implications in neurology and psychiatry. However, the high dimensionality of neuroimaging data increases the risk of overfitting, calling for the use of dimensionality reduction methods to build robust predictive models. In this work, we assess the ability of four well-known dimensionality reduction techniques to extract relevant features from resting state functional connectivity matrices of stroke patients, which are then used to build a predictive model of the associated deficits based on cross-validated regularized regression. In particular, we investigated the prediction ability over different neuropsychological scores referring to language, verbal memory, and spatial memory domains. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) were the two best methods at extracting representative features, followed by Dictionary Learning (DL) and Non-Negative Matrix Factorization (NNMF). Consistent with these results, features extracted by PCA and ICA were found to be the best predictors of the neuropsychological scores across all the considered cognitive domains. For each feature extraction method, we also examined the impact of the regularization method, model complexity (in terms of number of features that entered in the model) and quality of the maps that display predictive edges in the resting state networks. We conclude that PCA-based models, especially when combined with L1 (LASSO) regularization, provide optimal balance between prediction accuracy, model complexity, and interpretability.

Predicting language recovery in post-stroke aphasia using behavior and functional MRI

Language outcomes after speech and language therapy in post-stroke aphasia are challenging to predict. This study examines behavioral language measures and resting state fMRI (rsfMRI) as predictors of treatment outcome. Fifty-seven patients with chronic aphasia were recruited and treated for one of three aphasia impairments: anomia, agrammatism, or dysgraphia. Treatment effect was measured by performance on a treatment-specific language measure, assessed before and after three months of language therapy. Each patient also underwent an additional 27 language assessments and a rsfMRI scan at baseline. Patient scans were decomposed into 20 components by group independent component analysis, and the fractional amplitude of low-frequency fluctuations (fALFF) was calculated for each component time series. Post-treatment performance was modelled with elastic net regression, using pre-treatment performance and either behavioral language measures or fALFF imaging predictors. Analysis showed strong performance for behavioral measures in anomia (R² = 0.948, n = 28) and for fALFF predictors in agrammatism (R² = 0.876, n = 11) and dysgraphia (R² = 0.822, n = 18). Models of language outcomes after treatment trained using rsfMRI features may outperform models trained using behavioral language measures in some patient populations. This suggests that rsfMRI may have prognostic value for aphasia therapy outcomes.

Recovery of Apraxia of Speech and Aphasia in Patients With Hand Motor Impairment After Stroke

Objective: Aphasia and apraxia of speech (AOS) after stroke frequently co-occur with a hand motor impairment but few studies have investigated stroke recovery across motor and speech-language domains. In this study, we set out to test the shared recovery hypothesis. We aimed to (1) describe the prevalence of AOS and aphasia in subacute stroke patients with a hand motor impairment and (2) to compare recovery across speech-language and hand motor domains. In addition, we also explored factors predicting recovery from AOS. Methods: Seventy participants with mild to severe paresis in the upper extremity were assessed; 50% of these (n = 35) had left hemisphere (LH) lesions. Aphasia, AOS and hand motor assessments and magnetic resonance imaging were conducted at 4 weeks (A1) and at 6 months (A2) after stroke onset. Recovery was characterized in 15 participants showing initial aphasia that also had complete follow-up data at 6 months. Results: All participants with AOS and/or aphasia had LH lesions. In LH lesioned, the prevalence of aphasia was 71% and of AOS 57%. All participants with AOS had aphasia; 80% of the participants with aphasia also had AOS. Recovery in aphasia (n = 15) and AOS (n = 12) followed a parallel pattern to that observed in hand motor impairment and recovery correlated positively across speech-language and motor domains. The majority of participants with severe initial aphasia and AOS showed a limited but similar amount of recovery across domains. Lesion volume did not correlate with results from behavioral assessments, nor with recovery. The initial aphasia score was the strongest predictor of AOS recovery. Conclusion: Our findings confirm the common occurrence of AOS and aphasia in left hemisphere stroke patients with a hand motor impairment. Recovery was similar across speech-language and motor domains, even in patients with severe impairment, supporting the shared recovery hypothesis and that similar brain recovery mechanisms are involved in speech-language and motor recovery post stroke. These observations contribute to the knowledge of AOS and its relation to motor and language functions and add information that may serve as a basis for future studies of post stroke recovery. Studies including neuroimaging and/or biological assays are required to gain further knowledge on shared brain recovery mechanisms.

Neuro-Clinical Signatures of Language Impairments after Acute Stroke: A VBQ Analysis of Quantitative Native CT Scans

OBJECTIVES

Ischemic stroke affects language production and/or comprehension and leads to devastating long-term consequences for patients and their families. Previous studies have shown that neuroimaging can increase our knowledge of the basic mechanisms of language recovery. Currently, models for predicting patients' outcomes have limited use in the clinic for the evaluation and optimization of rehabilitative strategies mostly because that are often based on high-resolution magnetic resonance imaging (MRI) data, which are not always possible to carry out in the clinical routine. Here, we investigate the use of Voxel-Based Morphometry (VBM), multivariate modelling and native Computed Tomography (nCT) scans routinely acquired in the acute stage of stroke for identifying biological signatures that explicate the relationships between brain anatomy and types of impairments.

METHODS

80 stroke patients and 30 controls were included. nCT-scans were acquired in the acute ischemia stage and bedside clinical assessment from board-certified neurologist based on the NIH stroke scale. We use a multivariate Principal Component Analyses (PCA) to identify the brain signatures group the patients according to the presence or absence of impairment and identify the association between local Grey Matter (GM) and White Matter (WM) nCT values with the presence or absence of the impairment.

RESULTS

Individual patient's nCT scans were compared to a group of controls' with no radiological signs of stroke to provide an automated delineation of the lesion. Consistently across the whole group the regions that presented significant difference GM and WM values overlap with known areas that support language processing.

CONCLUSION

In summary, the method applied to nCT scans performed in the acute stage of stroke provided robust and accurate information about brain lesions' location and size, as well as quantitative values. We found that nCT and VBQ analyses are effective for identifying neural signatures of concomitant language impairments at the individual level, and neuroanatomical maps of aphasia at the population level. The signatures explicate the neurophysiological mechanisms underlying aetiology of the stroke. Ultimately, similar analyses with larger cohorts could lead to a more integrated multimodal model of behaviour and brain anatomy in the early stage of ischemic stroke.

Neuro-Clinical Signatures of Language Impairments: A Theoretical Framework for Function-to-structure Mapping in Clinics

In the past decades, neuroscientists and clinicians have collected a considerable amount of data and drastically increased our knowledge about the mapping of language in the brain. The emerging picture from the accumulated knowledge is that there are complex and combinatorial relationships between language functions and anatomical brain regions. Understanding the underlying principles of this complex mapping is of paramount importance for the identification of the brain signature of language and Neuro-Clinical signatures that explain language impairments and predict language recovery after stroke. We review recent attempts to addresses this question of language-brain mapping. We introduce the different concepts of mapping (from diffeomorphic one-to-one mapping to many-to-many mapping). We build those different forms of mapping to derive a theoretical framework where the current principles of brain architectures including redundancy, degeneracy, pluri-potentiality and bow-tie network are described.

Comparison of Oxford Cognitive Screen and Montreal Cognitive Assessment feasibility in the stroke unit setting. A pilot study

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MoCA and OCS are brief tools to assess cognition in stroke patients.

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We found good agreement between MoCA and OCS measures.

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MoCA and OCS were feasible in the stroke unit setting.

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Qualitative information related to the patients and setting were registered.

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We found high level of acceptability by patients for both tests.

Background

: Cognitive status evaluation is not routine in the acute stroke setting and there is no consensus on which neuropsychological tool is more feasible and informative. The aim of this pilot study was to compare the feasibility and acceptability of two brief cognitive tests, the Montreal Cognitive Assessment (MoCA) and the Oxford Cognitive Screen (OCS), in acute stroke, with a focus on patients' experience, administration time, and the cognitive data obtained.

Methods

: Patients with a diagnosis of ischemic or hemorrhagic stroke or of transient ischemic attack admitted to two stroke units were included. The sample consisted of 34 participants (mean age ±SD 71.1 ± 16.1 years, 25 males). Within five days of onset, patients were evaluated by means of the MoCA and OCS by a trained neuropsychologist.

Results

Both tests were feasible in the stroke unit setting and had a high level of acceptability by patients. MoCA test was fully completed by 25 patients, OCS by 21 patients. The OCS administration time was longer than that of the MoCA. However, OCS was perceived less demanding than MoCA by patients. Twenty patients completed both the MoCA and the OCS entirely, and only 2 of them did not show any impairment in both tests. Seventeen patients showed at least an impaired domain on the OCS and 15 patients presented with a MoCA global score below cut-off for cognitive impairment.

Conclusions

Our preliminary study did not show a superiority of the OCS over the widely used MoCA, and suggests the need for further validation in larger samples of stroke patients, exploring tests accuracy in detecting cognitive post-stroke impairment.

Picture naming yields highly consistent cortical activation patterns: Test-retest reliability of magnetoencephalography recordings

Reliable paradigms and imaging measures of individual-level brain activity are paramount when reaching from group-level research studies to clinical assessment of individual patients. Magnetoencephalography (MEG) provides a direct, non-invasive measure of cortical processing with high spatiotemporal accuracy, and is thus well suited for assessment of functional brain damage in patients with language difficulties. This MEG study aimed to identify, in a delayed picture naming paradigm, source-localized evoked activity and modulations of cortical oscillations that show high test-retest reliability across measurement days in healthy individuals, demonstrating their applicability in clinical settings. For patients with a language disorder picture naming can be a challenging task. Therefore, we also determined whether a semantic judgment task ('Is this item living?') with a spoken response ("yes"/"no") would suffice to induce comparably consistent activity within brain regions related to language production. The MEG data was collected from 19 healthy participants on two separate days. In picture naming, evoked activity was consistent across measurement days (intraclass correlation coefficient (ICC)>0.4) in the left frontal (400-800 ms after image onset), sensorimotor (200-800 ms), parietal (200-600 ms), temporal (200-800 ms), occipital (400-800 ms) and cingulate (600-800 ms) regions, as well as the right temporal (600-800 ms) region. In the semantic judgment task, consistent evoked activity was spatially more limited, occurring in the left temporal (200-800 ms), sensorimotor (400-800 ms), occipital (400-600 ms) and subparietal (600-800 ms) regions, and the right supramarginal cortex (600-800 ms). The delayed naming task showed typical beta oscillatory suppression in premotor and sensorimotor regions (800-1200 ms) but other consistent modulations of oscillatory activity were mostly observed in posterior cortical regions that have not typically been associated with language processing. The high test-retest consistency of MEG evoked activity in the picture naming task testifies to its applicability in clinical evaluations of language function, as well as in longitudinal MEG studies of language production in clinical and healthy populations.

Mechanisms underlying anomia treatment outcomes

Treatments for anomia have demonstrated short- and long-term efficacy. However, individual outcomes can be variable, and evidence for treatment generalization is limited. We investigated whether treatment-related measures of access to- and learning of language, namely, a) responsiveness to cues, and b) during-treatment improvements in naming, are good predictors of treatment outcomes. In addition, we investigated mechanisms underlying treatment generalization. Ten adults with chronic, post-stroke aphasia received a phonological treatment for anomia three times a week for five weeks. Naming accuracy of treated and untreated words was assessed pre- and post-treatment and at four- and eight-week follow-ups. Generalization to an untrained naming task, which involved analyses of naming accuracy and speech errors, was also assessed; speech errors were analyzed according to the Interactive Activation (IA) model of word retrieval. Group analyses indicate significant improvements in naming treated compared to untreated words, at all timepoints after therapy. Additional analyses showed significant long-term improvements in naming untreated words. Initial responsiveness to cueing and early improvement emerged as significant predictors of overall pre- to post-treatment improvements in naming treated words; naming improvements made early-on in treatment were also predictive of improvements in naming of the untreated words at follow-up. Furthermore, our study is the first to demonstrate that generalization after a phonological treatment for anomia may be driven by a strengthening of lexical-phonological connections. This study provides novel insights regarding mechanisms driving anomia treatment outcomes. Understanding such mechanisms is critical to improving existing assessment practices, optimizing treatment selection and building treatment protocols that are more likely to generalize.

A Review on Treatment-Related Brain Changes in Aphasia

Numerous studies have investigated brain changes associated with interventions targeting a range of language problems in patients with aphasia. We strive to integrate the results of these studies to examine (1) whether the focus of the intervention (i.e., phonology, semantics, orthography, syntax, or rhythmic-melodic) determines in which brain regions changes occur; and (2a) whether the most consistent changes occur within the language network or outside, and (2b) whether these are related to individual differences in language outcomes. The results of 32 studies with 204 unique patients were considered. Concerning (1), the location of treatment-related changes does not clearly depend on the type of language processing targeted. However, there is some support that rhythmic-melodic training has more impact on the right hemisphere than linguistic training. Concerning (2), we observed that language recovery is not only associated with changes in traditional language-related structures in the left hemisphere and homolog regions in the right hemisphere, but also with more medial and subcortical changes (e.g., precuneus and basal ganglia). Although it is difficult to draw strong conclusions, because there is a lack of systematic large-scale studies on this topic, this review highlights the need for an integrated approach to investigate how language interventions impact on the brain. Future studies need to focus on larger samples preserving subject-specific information (e.g., lesion effects) to cope with the inherent heterogeneity of stroke-induced aphasia. In addition, recovery-related changes in whole-brain connectivity patterns need more investigation to provide a comprehensive neural account of treatment-related brain plasticity and language recovery.

Clinical and neuroimaging factors associated with aphasia severity in stroke patients: diffusion tensor imaging study

This study investigated factors associated with aphasia severity at both 2 weeks and 3 months after stroke using demographic and clinical variables, brain diffusion tensor imaging (DTI) parameters, and lesion volume measurements. Patients with left hemisphere stroke were assessed at 2 weeks (n = 68) and at 3 months (n = 20) after stroke. Demographic, clinical, and neuroimaging data were collected; language functions were assessed using the Western Aphasia Battery. For neuroimaging, DTI parameters, including the laterality index (LI) of fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity, mean diffusivity and fibre density (FD) of the arcuate fasciculus (AF), and lesion volume, were measured. Lesion volume, cortical involvement, and the National Institutes of Health Stroke Scale score significantly predicted aphasia severity at 2 weeks after stroke, whereas the aphasia quotient and presence of depression during the early subacute stage were significant predictors at 3 months after stroke. According to Pearson correlation, LI-AD and LI-FD were significantly correlated with the aphasia quotient 2 weeks after ischaemic stroke, and the LI-FA was significantly correlated with the aphasia quotient 2 weeks after haemorrhagic stroke, suggesting that the extent and mechanism of AF injuries differ between ischaemic and haemorrhagic strokes. These differences may contribute to aphasia severity.

Pragmatic Solutions for Stroke Recovery and Improved Quality of Life in Low- and Middle-Income Countries-A Systematic Review

Background: Given the limited healthcare resources in low and middle income countries (LMICs), effective rehabilitation strategies that can be realistically adopted in such settings are required. Objective: A systematic review of literature was conducted to identify pragmatic solutions and outcomes capable of enhancing stroke recovery and quality of life of stroke survivors for low- and middle- income countries. Methods: PubMed, HINARI, and Directory of Open Access Journals databases were searched for published Randomized Controlled Trials (RCTs) till November 2018. Only completed trials published in English with non-pharmacological interventions on adult stroke survivors were included in the review while published protocols, pilot studies and feasibility analysis of trials were excluded. Obtained data were synthesized thematically and descriptively analyzed. Results: One thousand nine hundred and ninety six studies were identified while 347 (65.22% high quality) RCTs were found to be eligible for the review. The most commonly assessed variables (and outcome measure utility) were activities of daily living [75.79% of the studies, with Barthel Index (37.02%)], motor function [66.57%; with Fugl Meyer scale (71.88%)], and gait [31.12%; with 6 min walk test (38.67%)]. Majority of the innovatively high technology interventions such as robot therapy (95.24%), virtual reality (94.44%), transcranial direct current stimulation (78.95%), transcranial magnetic stimulation (88.0%) and functional electrical stimulation (85.00%) were conducted in high income countries. Several traditional and low-cost interventions such as constraint-induced movement therapy (CIMT), resistant and aerobic exercises (R&AE), task oriented therapy (TOT), body weight supported treadmill training (BWSTT) were reported to significantly contribute to the recovery of motor function, activity, participation, and improvement of quality of life after stroke. Conclusion: Several pragmatic, in terms of affordability, accessibility and utility, stroke rehabilitation solutions, and outcome measures that can be used in resource-limited settings were found to be effective in facilitating and enhancing post-stroke recovery and quality of life.

Assessing and mapping language, attention and executive multidimensional deficits in stroke aphasia

There is growing awareness that aphasia following a stroke can include deficits in other cognitive functions and that these are predictive of certain aspects of language function, recovery and rehabilitation. However, data on attentional and executive (dys)functions in individuals with stroke aphasia are still scarce and the relationship to underlying lesions is rarely explored. Accordingly in this investigation, an extensive selection of standardized non-verbal neuropsychological tests was administered to 38 individuals with chronic post-stroke aphasia, in addition to detailed language testing and MRI. To establish the core components underlying the variable patients’ performance, behavioural data were explored with rotated principal component analyses, first separately for the non-verbal and language tests, then in a combined analysis including all tests. Three orthogonal components for the non-verbal tests were extracted, which were interpreted as shift-update, inhibit-generate and speed. Three components were also extracted for the language tests, representing phonology, semantics and speech quanta. Individual continuous scores on each component were then included in a voxel-based correlational methodology analysis, yielding significant clusters for all components. The shift-update component was associated with a posterior left temporo-occipital and bilateral medial parietal cluster, the inhibit-generate component was mainly associated with left frontal and bilateral medial frontal regions, and the speed component with several small right-sided fronto-parieto-occipital clusters. Two complementary multivariate brain-behaviour mapping methods were also used, which showed converging results. Together the results suggest that a range of brain regions are involved in attention and executive functioning, and that these non-language domains play a role in the abilities of patients with chronic aphasia. In conclusion, our findings confirm and extend our understanding of the multidimensionality of stroke aphasia, emphasize the importance of assessing non-verbal cognition in this patient group and provide directions for future research and clinical practice. We also briefly compare and discuss univariate and multivariate methods for brain-behaviour mapping.

Elizabeth Usher Memorial Lecture: Lost in Translation? Challenges and future prospects for a neurobiological approach to aphasia rehabilitation

While there has been considerable progress in conducting trials of aphasia therapy, there is no consistent evidence for long-term benefits of aphasia treatment, suggesting the need to reconsider current approaches. There are also no accurate methods for determining the amount, type and timing of aphasia therapy that should be provided for an individual. At the same time, there has been increasing interest in applying various principles of neuroplasticity to aphasia treatment and using measures of brain structure and function to predict recovery. This article will consider the potential of neuroplasticity principles and neurobiological predictors to improve our current approach to aphasia rehabilitation and optimise outcomes. Reviewing these principles highlights some of the challenges of translating animal model-based principles and emphases the need to also consider relevant theories of human learning. While considerable progress has been made in considering neurobiological principles and using measures of brain structure and function to predict recovery, there is significant work required to achieve the full potential of this neurobiological approach to aphasia management.

The utility of lesion classification in predicting language and treatment outcomes in chronic stroke-induced aphasia

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.

Primate auditory prototype in the evolution of the arcuate fasciculus

The human arcuate fasciculus pathway is crucial for language, interconnecting posterior temporal and inferior frontal areas. Whether a monkey homolog exists is controversial and the nature of human-specific specialization unclear. Using monkey, ape and human auditory functional fields and diffusion-weighted MRI, we identified homologous pathways originating from the auditory cortex. This discovery establishes a primate auditory prototype for the arcuate fasciculus, reveals an earlier phylogenetic origin and illuminates its remarkable transformation.

Language Mapping in Aphasia

Purpose Recovery from aphasia is thought to depend on neural plasticity, that is, functional reorganization of surviving brain regions such that they take on new or expanded roles in language processing. To make progress in characterizing the nature of this process, we need feasible, reliable, and valid methods for identifying language regions of the brain in individuals with aphasia. This article reviews 3 recent studies from our lab in which we have developed and validated several novel functional magnetic resonance imaging paradigms for language mapping in aphasia. Method In the 1st study, we investigated the reliability and validity of 4 language mapping paradigms in neurologically normal older adults. In the 2nd study, we developed a novel adaptive semantic matching paradigm and assessed its feasibility, reliability, and validity in individuals with and without aphasia. In the 3rd study, we developed and evaluated 2 additional adaptive paradigms-rhyme judgment and syllable counting-for mapping phonological encoding regions. Results We found that the adaptive semantic matching paradigm could be performed by most individuals with aphasia and yielded reliable and valid maps of core perisylvian language regions in each individual participant. The psychometric properties of this paradigm were superior to those of other commonly used paradigms such as narrative comprehension and picture naming. The adaptive rhyme judgment paradigm was capable of identifying fronto-parietal phonological encoding regions in individual participants. Conclusion Adaptive language mapping paradigms offer a promising approach for future research on the neural basis of recovery from aphasia. Presentation Video https://doi.org/10.23641/asha.10257584.

Generalizing post-stroke prognoses from research data to clinical data

Around a third of stroke survivors suffer from acquired language disorders (aphasia), but current medicine cannot predict whether or when they might recover. Prognostic research in this area increasingly draws on datasets associating structural brain imaging data with outcome scores for ever-larger samples of stroke patients. The aim is to learn brain-behaviour trends from these data, and generalize those trends to predict outcomes for new patients. The practical significance of this work depends on the expected breadth of that generalization. Here, we show that these models can generalize across countries and native languages (from British patients tested in English to Chilean patients tested in Spanish), across neuroimaging technology (from MRI to CT), and from scans collected months or years after stroke for research purposes, to scans collected days or weeks after stroke for clinical purposes. Our results suggest one important confound, in attempting to generalize from research data to clinical data, is the delay between scan acquisition and language assessment. This delay is typically small for research data, where scans and assessments are often acquired contemporaneously. But the most natural, clinical application of these predictions will employ acute prognostic factors to predict much longer-term outcomes. We mitigated this confound by projecting the clinical patients' lesions from the time when their scans were acquired, to the time when their language abilities were assessed; with this projection in place, there was strong evidence that prognoses derived from research data generalized equally well to research and clinical data. These results encourage attention to the confounding role that lesion growth may play in other types of lesion-symptom analysis.

Language and language disorders: neuroscience to clinical practice

Language disorders are common in neurological practice but their accurate recognition and description can be challenging. In this review, we summarise the major landmarks in the understanding of language disorders and the organisation of language in the brain. We describe approaches to assessing language disorders at the bedside or in the clinic as well as the treatment and rehabilitation of aphasia. Finally, we describe how the field of neuroscience is providing new computational and neuroscientific approaches to study the mechanisms of recovery and rehabilitation of aphasia.

A Comparison of Shallow and Deep Learning Methods for Predicting Cognitive Performance of Stroke Patients From MRI Lesion Images

Stroke causes behavioral deficits in multiple cognitive domains and there is a growing interest in predicting patient performance from neuroimaging data using machine learning techniques. Here, we investigated a deep learning approach based on convolutional neural networks (CNNs) for predicting the severity of language disorder from 3D lesion images from magnetic resonance imaging (MRI) in a heterogeneous sample of stroke patients. CNN performance was compared to that of conventional (shallow) machine learning methods, including ridge regression (RR) on the images' principal components and support vector regression. We also devised a hybrid method based on re-using CNN's high-level features as additional input to the RR model. Predictive accuracy of the four different methods was further investigated in relation to the size of the training set and the level of redundancy across lesion images in the dataset, which was evaluated in terms of location and topological properties of the lesions. The Hybrid model achieved the best performance in most cases, thereby suggesting that the high-level features extracted by CNNs are complementary to principal component analysis features and improve the model's predictive accuracy. Moreover, our analyses indicate that both the size of training data and image redundancy are critical factors in determining the accuracy of a computational model in predicting behavioral outcome from the structural brain imaging data of stroke patients.

Trajectories of memory, language, and visuoperceptual problems in people with stroke during the first year and controls in Colombia

AIM

Neuropsychological normative data for Latin America have been recently published, and for Colombia, in particular, but longitudinal neuropsychological outcomes after stroke have not yet been examined in this global region. The purpose of the current study was to compare functioning of individuals with stroke in Colombia, South America during the first year post-stroke to healthy controls across neuropsychological assessments of memory, language, and visuoperceptual impairments.

METHOD

A sample of 50 individuals with stroke (mean age = 51.58) and 50 matched healthy controls (mean age = 51.54) from Colombia were included in this study. Because of a lack of access to health services, individuals with stroke did not receive any inpatient or outpatient cognitive or behavioral rehabilitation. Participants were assessed on 10 visuoperceptual, language, and memory tasks at 3, 6, and 12   months.

RESULTS

Trajectories of neuropsychological performance were significantly worse among individuals with stroke than healthy controls across every index. Further, hierarchical linear models suggested that although both individuals with stroke and controls generally improved over time on these assessments, the improvements among individuals with stroke were often of no greater magnitude than the improvements seen in controls, suggesting extremely low levels of rehabilitation gains in Colombia. Only three of the 10 neuropsychological assessments did a significant time*group interaction occur, suggesting greater gains for the stroke group than controls.

CONCLUSION

These findings suggest profound disparities in post-stroke cognitive functioning in Colombia compared to other more developed global region and underscore the importance of comprehensive cognitive rehabilitation services for individuals with stroke in Colombia and other similar global regions. Implications for rehabilitation Because this study found only negligible cognitive improvements beyond practice effects over the first year after stroke in Colombia among individuals without access to acute rehabilitation, it is imperative that comprehensive cognitive rehabilitation services be implemented immediately during the acute rehabilitation period. Memory, language, and visuoperceptual training strategies can be implemented for people with stroke in underserved global regions as part of the standard of care for stroke rehabilitation. Cognitive rehabilitation strategies should be adapted into Spanish and pilot tested in Latin America to ensure cultural equivalence. Culturally competent cognitive rehabilitation strategies should be tailored based on varied educational and literacy levels.

Progression of Aphasia Severity in the Chronic Stages of Stroke

Background and Purpose The severity of aphasic impairment in chronic stroke survivors is typically thought to be stable by 6 months postonset. However, a recent study showed that stroke survivors with aphasia experience language improvement or decline in the chronic phase, years beyond onset. Little is known about why some individuals improve whereas others remain stable or decline. Additionally, no study has tracked changes in aphasia from assessments completed at multiple time points across many years. The current study offers a comprehensive analysis of potential predictive demographic and health information to determine which factors predict dynamic changes in aphasia severity in chronic stroke. Methods Individuals in the chronic stage of a single-event, left-hemisphere ischemic stroke were identified from an archival database and included for study ( N = 39). Participants were included if they had undergone 2 or more standardized language assessments acquired at time points at least 6 months apart, with the 1st assessment at least 6 months postinjury. A linear mixed-effects model was used to determine the impact of treatment and a variety of demographic and health factors on language change. Results Over time, half of the participants improved (51%), whereas approximately a quarter (26%) decreased, and a quarter (23%) remained stable. A greater number of aphasia treatment hours significantly predicted language improvement ( p = .03), whereas older stroke age was associated with long-term decline ( p = .04). Two interactions were found to be significant in predicting improvement in individuals with diabetes: Increased exercise and younger age at stroke were significant in predicting outcomes ( p < .05). Conclusions Factors that significantly influence language recovery in chronic aphasia include stroke age and receiving aphasia treatment. For those with diabetes, increased exercise was shown to improve outcomes. Results from this study offer clinicians greater insight into the influence of patient factors on long-term recovery from stroke aphasia while suggesting a potential adjunct to language therapy: exercise. Supplemental Material https://doi.org/10.23641/asha.7849304.

The role of executive control in post-stroke aphasia treatment

Executive control (EC) ability is increasingly emerging as an important predictor of post-stroke aphasia recovery. This study examined whether EC predicted immediate treatment gains, treatment maintenance and generalization after naming therapy in ten adults with mild to severe chronic post-stroke aphasia. Performance on multiple EC tasks allowed for the creation of composite scores for common EC, and the EC processes of shifting, inhibition and working memory (WM) updating. Participants were treated three times a week for five weeks with a phonological naming therapy; difference scores in naming accuracy of treated and untreated words (assessed pre, post, four- and eight-weeks after therapy) served as the primary outcome measures. Results from simple and multiple linear regressions indicate that individuals with better shifting and WM updating abilities demonstrated better maintenance of treated words at four-week follow-up, and those with better common EC demonstrated better maintenance of treated words at both four- and eight-week follow-ups. Better shifting ability also predicted better generalization to untreated words post-therapy. Measures of EC were not indicative of improvements on treated words immediately post-treatment, nor of generalization to untreated words at follow-up. Findings suggest that immediate treatment gains, maintenance and generalization may be supported by different underlying mechanisms.

Left frontotemporal effective connectivity during semantic feature judgments in patients with chronic aphasia and age-matched healthy controls

Traditional models of neural reorganization of language skills in patients with chronic stroke-induced aphasia (PWA) propose activation of reperfused or spared left hemisphere tissue results in the most favorable language outcomes. However, these models do not fully explain variable behavioral recovery patterns observed in chronic patients. Instead, investigation of connectivity patterns of critical network nodes may elucidate better-informed recovery models. In the present study, we combined fMRI and dynamic causal modeling (DCM) to examine effective connectivity of a simple three-node left hemisphere network during a semantic feature decision task in 25 PWA and 18 age-matched neurologically intact healthy controls. The DCM model space utilized in Meier, Kapse, & Kiran (2016), which was organized according to exogenous input to one of three regions (i.e., left inferior frontal gyrus, pars triangularis [LIFGtri], left posterior middle temporal gyrus [LpMTG], or left middle frontal gyrus [LMFG]) implicated in various levels of lexical-semantic processing, was interrogated. This model space included all possible combinations of uni- and bidirectional task-modulated connections between LIFGtri, LMFG and LpMTG, resulting in 72 individual models that were partitioned into three separate families (i.e., Family #1: Input to LIFGtri, Family #2: Input to LMFG, Family #3: Input to LpMTG). Family-wise Bayesian model selection revealed Family #2: Input to LMFG best fit both patient and control data at a group level. Both groups relied heavily on LMFG's modulation of the other two model regions. By contrast, between-group differences in task-modulated coupling of LIFGtri and LpMTG were observed. Within the patient group, the strength of activity in LIFGtri and connectivity of LpMTG → LIFGtri were positively associated with lexical-semantic abilities inside and outside of the scanner, whereas greater recruitment of LpMTG was associated with poorer lexical-semantic skills.

Relative contributions of lesion location and lesion size to predictions of varied language deficits in post-stroke aphasia

Despite the widespread use of lesion-symptom mapping (LSM) techniques to study associations between location of brain damage and language deficits, the prediction of language deficits from lesion location remains a substantial challenge. The present study examined several factors which may impact lesion-symptom prediction by (1) testing the relative predictive advantage of general language deficit scores compared to composite scores that capture specific deficit types, (2) isolating the relative contribution of lesion location compared to lesion size, and (3) comparing standard voxel-based lesion-symptom mapping (VLSM) with a multivariate method (sparse canonical correlation analysis, SCCAN). Analyses were conducted on data from 128 participants who completed a detailed battery of psycholinguistic tests and underwent structural neuroimaging (MRI or CT) to determine lesion location. For both VLSM and SCCAN, overall aphasia severity (Western Aphasia Battery Aphasia Quotient) and object naming deficits were primarily predicted by lesion size, whereas deficits in Speech Production and Speech Recognition were better predicted by a combination of lesion size and location. The implementation of both VLSM and SCCAN raises important considerations regarding controlling for lesion size in lesion-symptom mapping analyses. These findings suggest that lesion-symptom prediction is more accurate for deficits within neurally-localized cognitive systems when both lesion size and location are considered compared to broad functional deficits, which can be predicted by overall lesion size alone.

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Lesion location improves prediction for speech production and speech recognition.

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Broad deficits, aphasia severity and naming, are primarily predicted by lesion size.

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Lesion location may be more informative for neurally-localized cognitive systems.

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Predictive inference is an alternative way to control for lesion size.

Predicting primary outcomes of brain tumor patients with advanced neuroimaging MRI measures

BACKGROUND

Advanced neuroimaging measures along with clinical variables acquired during standard imaging protocols provide a rich source of information for brain tumor patient treatment and management. Machine learning analysis has had much recent success in neuroimaging applications for normal and patient populations and has potential, specifically for brain tumor patient outcome prediction. The purpose of this work was to construct, using the current patient population distribution, a high accuracy predictor for brain tumor patient outcomes of mortality and morbidity (i.e., transient and persistent language and motor deficits). The clinical value offered is a statistical tool to help guide treatment and planning as well as an investigation of the influential factors of the disease process.

METHODS

Resting state fMRI, diffusion tensor imaging, and task fMRI data in combination with clinical and demographic variables were used to represent the tumor patient population (n = 62; mean age = 51.2 yrs.) in a machine learning analysis in order to predict outcomes.

RESULTS

A support vector machine classifier with a t-test filter and recursive feature elimination predicted patient mortality (18-month interval) with 80.7% accuracy, language deficits (transient) with 74.2%, motor deficits with 71.0%, language outcomes (persistent) with 80.7% and motor outcomes with 83.9%. The most influential features of the predictors were resting fMRI connectivity, and fractional anisotropy and mean diffusivity measures in the internal capsule, brain stem and superior and inferior longitudinal fasciculi.

CONCLUSIONS

This study showed that advanced neuroimaging data with machine learning methods can potentially predict patient outcomes and reveal influential factors driving the predictions.

Biomarkers of Stroke Recovery: Consensus-Based Core Recommendations from the Stroke Recovery and Rehabilitation Roundtable

The most difficult clinical questions in stroke rehabilitation are "What is this patient's potential for recovery?" and "What is the best rehabilitation strategy for this person, given her/his clinical profile?" Without answers to these questions, clinicians struggle to make decisions regarding the content and focus of therapy, and researchers design studies that inadvertently mix participants who have a high likelihood of responding with those who do not. Developing and implementing biomarkers that distinguish patient subgroups will help address these issues and unravel the factors important to the recovery process. The goal of the present paper is to provide a consensus statement regarding the current state of the evidence for stroke recovery biomarkers. Biomarkers of motor, somatosensory, cognitive and language domains across the recovery timeline post-stroke are considered; with focus on brain structure and function, and exclusion of blood markers and genetics. We provide evidence for biomarkers that are considered ready to be included in clinical trials, as well as others that are promising but not ready and so represent a developmental priority. We conclude with an example that illustrates the utility of biomarkers in recovery and rehabilitation research, demonstrating how the inclusion of a biomarker may enhance future clinical trials. In this way, we propose a way forward for when and where we can include biomarkers to advance the efficacy of the practice of, and research into, rehabilitation and recovery after stroke.

The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings

This study investigated how sample size affects the reproducibility of findings from univariate voxel-based lesion-deficit analyses (e.g., voxel-based lesion-symptom mapping and voxel-based morphometry). Our effect of interest was the strength of the mapping between brain damage and speech articulation difficulties, as measured in terms of the proportion of variance explained. First, we identified a region of interest by searching on a voxel-by-voxel basis for brain areas where greater lesion load was associated with poorer speech articulation using a large sample of 360 right-handed English-speaking stroke survivors. We then randomly drew thousands of bootstrap samples from this data set that included either 30, 60, 90, 120, 180, or 360 patients. For each resample, we recorded effect size estimates and p values after conducting exactly the same lesion-deficit analysis within the previously identified region of interest and holding all procedures constant. The results show (1) how often small effect sizes in a heterogeneous population fail to be detected; (2) how effect size and its statistical significance varies with sample size; (3) how low-powered studies (due to small sample sizes) can greatly over-estimate as well as under-estimate effect sizes; and (4) how large sample sizes (N ≥ 90) can yield highly significant p values even when effect sizes are so small that they become trivial in practical terms. The implications of these findings for interpreting the results from univariate voxel-based lesion-deficit analyses are discussed.

Resective Surgery for Double Epileptic Foci Overlapping Anterior and Posterior Language Areas: A Case of Epilepsy With Tuberous Sclerosis Complex

Tuberous sclerosis complex is a genetic systematic disorder characterized by hamartomas in multiple organs. Cortical tubers, the hamartomas in the cerebrum, cause multifocal refractory seizures. In certain cases, epileptic foci potentially involve language areas, and hence, extra- and intraoperative cortical mapping can help identify anterior and posterior areas, thus avoiding postsurgical language impairment. We report on a 21-year-old female with tuberous sclerosis complex experiencing refractory partial seizures due to two epileptic foci in the left hemisphere overlapping anterior and posterior language areas. To completely evaluate both language areas, we performed stepwise resections beginning from the anterior to the posterior epileptic focus. Although the patient presented with expressive aphasia following anterior resection, it was possible to conduct language tests during every resection. Postoperatively, she presented with expressive aphasia, comprehension deficits, left-right disorientations, and arithmetic deficits. The language dysfunctions almost disappeared at 5 weeks after the surgery and were completely resolved at 6 months after surgery. At postoperative 9 months, she was free from seizures.

Biomarkers of stroke recovery: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable

The most difficult clinical questions in stroke rehabilitation are "What is this patient's potential for recovery?" and "What is the best rehabilitation strategy for this person, given her/his clinical profile?" Without answers to these questions, clinicians struggle to make decisions regarding the content and focus of therapy, and researchers design studies that inadvertently mix participants who have a high likelihood of responding with those who do not. Developing and implementing biomarkers that distinguish patient subgroups will help address these issues and unravel the factors important to the recovery process. The goal of the present paper is to provide a consensus statement regarding the current state of the evidence for stroke recovery biomarkers. Biomarkers of motor, somatosensory, cognitive and language domains across the recovery timeline post-stroke are considered; with focus on brain structure and function, and exclusion of blood markers and genetics. We provide evidence for biomarkers that are considered ready to be included in clinical trials, as well as others that are promising but not ready and so represent a developmental priority. We conclude with an example that illustrates the utility of biomarkers in recovery and rehabilitation research, demonstrating how the inclusion of a biomarker may enhance future clinical trials. In this way, we propose a way forward for when and where we can include biomarkers to advance the efficacy of the practice of, and research into, rehabilitation and recovery after stroke.

Interpreting and Utilising Intersubject Variability in Brain Function

We consider between-subject variance in brain function as data rather than noise. We describe variability as a natural output of a noisy plastic system (the brain) where each subject embodies a particular parameterisation of that system. In this context, variability becomes an opportunity to: (i) better characterise typical versus atypical brain functions; (ii) reveal the different cognitive strategies and processing networks that can sustain similar tasks; and (iii) predict recovery capacity after brain damage by taking into account both damaged and spared processing pathways. This has many ramifications for understanding individual learning preferences and explaining the wide differences in human abilities and disabilities. Understanding variability boosts the translational potential of neuroimaging findings, in particular in clinical and educational neuroscience.

Considerations for the Use of Neuroimaging Technologies for Predicting Recovery of Speech and Language in Aphasia

PURPOSE

The number of research articles aimed at identifying neuroimaging biomarkers for predicting recovery from aphasia continues to grow. Although the clinical use of these biomarkers to determine prognosis has been proposed, there has been little discussion of how this would be accomplished. This is an important issue because the best translational science occurs when translation is considered early in the research process. The purpose of this clinical focus article is to present a framework to guide the discussion of how neuroimaging biomarkers for recovery from aphasia could be implemented clinically.

METHOD

The genomics literature reveals that implementing genetic testing in the real-world poses both opportunities and challenges. There is much similarity between these opportunities and challenges and those related to implementing neuroimaging testing to predict recovery in aphasia. Therefore, the Center for Disease Control's model list of questions aimed at guiding the review of genetic testing has been adapted to guide the discussion of using neuroimaging biomarkers as predictors of recovery in aphasia.

CONCLUSION

The adapted model list presented here is a first and useful step toward initiating a discussion of how neuroimaging biomarkers of recovery could be employed clinically to provide improved quality of care for individuals with aphasia.