The effects of lesion and treatment-related recovery on functional network modularity in post-stroke dysgraphia

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.

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

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

Speech and Language Therapy for Acquired Central Dysgraphia in Neurological Patients: A Systematic Review to Describe and Identify Trainings for Clinical Practice

PURPOSE

Acquired central dysgraphia is a heterogeneous neurological disorder that usually co-occurs with other language disorders. Written language training is relevant to improve everyday skills and as a compensatory strategy to support limited oral communication. A systematic evaluation of existing writing treatments is thus needed.

METHOD

We performed a systematic review of speech and language therapies for acquired dysgraphia in studies of neurological diseases (PROSPERO: CRD42018084221), following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist with a search on several databases for articles written in English and published until August 31, 2021. Only methodological well-designed studies were included. Further assessment of methodological quality was conducted by means of a modified version of the Downs and Black checklist.

RESULTS

Eleven studies of 43 patients in total were included. For each study, we collected data on type of population, type of impairment, experimental design, type of treatment, and measured outcomes. The studies had a medium level of assessed methodological quality. An informative description of treatments and linkages to deficits is reported.

CONCLUSIONS

Although there is a need for further experimental evidence, most treatments showed good applicability and improvement of written skills in patients with dysgraphia. Lexical treatments appear to be more frequently adopted and more flexible in improving dysgraphia and communication, especially when a multimodal approach is used. Finally, the reported description of treatment modalities for dysgraphia in relation to patients' deficits may be important for providing tailored therapies in clinical management.

Inter-hemispheric synchronicity and symmetry: The functional connectivity consequences of stroke and neurodegenerative disease

Stroke and neurodegenerative diseases differ along several dimensions, including their temporal trajectories -abrupt onset versus slow disease progression. Despite these differences, they can give rise to very similar cognitive impairments, such as specific forms of aphasia. What has been scarcely investigated, however, is the extent to which the underlying functional neuroplastic consequences are similar or different for these diseases. Here, for the first time, we directly compare changes in the brain's functional network connectivity, measured with resting-state fMRI, in stroke and progressive neurological disease. Specifically, we examined two groups of individuals with chronic post-stroke aphasia or non-fluent primary progressive aphasia, matched for their behavioral profiles and distribution of left-hemisphere damage. Using previous proposals regarding the neural functional connectivity (FC) phenotype of stroke as a starting point, we compared the two diseases in terms of homotopic FC, intra-hemispheric FC changes and also the symmetry of the FC patterns between the two hemispheres. We found, first, that progressive disease showed significantly higher levels of homotopic connectivity than neurotypical controls and, further, that stroke showed the reverse pattern. For both groups these effects were found to be behaviorally relevant. In addition, within the directly impacted left hemisphere, FC changes for the two diseases were significantly correlated. In contrast, in the right hemisphere, the FC changes differed markedly between the two groups, with the progressive disease group exhibiting rather symmetrical FC changes across the hemispheres whereas the post-stroke group showed asymmetrical FC changes across the hemispheres. These findings constitute novel evidence that the functional connectivity consequences of stroke and neurodegenerative disease can be very different despite similar behavioral outcomes and damage foci. Specifically, stroke may lead to greater independence of hemispheric responses, while neurodegenerative disease may produce more symmetrical changes across the hemispheres and more synchronized activity between the two hemispheres.

Cerebral laterality of writing in right- and left- handers: A functional transcranial Doppler ultrasound study

The cerebral lateralization of written language has received very limited research attention in comparison to the wealth of studies on the cerebral lateralization of oral language. The purpose of the present study was to further our understanding of written language lateralization, by elucidating the relative contribution of language and motor functions. We compared written word generation with a task that has equivalent visuomotor demands but does not include language: the repeated drawing of symbols. We assessed cerebral laterality using functional transcranial Doppler ultrasound (fTCD), a non-invasive, perfusion-sensitive neuroimaging technique in 23 left- and 31 right-handed participants. Findings suggest that the linguistic aspect of written word generation recruited more left-hemispheric areas during writing, in right-handers compared to left-handers. This difference could be explained by greater variability in cerebral laterality patterns within left-handers or the possibility that the areas subserving language in left-handers are broader than in right-handers. Another explanation is that the attentional demands of the more novel symbol copying task (compared to writing) contributed more right-hemispheric activation in right-handers, but this could not be captured in left-handers due to ceiling effects. Future work could investigate such attentional demands using both simple and complex stimuli in the copying condition.

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.

The role of disrupted functional connectivity in aphasia

Language is one of the most complex and specialized higher cognitive processes. Brain damage to the distributed, primarily left-lateralized language network can result in aphasia, a neurologic disorder characterized by receptive and/or expressive deficits in spoken and/or written language. Most often, aphasia is the consequence of stroke-termed poststroke aphasia (PSA)-yet, aphasia can also manifest due to neurodegenerative disease, specifically, a disorder called primary progressive aphasia (PPA). In recent years, functional connectivity neuroimaging studies have provided emerging evidence supporting theories regarding the relationships between language impairments, structural brain damage, and functional network properties in these two disorders. This chapter reviews the current evidence for the "network phenotype of stroke injury" hypothesis (Siegel et al., 2016) as it pertains to PSA and the "network degeneration hypothesis" (Seeley et al., 2009) as it pertains to PPA. Methodologic considerations for functional connectivity studies, limitations of the current functional connectivity literature in aphasia, and future directions are also discussed.

Abnormally weak functional connections get stronger in chronic stroke patients who benefit from naming therapy

Language recovery in aphasia is likely supported by a network of brain regions, but few studies have investigated treatment-related changes in functional connectivity while controlling for the absence of treatment. We examined functional connectivity in a 38-region picture-naming network in 30 patients with chronic aphasia who did or did not receive naming therapy. Compared to healthy controls, patients had abnormally low connectivity in a subset of connections from the naming network. Linear mixed models showed that the connectivity of abnormal connections increased significantly in patients who benefited from therapy, but not in those who did not benefit from or receive therapy. Changes in responders were specific to abnormal connections and did not extend to the larger network. Thus, successful naming therapy was associated with increased connectivity in connections that were abnormal prior to treatment. The potential to strengthen such connections may be a prerequisite for a successful treatment response.

Disrupted Brain Connectivity Networks in Aphasia Revealed by Resting-State fMRI

Aphasia is characterized by the disability of spontaneous conversation, listening, understanding, retelling, naming, reading, or writing. However, the neural mechanisms of language damage after stroke are still under discussion. This study aimed to investigate the global and nodal characterization of the functional networks in patients with aphasic stroke based on resting-state functional MRI (fMRI). Twenty-four right-handed patients with aphasia after stroke and 19 healthy controls (HC) underwent a 3-TfMRI scan. A whole-brain large-scale functional connectivity network was then constructed based on Power's atlas of 264 functional regions of interest, and the global and nodal topological properties of these networks were analyzed using graph theory approaches. The results showed that patients with aphasia had decreased in small-worldness (sigma), normalized clustering coefficient (gamma), and local efficiency (E_loc) values. Furthermore, E_loc was positively correlated with language ability, retelling, naming, and listening comprehension in patients with aphasia. Patients with aphasia also had decreased nodal degree and decreased nodal efficiency in the left postcentral gyrus, central opercular cortex, and insular cortex. Our results suggest that the global and local topology attributes were altered by injury in patients with aphasic stroke. We argue that the local efficiency of brain networks might be used as a potential indicator of basic speech function in patients with aphasia.

Post-Stroke Cognitive Impairment: Pathophysiological Insights into Brain Disconnectome from Advanced Neuroimaging Analysis Techniques

The neurological symptoms of stroke have traditionally provided the foundation for functional mapping of the brain. However, there are many unresolved aspects in our understanding of cerebral activity, especially regarding high-level cognitive functions. This review provides a comprehensive look at the pathophysiology of post-stroke cognitive impairment in light of recent findings from advanced imaging techniques. Combining network neuroscience and clinical neurology, our research focuses on how changes in brain networks correlate with post-stroke cognitive prognosis. More specifically, we first discuss the general consequences of stroke lesions due to damage of canonical resting-state large-scale networks or changes in the composition of the entire brain. We also review emerging methods, such as lesion-network mapping and gradient analysis, used to study the aforementioned events caused by stroke lesions. Lastly, we examine other patient vulnerabilities, such as superimposed amyloid pathology and blood-brain barrier leakage, which potentially lead to different outcomes for the brain network compositions even in the presence of similar stroke lesions. This knowledge will allow a better understanding of the pathophysiology of post-stroke cognitive impairment and provide a theoretical basis for the development of new treatments, such as neuromodulation.

Different reorganizations of functional brain networks after first-ever and recurrent ischemic stroke

Even though recurrent stroke patients constitute a large percentage of the stroke population, few studies specifically investigated their neural reorganization. In this study, we recruited seventeen first-ever stroke patients as well as fourteen recurrent stroke patients, and recorded their resting EEG signals and NIHSS score before and after two weeks of recovery, to compare their neural reorganization from network scale. The clinical improvements were comparable in two groups during the two weeks. However, their brain networks were differently reorganized, especially in the delta band. The recurrent stroke patients showed an increased clustering coefficient and a decreased characteristic path length of the delta network, along with increased ipsilesional intrahemispheric connectivity; while no such changes were observed in the first-ever stroke patients. Our results suggest that stroke history influences neural reorganization during recovery.

Language networks in aphasia and health: A 1000 participant activation likelihood estimation meta-analysis

Aphasia recovery post-stroke is classically and most commonly hypothesised to rely on regions that were not involved in language premorbidly, through 'neurocomputational invasion' or engagement of 'quiescent homologues'. Contemporary accounts have suggested, instead, that recovery might be supported by under-utilised areas of the premorbid language network, which are downregulated in health to save neural resources ('variable neurodisplacement'). Despite the importance of understanding the neural bases of language recovery clinically and theoretically, there is no consensus as to which specific regions are more likely to be activated in post-stroke aphasia (PSA) than healthy individuals. Accordingly, we performed an Activation Likelihood Estimation (ALE) meta-analysis of language functional neuroimaging studies in PSA. We obtained coordinate-based functional neuroimaging data for 481 individuals with aphasia following left-hemisphere stroke and 530 linked controls from 33 studies that met predefined inclusion criteria. ALE identified regions of consistent, above-chance spatial convergence of activation, as well as regions of significantly different activation likelihood, between participant groups and language tasks. Overall, these findings dispute the prevailing theory that aphasia recovery involves recruitment of novel right hemisphere territory into the language network post-stroke. Instead, multiple regions throughout both hemispheres were consistently activated during language tasks in both PSA and controls. Regions of the right anterior insula, frontal operculum and inferior frontal gyrus (IFG) pars opercularis were more likely to be activated across all language tasks in PSA than controls. Similar regions were more likely to be activated during higher than lower demand comprehension or production tasks, consistent with them representing enhanced utilisation of spare capacity within right hemisphere executive-control related regions. This provides novel evidence that 'variable neurodisplacement' underlies language network changes that occur post-stroke. Conversely, multiple undamaged regions were less likely to be activated across all language tasks in PSA than controls, including domain-general regions of medial superior frontal and paracingulate cortex, right IFG pars triangularis and temporal pole. These changes might represent functional diaschisis, and demonstrate that there is not global, undifferentiated upregulation of all domain-general neural resources during language in PSA. Such knowledge is essential if we are to design neurobiologically-informed therapeutic interventions to facilitate language recovery.

Investigating the network consequences of focal brain lesions through comparisons of real and simulated lesions

Given the increased interest in the functional human connectome, a number of computer simulation studies have sought to develop a better quantitative understanding of the effects of focal lesions on the brain’s functional network organization. However, there has been little work evaluating the predictions of this simulation work vis a vis real lesioned connectomes. One of the few relevant studies reported findings from real chronic focal lesions that only partially confirmed simulation predictions. We hypothesize that these discrepancies arose because although the effects of focal lesions likely consist of two components: short-term node subtraction and long-term network re-organization, previous simulation studies have primarily modeled only the short-term consequences of the subtraction of lesioned nodes and their connections. To evaluate this hypothesis, we compared network properties (modularity, participation coefficient, within-module degree) between real functional connectomes obtained from chronic stroke participants and “pseudo-lesioned” functional connectomes generated by subtracting the same sets of lesioned nodes/connections from healthy control connectomes. We found that, as we hypothesized, the network properties of real-lesioned connectomes in chronic stroke differed from those of the pseudo-lesioned connectomes which instantiated only the short-term consequences of node subtraction. Reflecting the long-term consequences of focal lesions, we found re-organization of the neurotopography of global and local hubs in the real but not the pseudo-lesioned connectomes. We conclude that the long-term network re-organization that occurs in response to focal lesions involves changes in functional connectivity within the remaining intact neural tissue that go well beyond the short-term consequences of node subtraction.

Path-dependent connectivity, not modularity, consistently predicts controllability of structural brain networks

The human brain displays rich communication dynamics that are thought to be particularly well-reflected in its marked community structure. Yet, the precise relationship between community structure in structural brain networks and the communication dynamics that can emerge therefrom is not well understood. In addition to offering insight into the structure-function relationship of networked systems, such an understanding is a critical step toward the ability to manipulate the brain's large-scale dynamical activity in a targeted manner. We investigate the role of community structure in the controllability of structural brain networks. At the region level, we find that certain network measures of community structure are sometimes statistically correlated with measures of linear controllability. However, we then demonstrate that this relationship depends on the distribution of network edge weights. We highlight the complexity of the relationship between community structure and controllability by performing numerical simulations using canonical graph models with varying mesoscale architectures and edge weight distributions. Finally, we demonstrate that weighted subgraph centrality, a measure rooted in the graph spectrum, and which captures higher order graph architecture, is a stronger and more consistent predictor of controllability. Our study contributes to an understanding of how the brain's diverse mesoscale structure supports transient communication dynamics.

Pseudoword spelling ability predicts response to word spelling treatment in acquired dysgraphia

Although rehabilitation of acquired dysgraphia can be quite effective, identifying predictors of responsiveness to treatment is useful for prognosis and individualization of treatment protocols. This study examined whether various features of treatment response were predicted by the integrity of one or more of the central cognitive components of spelling: orthographic long-term memory, orthographic working memory, and phoneme-grapheme conversion. Twenty dysgraphic individuals received 12 weeks of bi-weekly, individualized, lexically-based spelling rehabilitation using a spell-study-spell paradigm. Linear multiple regression modelling examined whether the type and severity of the dysgraphic deficit, assessed before rehabilitation, predicted the magnitude and rate of improvement, generalization to untrained items and maintenance of treatment gains. The results revealed that pseudoword spelling accuracy - indexing the integrity of the phoneme-grapheme conversion system - was the only factor examined that significantly predicted the rate of accuracy gains for trained words as well as the extent of generalization to untrained words. Pre-treatment pseudoword spelling accuracy also predicted retention of gains for trained and untrained words at 3-month follow-up. These findings reveal that the integrity of the phoneme-grapheme conversion system prior to dysgraphia rehabilitation may play a key role in rehabilitation-driven recovery, even when the treatment approach targets lexical rather than pseudoword spelling processes.

Different patterns of functional network reorganization across the variants of primary progressive aphasia: a graph-theoretic analysis

Primary progressive aphasia (PPA) is a neurodegenerative syndrome with three main variants (nonfluent, logopenic, semantic) that are identified primarily based on language deficit profiles and are associated with neurotopographically distinct atrophic patterns. We used a graph-theoretic analytic approach to examine changes in functional network properties measured with resting-state fMRI in all three PPA variants compared with age-matched healthy controls. All three variants showed a more segregated network organization than controls. To better understand the changes underlying the increased segregation, we examined the distribution of functional "hubs". We found that while all variants lost hubs in the left superior frontal and parietal regions, new hubs were recruited in different areas across the variants. In particular, both logopenic and semantic variants recruited significant numbers of hubs in the right hemisphere. Importantly, these functional characteristics could not be fully explained by local volume changes. These findings indicate that patterns of functional connectivity can serve as further evidence to distinguish the PPA variants, and provide a basis for longitudinal studies and for investigating treatment effects. This study also highlights the utility of graph-theoretic approaches in understanding the brain's functional reorganization in response to neurodegenerative disease.

How functional network connectivity changes as a result of lesion and recovery: An investigation of the network phenotype of stroke

This study, through a series of univariate and multivariate (classification) analyses, investigated fMRI task-based functional connectivity (FC) at pre- and post-treatment time-points in 18 individuals with chronic post-stroke dysgraphia. The investigation examined the effects of lesion and treatment-based recovery on functional organization, focusing on both inter-hemispheric (homotopic) and intra-hemispheric connectivity. The work confirmed, in the chronic stage, the "network phenotype of stroke injury" proposed by Siegel et al. (2016) consisting of abnormally low inter-hemispheric connectivity as well as abnormally high intra-hemispheric (ipsilesional) connectivity. In terms of recovery-based changes in FC, this study found overall hyper-normalization of these abnormal inter and intra-hemispheric connectivity patterns, suggestive of over-correction. Specifically, treatment-related homotopic FC increases were observed between left and right dorsal frontal-parietal regions. With regard to intra-hemispheric connections, recovery was dominated by increased ipsilateral connectivity between frontal and parietal regions along with decreased connectivity between the frontal regions and posterior parietal-occipital-temporal areas. Both inter and intra-hemispheric changes were associated with treatment-driven improvements in spelling performance. We suggest an interpretation according to which, with treatment, as posterior orthographic processing areas become more effective, executive control from frontal-parietal networks becomes less necessary.

Pre-treatment graph measures of a functional semantic network are associated with naming therapy outcomes in chronic aphasia

Naming treatment outcomes in post-stroke aphasia are variable and the factors underlying this variability are incompletely understood. In this study, 26 patients with chronic aphasia completed a semantic judgment fMRI task before receiving up to 12 weeks of naming treatment. Global (i.e., network-wide) and local (i.e., regional) graph theoretic measures of pre-treatment functional connectivity were analyzed to identify differences between patients who responded most and least favorably to treatment (i.e., responders and nonresponders) and determine if network measures predicted naming improvements. Responders had higher levels of global integration (i.e., average network strength and global efficiency) than nonresponders, and these measures predicted treatment effects after controlling for lesion volume and age. Group differences in local measures were identified in several regions associated with a variety of cognitive functions. These results suggest there is a meaningful and possibly prognostically-informative relationship between patients' functional network properties and their response to naming therapy.

Neuroplasticity in Aphasia: A Proposed Framework of Language Recovery

Purpose Despite a tremendous amount of research in this topic, the precise neural mechanisms underlying language recovery remain unclear. Much of the evidence suggests that activation of remaining left-hemisphere tissue, including perilesional areas, is linked to the best treatment outcomes, yet recruitment of the right hemisphere for various language tasks has also been linked to favorable behavioral outcomes. In this review article, we propose a framework of language recovery that incorporates a network-based view of the brain regions involved in recovery. Method We review evidence from the extant literature and work from our own laboratory to identify findings consistent with our proposed framework and identify gaps in our current knowledge. Results Expanding on Heiss and Thiel's (2006) hierarchy of language recovery, we identify 4 emerging themes: (a) Several bilateral regions constitute a network engaged in language recovery; (b) spared left-hemisphere regions are important components of the network engaged in language recovery; (c) as damage increases in the left hemisphere, activation expands to the right hemisphere and domain-general regions; and (d) patients with efficient, control-like network topology show greater improvement than patients with abnormal topology. We propose a mechanistic model of language recovery that accounts for individual differences in behavior, network topology, and treatment responsiveness. Conclusion Continued work in this topic will lead us to a better understanding of the mechanisms underlying language recovery, biomarkers that influence recovery, and, consequently, more personalized treatment options for individual patients. Presentation Video https://doi.org/10.23641/asha.10257590.