The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia.

BACKGROUND: Clinical variants of primary progressive aphasia (PPA) are diagnosed based on characteristic patterns of language deficits, supported by corresponding neural changes on brain imaging. However, there is (i) considerable phenotypic variability within and between each diagnostic category with partially overlapping profiles of language performance between variants and (ii) accompanying non-linguistic cognitive impairments that may be independent of aphasia magnitude and disease severity. The neurobiological basis of this cognitive-linguistic heterogeneity remains unclear. Understanding the relationship between these variables would improve PPA clinical/research characterisation and strengthen clinical trial and symptomatic treatment design. We address these knowledge gaps using a data-driven transdiagnostic approach to chart cognitive-linguistic differences and their associations with grey/white matter degeneration across multiple PPA variants. METHODS: Forty-seven patients (13 semantic, 15 non-fluent, and 19 logopenic variant PPA) underwent assessment of general cognition, errors on language performance, and structural and diffusion magnetic resonance imaging to index whole-brain grey and white matter changes. Behavioural data were entered into varimax-rotated principal component analyses to derive orthogonal dimensions explaining the majority of cognitive variance. To uncover neural correlates of cognitive heterogeneity, derived components were used as covariates in neuroimaging analyses of grey matter (voxel-based morphometry) and white matter (network-based statistics of structural connectomes). RESULTS: Four behavioural components emerged: general cognition, semantic memory, working memory, and motor speech/phonology. Performance patterns on the latter three principal components were in keeping with each variant's characteristic profile, but with a spectrum rather than categorical distribution across the cohort. General cognitive changes were most marked in logopenic variant PPA. Regardless of clinical diagnosis, general cognitive impairment was associated with inferior/posterior parietal grey/white matter involvement, semantic memory deficits with bilateral anterior temporal grey/white matter changes, working memory impairment with temporoparietal and frontostriatal grey/white matter involvement, and motor speech/phonology deficits with inferior/middle frontal grey matter alterations. CONCLUSIONS: Cognitive-linguistic heterogeneity in PPA closely relates to individual-level variations on multiple behavioural dimensions and grey/white matter degeneration of regions within and beyond the language network. We further show that employment of transdiagnostic approaches may help to understand clinical symptom boundaries and reveal clinical and neural profiles that are shared across categorically defined variants of PPA.

Distance-dependent distribution thresholding in probabilistic tractography.

Tractography is widely used in human studies of connectivity with respect to every brain region, function, and is explored developmentally, in adulthood, ageing, and in disease. However, the core issue of how to systematically threshold, taking into account the inherent differences in connectivity values for different track lengths, and to do this in a comparable way across studies has not been solved. By utilising 54 healthy individuals' diffusion-weighted image data taken from HCP, this study adopted Monte Carlo derived distance-dependent distributions (DDDs) to generate distance-dependent thresholds with various levels of alpha for connections of varying lengths. As a test case, we applied the DDD approach to generate a language connectome. The resulting connectome showed both short- and long-distance structural connectivity in the close and distant regions as expected for the dorsal and ventral language pathways, consistent with the literature. The finding demonstrates that the DDD approach is feasible to generate data-driven DDDs for common thresholding and can be used for both individual and group thresholding. Critically, it offers a standard method that can be applied to various probabilistic tracking datasets.

Decoding semantic representations in mind and brain.

A key goal for cognitive neuroscience is to understand the neurocognitive systems that support semantic memory. Recent multivariate analyses of neuroimaging data have contributed greatly to this effort, but the rapid development of these novel approaches has made it difficult to track the diversity of findings and to understand how and why they sometimes lead to contradictory conclusions. We address this challenge by reviewing cognitive theories of semantic representation and their neural instantiation. We then consider contemporary approaches to neural decoding and assess which types of representation each can possibly detect. The analysis suggests why the results are heterogeneous and identifies crucial links between cognitive theory, data collection, and analysis that can help to better connect neuroimaging to mechanistic theories of semantic cognition.

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.

Attention to attention in aphasia - elucidating impairment patterns, modality differences and neural correlates.

It is increasingly acknowledged that patients with aphasia following a left-hemisphere stroke often have difficulties in other cognitive domains. One of these domains is attention, the very fundamental ability to detect, select, and react to the abundance of stimuli present in the environment. Basic and more complex attentional functions are usually distinguished, and a variety of tests has been developed to assess attentional performance at a behavioural level. Attentional performance in aphasia has been investigated previously, but often only one specific task, stimulus modality, or type of measure was considered and usually only group-level analyses or data based on experimental tasks were presented. Also, information on brain-behaviour relationships for this cognitive domain and patient group is scarce. We report detailed analyses on a comprehensive dataset including patients' performance on various subtests of two well-known, standardised neuropsychological test batteries assessing attention. These tasks allowed us to explore: 1) how many patients show impaired performance in comparison to normative data, in which tasks and on what measure; 2) how the different tasks and measures relate to each other and to patients' language abilities; 3) the neural correlates associated with attentional performance. Up to 32 patients with varying aphasia severity were assessed with subtests from the Test of Attentional Performance (TAP) as well as the Test of Everyday Attention (TEA). Performance was compared to normative data, relationships between attention measures and other background data were explored with principal component analyses and correlations, and brain-behaviour relationships were assessed by means of voxel-based correlational methodology. Depending on the task and measure, between 3 and 53 percent of the patients showed impaired performance compared to normative data. The highest proportion of impaired performance was noted for complex attention tasks involving auditory stimuli. Patients differed in their patterns of performance and only the performance in the divided attention tests was (weakly) associated with their overall language impairment. Principal components analyses yielded four underlying factors, each being associated with distinct neural correlates. We thus extend previous research in characterizing different aspects of attentional performance within one sample of patients with chronic post stroke aphasia. Performance on a broad range of attention tasks and measures was variable and largely independent of patients' language abilities, which underlines the importance of assessing this cognitive domain in aphasic patients. Notably, a considerable proportion of patients showed difficulties with attention allocation to auditory stimuli. The reasons for these potentially modality-specific difficulties are currently not well understood and warrant additional investigations.

Damage to temporoparietal cortex is sufficient for impaired semantic control.

Semantic control allows us to focus semantic activation on currently relevant aspects of knowledge, even in the face of competition or when the required information is weakly encoded. Diverse cortical regions, including left prefrontal and posterior temporal cortex, are implicated in semantic control, however; the relative contribution of these regions is unclear. For the first time, we compared semantic aphasia (SA) patients with damage restricted to temporoparietal cortex (TPC; N = 8) to patients with infarcts encompassing prefrontal cortex (PF+; N = 22), to determine if prefrontal lesions are necessary for semantic control deficits. These SA groups were also compared with semantic dementia (SD; N = 10), characterised by degraded semantic representations. We asked whether TPC cases with semantic impairment show controlled retrieval deficits equivalent to PF+ cases or conceptual degradation similar to patients with SD. Independent of lesion location, the SA subgroups showed similarities, whereas SD patients showed a qualitatively distinct semantic impairment. Relative to SD, both TPC and PF+ SA subgroups: (1) showed few correlations in performance across tasks with differing control demands, but a strong relationship between tasks of similar difficulty; (2) exhibited attenuated effects of lexical frequency and concept familiarity, (3) showed evidence of poor semantic regulation in their verbal output - performance on picture naming was substantially improved when provided with a phonological cue, and (4) showed effects of control demands, such as retrieval difficulty, which were equivalent in severity across TPC and PF+ groups. These findings show that semantic impairment in SA is underpinned by damage to a distributed semantic control network, instantiated across anterior and posterior cortical areas.

Efficient and effective assessment of deficits and their neural bases in stroke aphasia.

OBJECTIVE: Multi-assessment batteries are necessary for diagnosing and quantifying the multifaceted deficits observed post-stroke. Extensive batteries are thorough but impractically long for clinical settings or large-scale research studies. Clinically-targeted "shallow" batteries superficially cover a wide range of language skills relatively quickly but can struggle to identify mild deficits or quantify the impairment level. Our aim was to compare these batteries across a large group of chronic stroke aphasia and to test a novel data-driven reduced version of an extensive battery that maintained sensitivity to mild impairment, ability to grade deficits and the underlying component structure. METHODS: We tested 75 chronic left-sided stroke participants, spanning global to mild aphasia. The underlying structure of these three batteries was analysed using cross-validation and principal component analysis, in addition to univariate and multivariate lesion-symptom mapping. RESULTS: This revealed a four-factor solution for the extensive and data-reduced batteries, identifying phonology, semantic skills, fluency and executive function in contrast to a two-factor solution using the shallow battery (language severity and cognitive severity). Lesion symptom mapping using participants' factor scores identified convergent neural structures for phonology (superior temporal gyrus), semantics (inferior temporal gyrus), speech fluency (precentral gyrus) and executive function (lateral occipitotemporal cortex). The two shallow battery components converged with the phonology and executive function clusters. In addition, we show that multivariate models could predict the component scores using neural data, however not for every component. CONCLUSIONS: Overall, the data-driven battery appears to be an effective way to save time yet retain maintained sensitivity to mild impairment, ability to grade deficits and the underlying component structure observed in post-stroke aphasia.

An efficient, accurate and clinically-applicable index of content word fluency in Aphasia.

Background: Despite the clinical importance of assessing the efficiency and accuracy of fluency in terms of content words production during connected speech, assessments based on discourse tasks are very time-consuming and thus not clinically feasible. Aims: (1) Examine the relationship between single-word naming and word retrieval during discourse production. (2) Investigate the relationship between word retrieval and content word fluency derived from a simple versus naturalistic discourse tasks. (3) Develop and validate an efficient and accurate index of content word fluency that is clinically viable. Methods: Two discourse tasks (simple picture description and naturalistic storytelling narrative) were collected from 46 participants with post-stroke aphasia, and 20 age/education matched neuro-typical controls. Each discourse sample was fully transcribed and quantitative analysis was applied to each sample to measure word retrieval and content word fluency. Three single-word naming tasks were also administered to each participant with aphasia. Results: Correlational analyses between single-word naming and word retrieval in connected speech revealed weak/moderate relationships. Conversely, strong correlations were found between measures derived from simple picture description against naturalistic storytelling discourse tasks. Moreover, we derived a novel, transcription-less index of content word fluency from the discourse samples of an independent group (neuro-typical controls), and then we validated this index across two discourse tasks in the tested group (persons with aphasia). Correlation and regression analyses revealed extremely strong relationships between participants' (neuro-typical controls and persons with aphasia) scores on the novel index and measures of content word fluency derived from the formal transcription and quantitative analyses of discourse samples, indicating high accuracy and validity of the new index. Conclusions: Simple picture description rather than picture naming provides a better estimate of word retrieval in naturalistic connected speech. The novel developed index is transcription-less and can be implemented online to provide an accurate and efficient measure of content word fluency. Thus, it is viable during clinical practice for assessment purposes, and possibly as an outcome measure to monitor therapy effectiveness, which can also be used in randomised clinical trials.

Mapping lesion, structural disconnection, and functional disconnection to symptoms in semantic aphasia.

Patients with semantic aphasia have impaired control of semantic retrieval, often accompanied by executive dysfunction following left hemisphere stroke. Many but not all of these patients have damage to the left inferior frontal gyrus, important for semantic and cognitive control. Yet semantic and cognitive control networks are highly distributed, including posterior as well as anterior components. Accordingly, semantic aphasia might not only reflect local damage but also white matter structural and functional disconnection. Here, we characterise the lesions and predicted patterns of structural and functional disconnection in individuals with semantic aphasia and relate these effects to semantic and executive impairment. Impaired semantic cognition was associated with infarction in distributed left-hemisphere regions, including in the left anterior inferior frontal and posterior temporal cortex. Lesions were associated with executive dysfunction within a set of adjacent but distinct left frontoparietal clusters. Performance on executive tasks was also associated with interhemispheric structural disconnection across the corpus callosum. In contrast, poor semantic cognition was associated with small left-lateralized structurally disconnected clusters, including in the left posterior temporal cortex. Little insight was gained from functional disconnection symptom mapping. These results demonstrate that while left-lateralized semantic and executive control regions are often damaged together in stroke aphasia, these deficits are associated with distinct patterns of structural disconnection, consistent with the bilateral nature of executive control and the left-lateralized yet distributed semantic control network.

Parallel transmit (pTx) with online pulse design for task-based fMRI at 7 T.

PURPOSE: Parallel transmission (pTx) is an approach to improve image uniformity for ultra-high field imaging. In this study, we modified an echo planar imaging (EPI) sequence to design subject-specific pTx pulses online. We compared its performance against EPI with conventional circularly polarised (CP) pulses. METHODS: We compared the pTx-EPI and CP-EPI sequences in a short EPI acquisition protocol and for two different functional paradigms in six healthy volunteers (2 female, aged 23-36 years, mean age 29.2 years). We chose two paradigms that are typically affected by signal dropout at 7 T: a visual objects localiser to determine face/scene selective brain regions and a semantic-processing task. RESULTS: Across all subjects, pTx-EPI improved whole-brain mean temporal signal-to-noise ratio (tSNR) by 11.0% compared to CP-EPI. We also compared the ability of pTx-EPI and CP-EPI to detect functional activation for three contrasts over the two paradigms: face > object and scene > object for the visual objects localiser and semantic association > pattern matching for the semantic-processing paradigm. Across all three contrasts, pTx-EPI showed higher median z-scores and detected more active voxels in relevant areas, as determined from previous 3 T studies. CONCLUSION: We have demonstrated a workflow for EPI acquisitions with online per-subject pulse calculations. We saw improved performance in both tSNR and functional acquisitions from pTx-EPI. Thus, we believe that online calculation pTx-EPI is robust enough for future fMRI studies, especially where activation is expected in brain areas liable to significant signal dropout.

Assessing executive functions in post-stroke aphasia-utility of verbally based tests.

It is increasingly acknowledged that, often, patients with post-stroke aphasia not only have language impairments but also deficits in other cognitive domains (e.g. executive functions) that influence recovery and response to therapy. Many assessments of executive functions are verbally based and therefore usually not administered in this patient group. However, the performance of patients with aphasia in such tests might provide valuable insights both from a theoretical and clinical perspective. We aimed to elucidate (i) if verbal executive tests measure anything beyond the language impairment in patients with chronic post-stroke aphasia, (ii) how performance in such tests relates to performance in language tests and nonverbal cognitive functions, and (iii) the neural correlates associated with performance in verbal executive tests. In this observational study, three commonly used verbal executive tests were administered to a sample of patients with varying aphasia severity. Their performance in these tests was explored by means of principal component analyses, and the relationships with a broad range of background tests regarding their language and nonverbal cognitive functions were elucidated with correlation analyses. Furthermore, lesion analyses were performed to explore brain-behaviour relationships. In a sample of 32 participants, we found that: (i) a substantial number of patients with aphasia were able to perform the verbal executive tests; (ii) variance in performance was not explained by the severity of an individual's overall language impairment alone but was related to two independent behavioural principal components per test; (iii) not all aspects of performance were related to the patient's language abilities; and (iv) all components were associated with separate neural correlates, some overlapping partly in frontal and parietal regions. Our findings extend our clinical and theoretical understanding of dysfunctions beyond language in patients with aphasia.

Demographic, clinical and neuroimaging markers of post-stroke emotionalism: A preliminary investigation.

INTRODUCTION: Post stroke emotionalism (PSE) is a common but poorly understood condition. The value of altered brain structure as a putative risk factor for PSE alongside routinely available demographic and clinical variables has yet to be elucidated. METHODS: 85 patients were recruited from acute inpatient settings within 2 weeks of stroke. PSE was diagnosed using a validated semi-structured interview and standardised measures of stroke severity, functional ability, cognition, mood and quality of life were obtained. Neuroimaging variables (intracranial volume and volumes of cortical grey matter, subcortical grey matter, normal appearing white matter, cerebrum, cerebrospinal fluid and stroke; white matter hyperintensities; and mean cortical thickness) were derived using standardised methods from Magnetic Resonance Imaging (MRI) studies. The relationships between PSE diagnosis, brain structure, demographic and clinical variables were investigated using machine learning algorithms to determine how well different sets of predictors could classify PSE. RESULTS: The model with the best performance was derived from neuroradiological variables alone (sensitivity = 0.75; specificity = 0.8235), successfully classifying 9/12 individuals with PSE and 28/34 non-PSE cases. CONCLUSIONS: Neuroimaging measures appear to be important in PSE. Future work is needed to determine which specific variables are key. Imaging may complement standard behavioural measures and aid clinicians and researchers.

Direct Neural Evidence for the Contrastive Roles of the Complementary Learning Systems in Adult Acquisition of Native Vocabulary.

The Complementary Learning Systems (CLS) theory provides a powerful framework for considering the acquisition, consolidation, and generalization of new knowledge. We tested this proposed neural division of labor in adults through an investigation of the consolidation and long-term retention of newly learned native vocabulary with post-learning functional neuroimaging. Newly learned items were compared with two conditions: 1) previously known items to highlight the similarities and differences with established vocabulary and 2) unknown/untrained items to provide a control for non-specific perceptual and motor speech output. Consistent with the CLS, retrieval of newly learned items was supported by a combination of regions associated with episodic memory (including left hippocampus) and the language-semantic areas that support established vocabulary (left inferior frontal gyrus and left anterior temporal lobe). Furthermore, there was a shifting division of labor across these two networks in line with the items' consolidation status; faster naming was associated with more activation of language-semantic areas and lesser activation of episodic memory regions. Hippocampal activity during naming predicted more than half the variation in naming retention 6 months later.

Content Word Production during Discourse in Aphasia: Deficits in Word Quantity, Not Lexical-Semantic Complexity.

Although limited and reduced connected speech production is one, if not the most, prominent feature of aphasia, few studies have examined the properties of content words produced during discourse in aphasia, in comparison to the many investigations of single-word production. In this study, we used a distributional analysis approach to investigate the properties of content word production during discourse by 46 participants spanning a wide range of chronic poststroke aphasia and 20 neurotypical adults, using different stimuli that elicited three discourse genres (descriptive, narrative, and procedural). Initially, we inspected the discourse data with respect to the quantity of production, lexical-semantic diversity, and psycholinguistic features (frequency and imageability) of content words. Subsequently, we created a "lexical-semantic landscape," which is sensitive to subtle changes and allowed us to evaluate the pattern of changes in discourse production across groups. Relative to neurotypical adults, all persons with aphasia (both fluent and nonfluent) showed significant reduction in the quantity and diversity of production, but the lexical-semantic complexity of word production directly mirrored neurotypical performance. Specifically, persons with aphasia produced the same rate of nouns/verbs, and their discourse samples covered the full range of word frequency and imageability, albeit with reduced word quantity. These findings provide novel evidence that, unlike in other disorders (e.g., semantic dementia), discourse production in poststroke aphasia has relatively preserved lexical-semantic complexity but demonstrates significantly compromised quantity of content word production. Voxel-wise lesion-symptom mapping using both univariate and multivariate approaches revealed left frontal regions particularly the pars opercularis, insular cortex, and central and frontal opercular cortices supporting word retrieval during connected speech, irrespective of their word class or lexical-semantic complexity.

The verbal, non-verbal and structural bases of functional communication abilities in aphasia.

The ability to communicate, functionally, after stroke or other types of acquired brain injury is crucial for the person involved and the people around them. Accordingly, assessment of functional communication is increasingly used in large-scale randomized controlled trials as the primary outcome measure. Despite the importance of functional communication abilities to everyday life and their centrality to the measured efficacy of aphasia interventions, there is little knowledge about how commonly used measures of functional communication relate to each other, whether they capture and grade the full range of patients' remaining communication skills and how these abilities relate to the patients' verbal and non-verbal impairments as well as the underpinning lesions. Going beyond language-only factors is essential given that non-verbal abilities can play a crucial role in an individual's ability to communicate effectively. This study, based on a large sample of patients covering the full range and types of post-stroke aphasia, addressed these important, open questions. The investigation combined data from three established measures of functional communication with a thorough assessment of verbal and non-verbal cognition as well as structural neuroimaging. The key findings included: (i) due to floor or ceiling effects, the full range of patients' functional communication abilities was not captured by a single assessment alone, limiting the utility of adopting individual tests as outcome measures in randomized controlled trials; (ii) phonological abilities were most strongly related to all measures of functional communication and (iii) non-verbal cognition was particularly crucial when language production was relatively impaired and other modes of communication were allowed, when patients rated their own communication abilities, and when carers rated patients' basic communication abilities. Finally, in addition to lesion load being significantly related to all measures of functional communication, lesion analyses showed partially overlapping clusters in language regions for the functional communication tests. Moreover, mirroring the findings from the regression analyses, additional regions previously associated with non-verbal cognition emerged for the Scenario Test and for the Patient Communication Outcome after Stroke rating scale. In conclusion, our findings elucidated the cognitive and neural bases of functional communication abilities, which may inform future clinical practice regarding assessments and therapy. In particular, it is necessary to use more than one measure to capture the full range and multifaceted nature of patients' functional communication abilities and a therapeutic focus on non-verbal cognition might have positive effects on this important aspect of activity and participation.

Evaluating the granularity and statistical structure of lesions and behaviour in post-stroke aphasia.

The pursuit of relating the location of neural damage to the pattern of acquired language and general cognitive deficits post-stroke stems back to the 19th century behavioural neurology. While spatial specificity has improved dramatically over time, from the large areas of damage specified by post-mortem investigation to the millimetre precision of modern MRI, there is an underlying issue that is rarely addressed, which relates to the fact that damage to a given area of the brain is not random but constrained by the brain's vasculature. Accordingly, the aim of this study was to uncover the statistical structure underlying the lesion profile in chronic aphasia post-stroke. By applying varimax-rotated principal component analysis to the lesions of 70 patients with chronic post-stroke aphasia, we identified 17 interpretable clusters, largely reflecting the vascular supply of middle cerebral artery sub-branches and other sources of individual variation in vascular supply as shown in classical angiography studies. This vascular parcellation produced smaller displacement error in simulated lesion-symptom analysis compared with individual voxels and Brodmann regions. A second principal component analysis of the patients' detailed neuropsychological data revealed a four-factor solution reflecting phonological, semantic, executive-demand and speech fluency abilities. As a preliminary exploration, stepwise regression was used to relate behavioural factor scores to the lesion principal components. Phonological ability was related to two components, which covered the posterior temporal region including the posterior segment of the arcuate fasciculus, and the inferior frontal gyrus. Three components were linked to semantic ability and were located in the white matter underlying the anterior temporal lobe, the supramarginal gyrus and angular gyrus. Executive-demand related to two components covering the dorsal edge of the middle cerebral artery territory, while speech fluency was linked to two components that were located in the middle frontal gyrus, precentral gyrus and subcortical regions (putamen and thalamus). Future studies can explore in formal terms the utility of these principal component analysis-derived lesion components for relating post-stroke lesions and symptoms.

Graded, multidimensional intra- and intergroup variations in primary progressive aphasia and post-stroke aphasia.

Language impairments caused by stroke (post-stroke aphasia, PSA) and neurodegeneration (primary progressive aphasia, PPA) have overlapping symptomatology, nomenclature and are classically divided into categorical subtypes. Surprisingly, PPA and PSA have rarely been directly compared in detail. Rather, previous studies have compared certain subtypes (e.g. semantic variants) or have focused on a specific cognitive/linguistic task (e.g. reading). This study assessed a large range of linguistic and cognitive tasks across the full spectra of PSA and PPA. We applied varimax-rotated principal component analysis to explore the underlying structure of the variance in the assessment scores. Similar phonological, semantic and fluency-related components were found for PSA and PPA. A combined principal component analysis across the two aetiologies revealed graded intra- and intergroup variations on all four extracted components. Classification analysis was used to test, formally, whether there were any categorical boundaries for any subtypes of PPA or PSA. Semantic dementia formed a true diagnostic category (i.e. within group homogeneity and distinct between-group differences), whereas there was considerable overlap and graded variations within and between other subtypes of PPA and PSA. These results suggest that (i) a multidimensional rather than categorical classification system may be a better conceptualization of aphasia from both causes; and (ii) despite the very different types of pathology, these broad classes of aphasia have considerable features in common.

Investigating the effect of changing parameters when building prediction models for post-stroke aphasia.

Neuroimaging has radically improved our understanding of how speech and language abilities map to the brain in normal and impaired participants, including the diverse, graded variations observed in post-stroke aphasia. A handful of studies have begun to explore the reverse inference: creating brain-to-behaviour prediction models. In this study, we explored the effect of three critical parameters on model performance: (1) brain partitions as predictive features, (2) combination of multimodal neuroimaging and (3) type of machine learning algorithms. We explored the influence of these factors while predicting four principal dimensions of language and cognition variation in post-stroke aphasia. Across all four behavioural dimensions, we consistently found that prediction models derived from diffusion-weighted data did not improve performance over models using structural measures extracted from T1 scans. Our results provide a set of principles to guide future work aiming to predict outcomes in neurological patients from brain imaging data.

A unified model of post-stroke language deficits including discourse production and their neural correlates.

The clinical profiles of individuals with post-stroke aphasia demonstrate considerable variation in the presentation of symptoms. Recent aphasiological studies have attempted to account for this individual variability using a multivariate data-driven approach (principal component analysis) on an extensive neuropsychological and aphasiological battery, to identify fundamental domains of post-stroke aphasia. These domains mainly reflect phonology, semantics and fluency; however, these studies did not account for variability in response to different forms of connected speech, i.e. discourse genres. In the current study, we initially examined differences in the quantity, diversity and informativeness between three different discourse genres, including a simple descriptive genre and two naturalistic forms of connected speech (storytelling narrative, and procedural discourse). Subsequently, we provided the first quantitative investigation on the multidimensionality of connected speech production at both behavioural and neural levels. Connected speech samples across descriptive, narrative, and procedural discourse genres were collected from 46 patients with chronic post-stroke aphasia and 20 neurotypical adults. Content analyses conducted on all connected speech samples indicated that performance differed across discourse genres and between groups. Specifically, storytelling narratives provided higher quantities of content words and lexical diversity compared to composite picture description and procedural discourse. The analyses further revealed that, relative to neurotypical adults, patients with aphasia, both fluent and non-fluent, showed reduction in the quantity of verbal production, lexical diversity, and informativeness across all discourses. Given the differences across the discourses, we submitted the connected speech metrics to principal component analysis alongside an extensive neuropsychological/aphasiological battery that assesses a wide range of language and cognitive skills. In contrast to previous research, three unique orthogonal connected speech components were extracted in a unified model, reflecting verbal quantity, verbal quality, and motor speech, alongside four core language and cognitive components: phonological production, semantic processing, phonological recognition, and executive functions. Voxel-wise lesion-symptom mapping using these components provided evidence on the involvement of widespread cortical regions and their white matter connections. Specifically, left frontal regions and their underlying white matter tracts corresponding to the frontal aslant tract and the anterior segment of the arcuate fasciculus were particularly engaged with the quantity and quality of fluent connected speech production while controlling for other co-factors. The neural correlates associated with the other language domains align with existing models on the ventral and dorsal pathways for language processing.