Four dimensions of naturalistic language production in aphasia after stroke.

There is a rich tradition of research on the neuroanatomical correlates of spoken language production in aphasia using constrained tasks (e.g., picture naming), which offer controlled insights into the distinct processes that govern speech and language (i.e., lexical-semantic access, morphosyntactic construction, phonological encoding, speech motor programming/execution). Yet these tasks do not necessarily reflect everyday language use. In contrast, naturalistic language production (also referred to as connected speech or discourse) more closely approximates typical processing demands, requiring the dynamic integration of all aspects of speech and language. The brain bases of naturalistic language production remain relatively unknown, however, in part because of the difficulty in deriving features that are salient, quantifiable, and interpretable relative to both speech-language processes and the extant literature. The present cross-sectional observational study seeks to address these challenges by leveraging a validated and comprehensive auditory-perceptual measurement system that yields four explanatory dimensions of performance-Paraphasia (misselection of words and sounds), Logopenia (paucity of words), Agrammatism (grammatical omissions), and Motor speech (impaired speech motor programming/execution). We used this system to characterize naturalistic language production in a large and representative sample of individuals with acute post-stroke aphasia (n = 118). Scores on each of the four dimensions were correlated with lesion metrics, and multivariate associations among the dimensions and brain regions were then explored. Our findings revealed distinct yet overlapping neuroanatomical correlates throughout the left-hemisphere language network. Paraphasia and Logopenia were associated primarily with posterior regions, spanning both dorsal and ventral streams, which are critical for lexical-semantic access and phonological encoding. In contrast, Agrammatism and Motor speech were associated primarily with anterior regions of the dorsal stream that are involved in morphosyntactic construction and speech motor planning/execution respectively. Collectively, we view these results as constituting a brain-behavior model of naturalistic language production in aphasia, aligning with both historical and contemporary accounts of the neurobiology of spoken language production.

Recovery from aphasia in the first year after stroke.

Most individuals who experience aphasia after a stroke recover to some extent, with the majority of gains taking place in the first year. The nature and time course of this recovery process is only partially understood, especially its dependence on lesion location and extent, which are the most important determinants of outcome. The aim of this study was to provide a comprehensive description of patterns of recovery from aphasia in the first year after stroke. We recruited 334 patients with acute left hemisphere supratentorial ischaemic or haemorrhagic stroke and evaluated their speech and language function within 5 days using the Quick Aphasia Battery (QAB). At this initial time point, 218 patients presented with aphasia. Individuals with aphasia were followed longitudinally, with follow-up evaluations of speech and language at 1 month, 3 months, and 1 year post-stroke, wherever possible. Lesions were manually delineated based on acute clinical MRI or CT imaging. Patients with and without aphasia were divided into 13 groups of individuals with similar, commonly occurring patterns of brain damage. Trajectories of recovery were then investigated as a function of group (i.e. lesion location and extent) and speech/language domain (overall language function, word comprehension, sentence comprehension, word finding, grammatical construction, phonological encoding, speech motor programming, speech motor execution, and reading). We found that aphasia is dynamic, multidimensional, and gradated, with little explanatory role for aphasia subtypes or binary concepts such as fluency. Patients with circumscribed frontal lesions recovered well, consistent with some previous observations. More surprisingly, most patients with larger frontal lesions extending into the parietal or temporal lobes also recovered well, as did patients with relatively circumscribed temporal, temporoparietal, or parietal lesions. Persistent moderate or severe deficits were common only in patients with extensive damage throughout the middle cerebral artery distribution or extensive temporoparietal damage. There were striking differences between speech/language domains in their rates of recovery and relationships to overall language function, suggesting that specific domains differ in the extent to which they are redundantly represented throughout the language network, as opposed to depending on specialized cortical substrates. Our findings have an immediate clinical application in that they will enable clinicians to estimate the likely course of recovery for individual patients, as well as the uncertainty of these predictions, based on acutely observable neurological factors.

Computer Adaptive Testing for the Assessment of Anomia Severity.

Anomia assessment is a fundamental component of clinical practice and research inquiries involving individuals with aphasia, and confrontation naming tasks are among the most commonly used tools for quantifying anomia severity. While currently available confrontation naming tests possess many ideal properties, they are ultimately limited by the overarching psychometric framework they were developed within. Here, we discuss the challenges inherent to confrontation naming tests and present a modern alternative to test development called item response theory (IRT). Key concepts of IRT approaches are reviewed in relation to their relevance to aphasiology, highlighting the ability of IRT to create flexible and efficient tests that yield precise measurements of anomia severity. Empirical evidence from our research group on the application of IRT methods to a commonly used confrontation naming test is discussed, along with future avenues for test development.

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.

Multivariate lesion symptom mapping for predicting trajectories of recovery from aphasia.

Individuals with post-stroke aphasia tend to recover their language to some extent; however, it remains challenging to reliably predict the nature and extent of recovery that will occur in the long term. The aim of this study was to quantitatively predict language outcomes in the first year of recovery from aphasia across multiple domains of language and at multiple timepoints post-stroke. We recruited 217 patients with aphasia following acute left hemisphere ischaemic or haemorrhagic stroke and evaluated their speech and language function using the Quick Aphasia Battery acutely and then acquired longitudinal follow-up data at up to three timepoints post-stroke: 1 month (n = 102), 3 months (n = 98) and 1 year (n = 74). We used support vector regression to predict language outcomes at each timepoint using acute clinical imaging data, demographic variables and initial aphasia severity as input. We found that ∼60% of the variance in long-term (1 year) aphasia severity could be predicted using these models, with detailed information about lesion location importantly contributing to these predictions. Predictions at the 1- and 3-month timepoints were somewhat less accurate based on lesion location alone, but reached comparable accuracy to predictions at the 1-year timepoint when initial aphasia severity was included in the models. Specific subdomains of language besides overall severity were predicted with varying but often similar degrees of accuracy. Our findings demonstrate the feasibility of using support vector regression models with leave-one-out cross-validation to make personalized predictions about long-term recovery from aphasia and provide a valuable neuroanatomical baseline upon which to build future models incorporating information beyond neuroanatomical and demographic predictors.

ParAlg: A Paraphasia Algorithm for Multinomial Classification of Picture Naming Errors.

PURPOSE: A preliminary version of a paraphasia classification algorithm (henceforth called ParAlg) has previously been shown to be a viable method for coding picture naming errors. The purpose of this study is to present an updated version of ParAlg, which uses multinomial classification, and comprehensively evaluate its performance when using two different forms of transcribed input. METHOD: A subset of 11,999 archival responses produced on the Philadelphia Naming Test were classified into six cardinal paraphasia types using ParAlg under two transcription configurations: (a) using phonemic transcriptions for responses exclusively (phonemic-only) and (b) using phonemic transcriptions for nonlexical responses and orthographic transcriptions for lexical responses (orthographic-lexical). Agreement was quantified by comparing ParAlg-generated paraphasia codes between configurations and relative to human-annotated codes using four metrics (positive predictive value, sensitivity, specificity, and F1 score). An item-level qualitative analysis of misclassifications under the best performing configuration was also completed to identify the source and nature of coding discrepancies. RESULTS: Agreement between ParAlg-generated and human-annotated codes was high, although the orthographic-lexical configuration outperformed phonemic-only (weighted-average F1 scores of .78 and .87, respectively). A qualitative analysis of the orthographic-lexical configuration revealed a mix of human- and ParAlg-related misclassifications, the former of which were related primarily to phonological similarity judgments whereas the latter were due to semantic similarity assignment. CONCLUSIONS: ParAlg is an accurate and efficient alternative to manual scoring of paraphasias, particularly when lexical responses are orthographically transcribed. With further development, it has the potential to be a useful software application for anomia assessment. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.22087763.

Refining Semantic Similarity of Paraphasias Using a Contextual Language Model.

PURPOSE: ParAlg (Paraphasia Algorithms) is a software that automatically categorizes a person with aphasia's naming error (paraphasia) in relation to its intended target on a picture-naming test. These classifications (based on lexicality as well as semantic, phonological, and morphological similarity to the target) are important for characterizing an individual's word-finding deficits or anomia. In this study, we applied a modern language model called BERT (Bidirectional Encoder Representations from Transformers) as a semantic classifier and evaluated its performance against ParAlg's original word2vec model. METHOD: We used a set of 11,999 paraphasias produced during the Philadelphia Naming Test. We trained ParAlg with word2vec or BERT and compared their performance to humans. Finally, we evaluated BERT's performance in terms of word-sense selection and conducted an item-level discrepancy analysis to identify which aspects of semantic similarity are most challenging to classify. RESULTS: Compared with word2vec, BERT qualitatively reduced word-sense issues and quantitatively reduced semantic classification errors by almost half. A large percentage of errors were attributable to semantic ambiguity. Of the possible semantic similarity subtypes, responses that were associated with or category coordinates of the intended target were most likely to be misclassified by both models and humans alike. CONCLUSIONS: BERT outperforms word2vec as a semantic classifier, partially due to its superior handling of polysemy. This work is an important step for further establishing ParAlg as an accurate assessment tool.

Item Response Theory Modeling of the Verb Naming Test.

PURPOSE: Item response theory (IRT) is a modern psychometric framework with several advantageous properties as compared with classical test theory. IRT has been successfully used to model performance on anomia tests in individuals with aphasia; however, all efforts to date have focused on noun production accuracy. The purpose of this study is to evaluate whether the Verb Naming Test (VNT), a prominent test of action naming, can be successfully modeled under IRT and evaluate its reliability. METHOD: We used responses on the VNT from 107 individuals with chronic aphasia from AphasiaBank. Unidimensionality and local independence, two assumptions prerequisite to IRT modeling, were evaluated using factor analysis and Yen's Q 3 statistic (Yen, 1984), respectively. The assumption of equal discrimination among test items was evaluated statistically via nested model comparisons and practically by using correlations of resulting IRT-derived scores. Finally, internal consistency, marginal and empirical reliability, and conditional reliability were evaluated. RESULTS: The VNT was found to be sufficiently unidimensional with the majority of item pairs demonstrating adequate local independence. An IRT model in which item discriminations are constrained to be equal demonstrated fit equivalent to a model in which unique discrimination parameters were estimated for each item. All forms of reliability were strong across the majority of IRT ability estimates. CONCLUSIONS: Modeling the VNT using IRT is feasible, yielding ability estimates that are both informative and reliable. Future efforts are needed to quantify the validity of the VNT under IRT and determine the extent to which it measures the same construct as other anomia tests. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.22329235.

Leukoaraiosis Is Not Associated With Recovery From Aphasia in the First Year After Stroke.

After a stroke, individuals with aphasia often recover to a certain extent over time. This recovery process may be dependent on the health of surviving brain regions. Leukoaraiosis (white matter hyperintensities on MRI reflecting cerebral small vessel disease) is one indication of compromised brain health and is associated with cognitive and motor impairment. Previous studies have suggested that leukoaraiosis may be a clinically relevant predictor of aphasia outcomes and recovery, although findings have been inconsistent. We investigated the relationship between leukoaraiosis and aphasia in the first year after stroke. We recruited 267 patients with acute left hemispheric stroke and coincident fluid attenuated inversion recovery MRI. Patients were evaluated for aphasia within 5 days of stroke, and 174 patients presented with aphasia acutely. Of these, 84 patients were evaluated at ∼3 months post-stroke or later to assess longer-term speech and language outcomes. Multivariable regression models were fit to the data to identify any relationships between leukoaraiosis and initial aphasia severity, extent of recovery, or longer-term aphasia severity. We found that leukoaraiosis was present to varying degrees in 90% of patients. However, leukoaraiosis did not predict initial aphasia severity, aphasia recovery, or longer-term aphasia severity. The lack of any relationship between leukoaraiosis severity and aphasia recovery may reflect the anatomical distribution of cerebral small vessel disease, which is largely medial to the white matter pathways that are critical for speech and language function.

An open dataset of connected speech in aphasia with consensus ratings of auditory-perceptual features.

Purpose: Auditory-perceptual rating of connected speech in aphasia (APROCSA) involves trained listeners rating a large number of perceptual features of speech samples, and has shown promise as an approach for quantifying expressive speech and language function in individuals with aphasia. The aim of this study was to obtain consensus ratings for a diverse set of speech samples, which can then be used as training materials for learning the APROCSA system. Method: Connected speech samples were recorded from six individuals with chronic post-stroke aphasia. A segment containing the first five minutes of participant speech was excerpted from each sample, and 27 features were rated on a five-point scale by five researchers. The researchers then discussed each feature in turn to obtain consensus ratings. Results: Six connected speech samples are made freely available for research, education, and clinical uses. Consensus ratings are reported for each of the 27 features, for each speech sample. Discrepancies between raters were resolved through discussion, yielding consensus ratings that can be expected to be more accurate than mean ratings. Conclusions: The dataset will provide a useful resource for scientists, students, and clinicians to learn how to evaluate aphasic speech samples with an auditory-perceptual approach.

Auditory-Perceptual Rating of Connected Speech in Aphasia.

Purpose Auditory-perceptual assessment, in which trained listeners rate a large number of perceptual features of speech samples, is the gold standard for the differential diagnosis of motor speech disorders. The goal of this study was to investigate the feasibility of applying a similar, formalized auditory-perceptual approach to the assessment of language deficits in connected speech samples from individuals with aphasia. Method Twenty-seven common features of connected speech in aphasia were defined, each of which was rated on a 5-point scale. Three experienced researchers evaluated 24 connected speech samples from the AphasiaBank database, and 12 student clinicians evaluated subsets of 8 speech samples each. We calculated interrater reliability for each group of raters and investigated the validity of the auditory-perceptual approach by comparing feature ratings to related quantitative measures derived from transcripts and clinical measures, and by examining patterns of feature co-occurrence. Results Most features were rated with good-to-excellent interrater reliability by researchers and student clinicians. Most features demonstrated strong concurrent validity with respect to quantitative connected speech measures computed from AphasiaBank transcripts and/or clinical aphasia battery subscores. Factor analysis showed that 4 underlying factors, which we labeled Paraphasia, Logopenia, Agrammatism, and Motor Speech, accounted for 79% of the variance in connected speech profiles. Examination of individual patients' factor scores revealed striking diversity among individuals classified with a given aphasia type. Conclusion Auditory-perceptual rating of connected speech in aphasia shows potential to be a comprehensive, efficient, reliable, and valid approach for characterizing connected speech in aphasia.