Andrew T. DeMarco's research while affiliated with Georgetown University Medical Center and other places

Research over the past several decades has revealed that non-linguistic cognitive impairments can appear alongside language deficits in individuals with aphasia. One vulnerable cognitive domain is executive function, an umbrella term for the higher-level cognitive processes that allow us to direct our behavior towards a goal. Studies in healthy adults reveal that executive function abilities are supported by inner speech, the ability to use language silently in one’s head. Therefore, inner speech may mediate the connection between language and executive function deficits in individuals with aphasia.Here, we investigated whether inner speech ability links language and cognitive impairments in 59 adults with chronic, post-stroke aphasia. We used two approaches to measure inner speech: one based on internal retrieval of words and one based on internal retrieval plus silent manipulation of the retrieved phonological forms. Then, we examined relationships between these two approaches to measuring inner speech and five aspects of executive function ability: response inhibition, conflict monitoring/resolution, general task-switching ability, phonological control, and semantic control. We also looked for dissociations between inner speech ability and executive function ability.Our results show tentative relationships between inner speech and all aspects of executive function examined in the study. The most consistent relationships were found between executive function and measures of inner speech that require both retrieval and manipulation of internal representations of words (e.g., silent picture-pair rhyme judgment). We also found evidence for a double dissociation: many participants show intact executive function despite poor inner speech, and vice versa, so neither process is strictly reliant on the other. We suggest that this work provides preliminary evidence of a bidirectional relationship between inner speech and executive function: inner speech supports some aspects of executive function via internal self-cueing and certain aspects of executive function support performance on complex inner speech tasks.

OBJECTIVES/GOALS: Many left hemisphere stroke survivors have a reading disorder (alexia), which is experienced as decreasing well-being. Therapies produce inconsistent results, demonstrating a need for treatment response predictors. We are investigating neural correlates of reading computational models to identify biomarkers to improve therapeutic outcomes. METHODS/STUDY POPULATION: Artificial neural network models of reading, mapping between orthography (visual word form), phonology (auditory word form), and semantics (word meaning), are trained to read single words at a healthy, adult capacity. The models are independently damaged to reflect the individual orthography-to-semantics, semantics-to-phonology, and orthography-to-phonology deficits of a sample of left hemisphere stroke survivors (n = 85). These deficits are measured with cognitive tests assessing the intactness of mappings between representations. Model damage is enacted by removing percentages of the connections between representations. For each type of deficit, the percentages of links removed are entered into a voxel-based lesion symptom mapping analysis to identify areas of cortex associated with that mapping. RESULTS/ANTICIPATED RESULTS: We anticipate that the neural correlates of model layers will be localized to a mostly left-lateralized network. Increased damage to the links between semantics and phonology in the model will likely be related to lesions involving the left posterior superior temporal sulcus and inferior frontal gyrus (IFG). Damaged orthography-to-semantic links will be related to the left fusiform gyrus (FG) and IFG. Finally, damage to the orthography-to-phonology links will be related to the left FG and superior temporal gyrus. DISCUSSION/SIGNIFICANCE: Mapping components of language models onto the brain will improve our understanding of the neural networks supporting language processing. Identifying these neural correlates may also produce biomarkers that can be used in predicting reading impairment at the acute stage or optimizing therapy in the chronic stage of stroke.

After initial bilateral acoustic processing of the speech signal, much of the subsequent language processing is left-lateralized. The reason for this lateralization remains an open question. Prevailing hypotheses describe a left hemisphere (LH) advantage for rapidly unfolding information—such as the segmental (e.g., phonetic and phonemic) components of speech. Here we investigated whether and where damage to the LH predicted impaired performance on judging the directionality of frequency modulated (FM) sweep stimuli that changed within short (25ms) or longer (250ms) temporal windows. Performance was significantly lower for stroke survivors (n = 50; 18 female) than controls (n = 61; 34 female) on FM Sweeps judgments, particularly on the short sweeps. Support vector regression lesion-symptom mapping (SVR-LSM) revealed that part of the left planum temporale (PT) was related to worse performance on judging the short FM sweeps, controlling for performance on the long sweeps. We then investigated whether damage to this particular area related to diminished performance on two levels of linguistic processing that theoretically depend on rapid auditory processing: stop consonant identification and pseudoword repetition. We separated stroke participants into subgroups based on whether their LH lesion included the part of the left PT that related to diminished short sweeps judgments. Participants with PT lesions (PT lesion+, n = 24) performed significantly worse than those without (PT lesion-, n = 26) on stop consonant identification and pseudoword repetition, controlling for lesion size and hearing ability. Interestingly, PT lesions impacted pseudoword repetition more than real word repetition (PT lesion-by-repetition trial type interaction), which is of interest because pseudowords rely solely on sound perception and sequencing, whereas words can also rely on lexical-semantic knowledge. We conclude that the left PT is a critical region for processing auditory information in short temporal windows, and it may also be an essential transfer point in auditory-to-linguistic processing.

Stroke is one of the most common causes of disability, and there are few treatments that can improve recovery after stroke. Therapeutic development has been hindered because of a lack of understanding of precisely how neural circuits are affected by stroke, and how these circuits change to mediate recovery. Indeed, some of the hypotheses for how the CNS changes to mediate recovery, including remapping, redundancy, and diaschisis, date to more than a century ago. Recent technological advances have enabled the interrogation of neural circuits with ever greater temporal and spatial resolution. These techniques are increasingly being applied across animal models of stroke and to human stroke survivors, and are shedding light on the molecular, structural, and functional changes that neural circuits undergo after stroke. Here we review these studies and highlight important mechanisms that underlie impairment and recovery after stroke. We begin by summarizing knowledge about changes in neural activity that occur in the peri-infarct cortex, specifically considering evidence for the functional remapping hypothesis of recovery. Next, we describe the importance of neural population dynamics, disruptions in these dynamics after stroke, and how allocation of neurons into spared circuits can restore functionality. On a more global scale, we then discuss how effects on long-range pathways, including interhemispheric interactions and corticospinal tract transmission, contribute to post-stroke impairments. Finally, we look forward and consider how a deeper understanding of neural circuit mechanisms of recovery may lead to novel treatments to reduce disability and improve recovery after stroke.

Despite the many mistakes we make while speaking, people can effectively communicate because we monitor our speech errors. However, the cognitive abilities and brain structures that support speech error monitoring are unclear. There may be different abilities and brain regions that support monitoring phonological speech errors versus monitoring semantic speech errors. We investigated speech, language, and cognitive control abilities that relate to detecting phonological and semantic speech errors in 41 individuals with aphasia who underwent detailed cognitive testing. Then, we used support vector regression lesion symptom mapping to identify brain regions supporting detection of phonological versus semantic errors in a group of 76 individuals with aphasia. The results revealed that motor speech deficits as well as lesions to the ventral motor cortex were related to reduced detection of phonological errors relative to semantic errors. Detection of semantic errors selectively related to auditory word comprehension deficits. Across all error types, poor cognitive control related to reduced detection. We conclude that monitoring of phonological and semantic errors relies on distinct cognitive abilities and brain regions. Furthermore, we identified cognitive control as a shared cognitive basis for monitoring all types of speech errors. These findings refine and expand our understanding of the neurocognitive basis of speech error monitoring.

Background Discourse analyses yield quantitative measures of functional communication in aphasia. However, they are historically underutilized in clinical settings. Confrontation naming assessments are used widely clinically and have been used to estimate discourse-level production. Such work shows that naming accuracy explains moderately high proportions of variance in measures of discourse, but proportions of variance remain unexplained. We propose that the inclusion of circumlocution productions into predictive models will account for a significant amount more of the variance. Circumlocution productions at the naming-level, while they may not contain the target word, are similar to the content that contributes to discourse informativeness and efficiency. Thus, additionally measuring circumlocution may improve our ability to estimate discourse performance and functional communication. Aim This study aimed to test whether, after controlling for naming accuracy, the addition of a measure of circumlocution into predictive models of discourse-level informativeness and efficiency would account for a significant amount more of the variance in these discourse-level outcomes. Methods & Procedures Naming and discourse data from 43 people with poststroke aphasia were analyzed. Naming data were collected using 120 pictured items and discourse data were collected using two picture description prompts. Data scoring and coding yielded measures of naming accuracy, incorrect response type, communicative informativeness, and efficiency. We used robust hierarchical regression to evaluate study predictions. Outcomes & Results After controlling for naming accuracy, the inclusion of circumlocution into predictive models accounted for a significant amount more of the variance in both informativeness and efficiency. The subsequent inclusion of other response types, such as real word and nonword errors, did not account for a significant amount more of the variance in either outcome. Conclusions In addition to naming accuracy, the production of circumlocution during naming assessments may correspond with measures of informativeness and efficiency at the discourse-level. Reducing the burden of estimating patients’ functional communication will increase our ability to estimate functional communication using tools that are easy to administer and interpret.

Introduction In stroke survivors with aphasia (SWA), differences in behavioral language performance have been observed between Black and White Americans. These racial differences in aphasia outcomes may reflect biological stroke severity, disparities in access to care, potential assessment bias, or interactions between these factors and race. Understanding the origin of disparities in aphasia outcomes is critical to any efforts to promote health equity among SWA. In this study, we explore aphasia outcomes by examining the relationship between race, socioeconomic status, and neurological factors in SWA. Method Eighty-five chronic left-hemisphere SWA (31 Black, 54 White) participated in the study. The primary aphasia outcome measure was the Western Aphasia Battery-Revised (WAB-R). Lesion size was measured based on manual lesion segmentations. FLAIR and T2 images were scored for severity of white matter disease. Independent sample t-tests were used to determine differences by race in education, age, income, aphasia severity, white matter disease, and lesion size. A linear regression model was used to explore factors that predicted aphasia severity on the WAB-R. Result Level of education and estimated income differed by race in our sample. For predictors of aphasia severity, the regression model revealed a significant effect of lesion size on WAB Aphasia Quotient and an interaction of race x lesion size, such that Black and White participants with small lesions had similar WAB scores, but in individuals with larger lesions, Black participants had lower WAB scores than White participants. Conclusion We suggest two explanations for the difference between Black and White SWA in the relationship between lesion size and aphasia severity. First, the impact of disparities in access to rehabilitation after stroke may be more evident when a stroke is larger and causes significant aphasia. Additionally, an assessment bias in aphasia outcome measures may be more evident with increasing severity of aphasia. Future studies should further discern the drivers of observed disparities in aphasia outcomes in order to identify opportunities to improve equity in aphasia care.

Language function in the brain, once thought to be highly localized, is now appreciated as relying on a connected but distributed network. The semantic system is of particular interest in the language domain because of its hypothesized integration of information across multiple cortical regions. Previous work in healthy individuals has focused on group-level functional connectivity (FC) analyses of the semantic system, which may obscure interindividual differences driving variance in performance. These studies also overlook the contributions of white matter networks to semantic function. Here, we identified semantic network nodes at the individual level with a semantic decision fMRI task in 53 typically aging adults, characterized network organization using structural connectivity (SC), and quantified the segregation and integration of the network using FC. Hub regions were identified in left inferior frontal gyrus. The individualized semantic network was composed of three interacting modules: (1) default-mode module characterized by bilateral medial prefrontal and posterior cingulate regions and also including right-hemisphere homotopes of language regions; (2) left frontal module extending dorsally from inferior frontal gyrus to pre-motor area; and (3) left temporoparietal module extending from temporal pole to inferior parietal lobule. FC within Module3 and integration of the entire network related to a semantic verbal fluency task, but not a matched phonological task. These results support and extend the tri-network semantic model (Xu in Front Psychol 8: 1538 1538, 2017) and the controlled semantic cognition model (Chiou in Cortex 103: 100 116, 2018) of semantic function.

The severity of post-stroke aphasia is related to damage to white matter connections. However, neural signaling can route not only through direct connections, but also along multi-step network paths. When brain networks are damaged by stroke, paths can bypass around the damage to restore communication. The shortest network paths between regions could be the most efficient routes for mediating bypasses. We examined how shortest-path bypasses after left hemisphere strokes were related to language performance. Regions within and outside of the canonical language network could be important in aphasia recovery. Therefore, we innovated methods to measure the influence of bypasses in the whole brain. Distinguishing bypasses from all residual shortest paths is difficult without pre-stroke imaging. We identified bypasses by finding shortest paths in subjects with stroke that were longer than the most reliably observed connections in age-matched control networks. We tested whether features of those bypasses predicted scores in four orthogonal dimensions of language performance derived from a principal components analysis of a battery of language tasks. The features were the length of each bypass in steps, and how many bypasses overlapped on each individual direct connection. We related these bypass features to language factors using support vector regression, a technique that extracts robust relationships in high-dimensional data analysis. The support vector regression parameters were tuned using grid-search cross-validation. We discovered that the length of bypasses reliably predicted variance in lexical production (R² = .576) and auditory comprehension scores (R² = .164). Bypass overlaps reliably predicted variance in Lexical Production scores (R² = .247). The predictive elongation features revealed that bypass efficiency along the dorsal stream and ventral stream were most related to Lexical Production and Auditory Comprehension, respectively. Among the predictive bypass overlaps, increased bypass routing through the right hemisphere putamen was negatively related to lexical production ability.

The success of a lesion-symptom mapping (LSM) study in answering a specific research question critically depends on how behavioral variables are selected and handled in the analysis. In this chapter, we discuss the theoretical and practical considerations regarding the use of behavioral measures in LSM studies. We begin by addressing theoretical considerations that impact both the choice of behavioral measures and the design of LSM studies. This includes determining whether the main aim of the study is to address a basic science or a clinical research question, considering what type of brain-behavior relationship is hypothesized, and adopting a testing theory framework for the study. We then address practical aspects of selecting behavioral measures, including considering the psychometric properties of measures, deciding whether to use published tests or to develop new measures, deciding whether to categorize participants or to treat scores as continuous measures, examining the distribution of performance on the tests, and considering how to develop a battery of tests to address the research questions. We then discuss analysis decisions that impact the behavioral and anatomical specificity of LSM results, including methods to address lesion volume confounds and methods to compare multiple behaviors. We end by discussing extensions of LSM that examine the relationship between lesions and non-behavioral variables. We hope this chapter provides guidance to investigators on major issues that should be considered when selecting behavioral measures and developing LSM analysis approaches. Attention to these issues will improve the validity and reliability of LSM results.Key wordsNeuropsychologyBehavioral neurologyLesion studiesPsychometrics Neuroimaging methods