Assessing lexical-semantic naming deficits using an automated machine learning approach

After left hemisphere stroke, 20-50% of people experience language deficits, including difficulties in naming. Naming errors that are semantically related to the intended target (e.g., producing “violin” for picture HARP) indicate a potential impairment in accessing knowledge of word forms and their meanings. Understanding the cause of naming impairments is crucial to better modeling of language production as well as for tailoring individualized rehabilitation. However, evaluation of naming errors is typically by subjective and laborious dichotomous classification. As a result, these evaluations do not capture the degree of semantic similarity and are susceptible to lower inter-rater reliability because of subjectivity. We investigated whether a computational linguistic measure, word2vec (Mikolov, Chen, Corrado, & Dean, 2013) addressed these limitations by evaluating errors during object naming in a group of patients during the acute stage of a left-hemisphere stroke (N=105). Pearson correlations demonstrated excellent convergent validity of word2vec’s semantically related estimates of naming errors and independent tests of access to lexical-semantic knowledge (p’s < .0001). Further, multiple regression analysis showed word2vec’s semantically related estimates were significantly better than human error classification at predicting performance on tests of lexical-semantic knowledge (p < .001). Useful to both theorists and clinicians, word2vec provides an automated, continuous, and objective psychometric measure of access to lexical-semantic knowledge during naming.

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. Poor semantic cognition was associated with small left-lateralized structurally disconnected clusters, including in the left posterior temporal cortex. 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.

A Novel Method to Assess Motor Cortex Connectivity and Event Related Desynchronization Based on Mass Models

Knowledge of motor cortex connectivity is of great value in cognitive neuroscience, in order to provide a better understanding of motor organization and its alterations in pathological conditions. Traditional methods provide connectivity estimations which may vary depending on the task. This work aims to propose a new method for motor connectivity assessment based on the hypothesis of a task-independent connectivity network, assuming nonlinear behavior. The model considers six cortical regions of interest (ROIs) involved in hand movement. The dynamics of each region is simulated using a neural mass model, which reproduces the oscillatory activity through the interaction among four neural populations. Parameters of the model have been assigned to simulate both power spectral densities and coherences of a patient with left-hemisphere stroke during resting condition, movement of the affected, and movement of the unaffected hand. The presented model can simulate the three conditions using a single set of connectivity parameters, assuming that only inputs to the ROIs change from one condition to the other. The proposed procedure represents an innovative method to assess a brain circuit, which does not rely on a task-dependent connectivity network and allows brain rhythms and desynchronization to be assessed on a quantitative basis.

Simultaneous Normalization and Compensatory Changes in Right Hemisphere Connectivity during Aphasia Therapy

Changes in brain connectivity during language therapy were examined among participants with aphasia (PWA), aiming to shed light on neural reorganization in the language network. Four PWA with anomia following left hemisphere stroke and eight healthy controls (HC) participated in the study. Two fMRI scans were administered to all participants with a 3.5-month interval. The fMRI scans included phonological and semantic tasks, each consisting of linguistic and perceptual matching conditions. Between the two fMRI scans, PWA underwent Phonological Components Analysis treatment. Changes in effective connectivity during the treatment were examined within right hemisphere (RH) architecture. The results illustrate that following the treatment, the averaged connectivity of PWA across all perceptual and linguistic conditions in both tasks increased resemblance to HC, reflecting the normalization of neural processes associated with silent object name retrieval. In contrast, connections that were specifically enhanced by the phonological condition in PWA decreased in their resemblance to HC, reflecting emerging compensatory reorganization in RH connectivity to support phonological processing. These findings suggest that both normalization and compensation play a role in neural language reorganization at the chronic stage, occurring simultaneously in the same brain.

Right-hemisphere compensation during word production: A single case of left-hemisphere young stroke

Our understanding of post-stroke language recovery and underlying neuroplasticity is largely based on older age groups, who have increasing brain pathology and potentially more bilateral language functioning. We present the case of A., a 23 y.o. woman with chronic aphasia from a left-hemisphere stroke. Deterministic tractography indicated that A.’s language-relevant white matter structures were severely damaged. Using magnetoencephalography (MEG), we explored A.’s conceptual preparation and subsequent word planning abilities. Context-driven and Bare picture-naming tasks revealed substantial naming deficits, manifesting as word-finding difficulties and semantic paraphasias about half of the time. Naming was however facilitated by semantically constraining lead-in sentences. Altogether, this pattern indicates intact conceptual preparation but disrupted lexical and phonological retrieval abilities. MEG revealed that A.’s naming-related neural responses differed from that of a matched control. Source localisation showed active but differential recruitment of right-hemisphere structures (300-400 ms post-picture onset) during both correct naming (right temporo-parietal regions) and anomic (right inferior frontal gyrus) attempts. We consider that, despite A.’s young age, the presumed strong degree of language lateralisation and extensive structural damage limited her recovery. Although A.’s right hemisphere responded in a timely manner during word planning, its lexical and phonological retrieval abilities remained modest.

Distinguishing Semantic Control and Phonological Control And Their Role in Aphasic Deficits: A Task Switching Investigation

People use cognitive control across many contexts in daily life, yet it remains unclear how cognitive control is used in contexts involving language. Distinguishing language-specific cognitive control components may be critical to understanding aphasia, which can co-occur with cognitive control deficits. For example, deficits in control of semantic representations (i.e., semantic control), are thought to contribute to semantic deficits in aphasia. Conversely, little is known about control of phonological representations (i.e., phonological control) in aphasia. We developed a switching task to investigate semantic and phonological control in 32 left hemisphere stroke survivors with aphasia and 37 matched controls. We found that phonological and semantic control were related, but dissociate in the presence of switching demands. People with aphasia exhibited group-wise impairment at phonological control, although individual impairments were subtle. Several individuals with aphasia exhibited frank semantic control impairments, and these individuals had relative deficits on other semantic tasks. The present findings distinguish semantic control from phonological control, and confirm that semantic control impairments contribute to semantic deficits in aphasia.

Distinct Contributions of Working Memory and Attentional Control to Sentence Comprehension in Noise in Persons With Stroke

Purpose Sentence comprehension deficits are common following a left hemisphere stroke and have primarily been investigated under optimal listening conditions. However, ample work in neurotypical controls indicates that background noise affects sentence comprehension and the cognitive resources it engages. The purpose of this study was to examine how background noise affects sentence comprehension poststroke using both energetic and informational maskers. We further sought to identify whether sentence comprehension in noise abilities are related to poststroke cognitive abilities, specifically working memory and/or attentional control. Method Twenty persons with chronic left hemisphere stroke completed a sentence–picture matching task where they listened to sentences presented in three types of maskers: multispeakers, broadband noise, and silence (control condition). Working memory, attentional control, and hearing thresholds were also assessed. Results A repeated-measures analysis of variance identified participants to have the greatest difficulty with the multispeakers condition, followed by broadband noise and then silence. Regression analyses, after controlling for age and hearing ability, identified working memory as a significant predictor of listening engagement (i.e., mean reaction time) in broadband noise and multispeakers and attentional control as a significant predictor of informational masking effects (computed as a reaction time difference score where broadband noise is subtracted from multispeakers). Conclusions The results from this study indicate that background noise impacts sentence comprehension abilities poststroke and that these difficulties may arise due to deficits in the cognitive resources supporting sentence comprehension and not other factors such as age or hearing. These findings also highlight a relationship between working memory abilities and sentence comprehension in background noise. We further suggest that attentional control abilities contribute to sentence comprehension by supporting the additional demands associated with informational masking. Supplemental Material https://doi.org/10.23641/asha.14984511