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

Abstract

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.

Fig. 1. Lesion overlap map across 46 participants with post-stroke aphasia.

Colour scale illustrates the distribution of the lesions and represents the number of participants with a lesion at that location. The maximum number of participants who had a lesion in one voxel was 36 (MNI coordinate: -38, -9, 24; central opercular cortex).

Fig. 2. The quantity and diversity of nouns and verbs produced during discourse.

Bar graphs showing the group mean and standards errors (errors bars) of the quantity of nouns and verbs (turquoise bars) and the diversity of nouns and verbs (purple bars) produced during three different discourse genres among the: (A) neuro-typical adults and all persons with aphasia, and (B) the fluent and non-fluent aphasia sub-groups.

Fig. 3. Imageability distribution of the content words produced during different discourse genres.

The group mean of the number of words produced within each imageability band by: A) neuro-typical adult group, B) persons with aphasia group, C) persons with fluent aphasia sub-groups, and D) persons with non-fluent aphasia sub-group. Top row: nouns and verbs combined, middle row: nouns, bottom row: verbs. Error bars represent the standard error of the mean.

Fig. 4. Frequency distribution of the content words produced during different discourse genres.

The group mean of the number of words produced within each frequency band by: A) neuro-typical adult group, B) persons with aphasia group, C) persons with fluent aphasia sub-group, and D) persons with non-fluent aphasia sub-group. Top row: nouns and verbs combined, middle row: nouns, bottom row: verbs. Error bars represent the standard error of the mean.

Fig. 5. Contour maps of neuro-typical adults and persons with aphasia representing lexical-semantic landscapes.

Two-dimensional frequency × imageability landscapes representing the mean word count produced during storytelling narrative. T-tests were used to show differences between the two groups in the third column and significantly different parts of the spaces are shown in green (p ≤ 0.001).

Fig. 6. Contour maps for different aphasia sub-groups representing lexical-semantic landscapes.

Two-dimensional frequency × imageability landscapes showing the mean word count produced during storytelling narrative by: A) persons with fluent versus non-fluent aphasia, B) high versus low performers on semantic domain, and C) high versus low performers on phonological domain. T-tests were used to show differences between the two groups in the third column and significantly different parts of the spaces are shown in green (p ≤ 0.001).

Fig. 7. Neuroimaging results from different lesion-symptom mapping approaches showing the neural correlates associated with word retrieval during connected speech accounting for the lexical-semantic properties of the words.

Left panels: models controlled for demographic variables (months post stroke onset, age, and education); right panels: models also controlled for lesion volume. MNI coordinates of slices from left to right: Z = 11, Y = 1, X = -45. (A) VBCM indicating the neural correlates associated with verb retrieval (red) and noun retrieval (green) within the lexical-semantic landscape thresholded at p<0.005 voxel-wise and FWE cluster corrected at p<0.05. (B) SVR-LSM showing voxels with significant beta weights after 10000 permutations testing, p<0.005 voxel-wise and p<0.005 cluster-wise for the models without lesion volume correction; and p<0.005 voxel-wise for the models with lesion volume correction. (C) PRoNTo depicting the neural weights back-projected on to 3D brain for significant model of noun and verb retrieval within the lexical-semantic landscape (permutation p<0.05) on the whole brain space. (D) PRoNTo depicting the neural weights back-projected on to 3D brain for significant model of noun and verb retrieval within the lexical-semantic landscape (permutation p<0.05) restricted to lesion territory. PRoNTo results thresholded from -0.0001 to -0.01 (blue-green colours) and 0.0001 to 0.01 (red-yellow couloirs), and the negative weights are considered as stronger in this approach. A grey surface indicates that no significant results were found for the respective measure and methodological approach.