Cognitive deficits revealed with the Rus-BCoS and their relationships with language comprehension in fluent and nonfluent aphasia

Abstract

We know that fluent and nonfluent PWA present with different language profiles. However, the question of whether fluent and nonfluent PWA present with similar cognitive deficits and whether such deficits contribute to language comprehension, is open. Although we know that all PWA have diminished verbal cognitive control, nonfluent PWA display greater vulnerability in domain-general cognitive control compared to fluent PWA and nonfluent PWA rely on domain-general relational reasoning during language comprehension (Kuzmina & Weekes, 2016). Study aims and hypotheses: Our first objective was to examine cognitive deficits using the Russian version of the Birmingham Cognitive Screen (Rus-BCoS; Kuzmina et al., 2017) in fluent and nonfluent aphasia groups. Given heterogeneous patterns of cognitive deficits in PWA (Murray, 2012; Seniów et al., 2009), we did not make predictions about differences between groups. The second objective was to correlate relationships between cognitive processing and language comprehension in both fluent and nonfluent PWA. Assuming that PWA compensate linguistic disturbances via intact cognitive mechanisms (Luria, 1980) and that fluent and nonfluent PWA differ in their primary linguistic disturbances (Ardila 2010; Jakobson, 1964; Luria, 1973), we expected, firstly, that all PWA would recruit extra-linguistic cognitive processes to compensate for impaired language comprehension and, secondly, that fluent and nonfluent PWA would display different patterns of compensation. Method: 17 participants with sensory or acoustic‑amnestic aphasia defined according to the Lurian nosology comprised the fluent group and 17 participants diagnosed with efferent-motor aphasia or complex motor aphasia with a prevalence of efferent-motor aphasic symptoms comprised the nonfluent group. All participants were tested with subtests from the Rus-BCoS and the Quantitative Assessment of Speech in Aphasia (QASA; Tsvetkova, Akhutina, & Pylaeva, 1981). To compare cognitive deficits, participants’ averaged rank scores from Rus‑BCoS subtests were entered into a principal component analysis with varimax rotation. To compare scores for the extracted cognitive factors, Student’s t-test was used. Next, scores on each factor were correlated with language comprehension ability. Results: The loadings of rotated factors on each Rus-BCoS subtest enabled interpretation of cognitive processes underlying each factor (see Table 1). The nonfluent group had significantly lower scores for Factor 2 “Domain-general cognitive control”, t(32) = -2.52, p = .02. There were no significant differences between the groups on other factors. Domain-general memory was significantly correlated to language comprehension for fluent PWA, r(16) = .78, p < .001, but not nonfluent PWA, r(16) = .33, p = .20. Domain-general cognitive control was significantly correlated with language comprehension for nonfluent PWA, r(16) = .50, p = .04, but not for fluent PWA, r(16) = -.18, p = .50. There were no significant correlations between other factors and language comprehension scores for either group. Conclusions: The nonfluent group seemed to show more impairment on average on tasks requiring cognitive control. The results suggest that better attention allocation allows nonfluent PWA compensate for their impaired linguistic sequencing and, consequently, achieve better comprehension. On the other hand, better memory allows fluent PWA compensate for their specific impairment in the selection of linguistic elements during language comprehension.