Assessment of verb and sentence processing deficits in stroke-induced aphasia: the Italian version of the Northwestern Assessment of Verbs and Sentences (NAVS-I)

Abstract

Background: The Northwestern Assessment of Verbs and Sentences (NAVS) assesses verb and sentence production and comprehension in aphasia. Results from the original English version and from its adaptation to German have shown that the NAVS is able to capture effects of verb-argument structure (VAS) complexity (i.e., lower accuracy for two- and three-argument vs. one-argument verbs) and syntactic complexity (i.e., lower accuracy for non-canonical vs. canonical sentences) in both agrammatic participants and individuals with mild (residual) forms of aphasia. The NAVS has been recently adapted to Italian (NAVS-I) and tested on a group of healthy participants, with results showing longer reaction times to complex vs. simple verbs and sentences.

Aims: The present study aimed to test the ability of NAVS-I to i) capture verb/sentence production and comprehension deficits in Italian-speaking individuals with agrammatism or with fluent aphasia, and ii) differentiate individuals with aphasia from healthy age-matched participants, with the overall goal to validate its use in clinical practice.

Methods & procedures: Forty-four healthy participants and 28 individuals with aphasia (10 with agrammatic speech production) were administered the NAVS-I, which includes tasks assessing production and comprehension of verbs requiring one, two or three arguments, as well as production and comprehension of canonical and non-canonical sentences.

Outcomes & results: On the Verb Naming Task (VNT), better production of one- (vs. two- and three-) argument verbs was found in the agrammatic group, whereas, verb production in the fluent group was solely predicted by word length and imageability. No effects of argument optionality (i.e., greater difficulty for optionally transitive verbs than for 1-argument verbs) were found. Sentence-level tasks found no differences between the agrammatic and the fluent group in production or comprehension of both canonical and non-canonical sentences; rather, sentence comprehension accuracy was predicted by demographic variables and by aphasia severity. At the individual level, performance on the NAVS-I was significantly different from that of healthy speakers in 26/28 patients.

Conclusions: Data show that the NAVS-I is able to capture effects of argument structure complexity in verb production, and effects of syntactic complexity in sentence production and comprehension. In addition, our results point to verb production as the task with greater capability to differentiate agrammatism from other (fluent) forms of aphasia. The study provides support for the use of the NAVS-I in the diagnosis of aphasia, as it is able to detect language deficits at the individual level, even in participants with mild (residual) forms of aphasia.

Keywords: Agrammatism; Assessment; Non-canonical word order; Sentence processing; Verb argument structure.

Figure 1.

Example items for the target verb dare (to give), for each of the first three subtests: Verb Naming Task (VNT), Verb Comprehension Task (VCT), and Argument Structure Production Task (ASPT).

Figure 2.

Example items for the last two subtests: Sentence Production Priming Task (SPPT) and Sentence Comprehension Task (SCT).

Figure 3.

Proportion of correct responses for one, two, and three-argument verbs, obtained from each participant group on the VNT (a), VCT (b), or ASPT (c).

Figure 4.

Interaction between sentence length and verb frequency on the Argument Structure Production Task (ASPT). The graph shows the predicted accuracy (ACC) values (expressed as probabilities) for short (red) and long (blue) sentences, based on verb frequency (mean-centered).

Figure 5.

Proportion of correct responses on the SPPT, reported separately for canonical and noncanonical sentences (a) or by sentence type (b), for each of the participant groups. C = canonical; NC = non-canonical; SC = subject-cleft sentences; OC = object-cleft sentences; SR = subject-relative sentences; OR = object-relative sentences.

Figure 6.

Proportion of correct responses on the SCT, reported separately for canonical and noncanonical sentences (a) or by sentence type (b), for each of the participant groups. C = canonical; NC = noncanonical; SC = subject-cleft sentences; OC = object-cleft sentences; SR = subject-relative sentences; OR = object-relative sentences.

Figure 7.

Interaction between canonicity and age on the SCT. The graph shows the proportion of correct responses to canonical and non-canonical sentences, separately for younger and older participants with aphasia, based on a median split. C = canonical; NC = non-canonical.

Figure 8.

Interactions between sentence type and aphasia severity (a), sentence type and months post-onset (b) and sentence type and age (c). The graphs show the proportion of correct responses to each sentence type in groups of individuals with aphasia classified as having milder or more severe aphasia (a), as being in earlier or later stages of recovery (b), and as being younger or older (c), following median split.