Quantifier processing and semantic flexibility in patients with aphasia

Abstract

Processing of quantifiers such as "many" and "few" relies on number knowledge, linguistic abilities, and working memory. Negative quantifiers (e.g., "few," "less than half") induce higher processing costs than their positive counterparts. Furthermore, the meaning of some quantifiers is flexible and thus adaptable. Importantly, in neurotypical individuals, changing the meaning of one quantifier also leads to a generalized change in meaning for its polar opposite (e.g., the change of the meaning of "many" leads to the change of that of "few"). Here, we extended this research to patients with fluent and non-fluent aphasia after stroke. In two experiments, participants heard sentences of the type "Many/few of the circles are yellow/blue," each followed by a picture with different quantities of blue and yellow circles. The participants judged whether the sentence adequately described the picture. Each experiment consisted of three blocks: a baseline block to assess the participants' criteria for both quantifiers, a training block to shift the criteria for "many," and a test block, identical to the baseline to capture any changes in quantifier semantics. In Experiment 1, the change of the meaning of "many" was induced by using adaptation to small numbers (20-50%) of circles of the named color. In Experiment 2, explicit feedback was given in the training block after each response to rate proportions of 40% (or higher) as "many," whereas 40% is normally rather rated as "few." The objective was to determine whether people with fluent or non-fluent aphasia were able to process quantifiers appropriately and whether generalized semantic flexibility was present after brain damage. Sixteen out of 21 patients were able to perform the task. People with fluent aphasia showed the expected polarity effect in the reaction times and shifted their criteria for "many" with generalization to the untrained quantifier "few." This effect, however, was only obtained after explicit feedback (Experiment 2) but not by mere adaptation (Experiment 1). In contrast, people with non-fluent aphasia did not change the quantifier semantics in either experiment. This study contributes to gaining new insights into quantifier processing and semantic flexibility in people with aphasia and general underlying processing mechanisms.

Keywords: adaptation; aphasia; feedback; flexibility; learning; quantifier; semantics.

Figure 1

Schematic illustration of practice items in both test runs. First test run with a nonverbal version of the task (Left). PWA were presented with a printed version of a picture with blue and yellow circles with a mathematical expression underneath indicating that one color outweighs the other. The patients were instructed to evaluate whether the expression matched the picture or not. In preparation for the computer version of the experiment a keyboard was also depicted. In the second test run (Right) a sentence containing a quantifier was spoken by the examiner. Following this, a picture was presented in printed version. The patient then had to decide whether the sentence adequately described the picture.

Figure 2

Exemplary trials of blocks 1 and 3 (A) and of block 2 (B) in both experiments based on Heim et al. (2012, .

Figure 3

Average reaction times of all participants in Experiment 1 (adaptation) for both quantifiers (“many”, “few”) related to each proportion of circles in the target color (in %), divided in groups: all participants, PWFA and PWNFA. Reaction times are presented for blocks 1 and 3, before and after adaptation to visualize changes in the course.

Figure 4

Average acceptability of quantifiers in Experiment 1 (adaptation), divided in groups: all participants, PWFA and PWNFA. (A) Illustration of acceptability of quantifiers (“many” = black lines, “few” = gray lines) at each proportion of circles in the target color (in %) in block 1 (dashed lines) and block 3 (solid lines). (B) Average acceptability judgments for the critical proportion of circles in the target color (40%), sorted by quantifier (“many” = black bars, “few” = gray bars) and block (block 1 = dashed bars, block 3 = solid bars).

Figure 5

Average reaction times of all participants in Experiment 2 (feedback) for both quantifiers (“many”, “few”) related to each proportion of circles in the target color (in %), divided in groups: all participants, PWFA and PWNFA. Reaction times are presented for blocks 1 and 3, before and after feedback to visualize changes in the course.

Figure 6

Average acceptability of quantifiers in Experiment 2 (feedback), divided in groups: all participants, PWFA and PWNFA. (A) Illustration of acceptability of quantifiers (“many” = black lines, “few” = gray lines) at each proportion of circles in the target color (in %) in block 1 (dashed lines) and block 3 (solid lines). (B) Average acceptability judgments for the critical proportion of circles in the target color (40%), sorted by quantifier (“many” = black bars, “few” = gray bars) and block (block 1 = dashed bars, block 3 = solid bars).

Figure 7

Performance of participants and non-participants in the token test and language comprehension test of the AAT in comparison. (A) Demonstration of the T-value achieved by each patient in both tests, plotted separately for non-participants (dashed columns) and participants (solid columns). (B) Average T-values achieved by non-participants and participants in both tests. With regard to the language comprehension test, in one case no test value was available, which is why only 20 instead of 21 test subjects are listed on the x-axis. The data are reported in ascending order of values. The participant numbers in panels (A,B) only indicate order of values and do not identify individual participants.