Storage Costs and Heuristics Interact to Produce Patterns of Aphasic Sentence Comprehension Performance

摘要

>Background: Despite general agreement that aphasic individuals exhibit difficulty understanding complex sentences, the nature of sentence complexity itself is unresolved. In addition, aphasic individuals appear to make use of heuristic strategies for understanding sentences. This research is a comparison of predictions derived from two approaches to the quantification of sentence complexity, one based on the hierarchical structure of sentences, and the other based on dependency locality theory (DLT). Complexity metrics derived from these theories are evaluated under various assumptions of heuristic use. >Method: A set of complexity metrics was derived from each general theory of sentence complexity and paired with assumptions of heuristic use. Probability spaces were generated that summarized the possible patterns of performance across 16 different sentence structures. The maximum likelihood of comprehension scores of 42 aphasic individuals was then computed for each probability space and the expected scores from the best-fitting points in the space were recorded for comparison to the actual scores. Predictions were then compared using measures of fit quality derived from linear mixed effects models. >Results: All three of the metrics that provide the most consistently accurate predictions of patient scores rely on storage costs based on the DLT. Patients appear to employ an Agent–Theme heuristic, but vary in their tendency to accept heuristically generated interpretations. Furthermore, the ability to apply the heuristic may be degraded in proportion to aphasia severity. >Conclusion: DLT-derived storage costs provide the best prediction of sentence comprehension patterns in aphasia. Because these costs are estimated by counting incomplete syntactic dependencies at each point in a sentence, this finding suggests that aphasia is associated with reduced availability of cognitive resources for maintaining these dependencies.