Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance
Background: Aphasic individuals exhibit greater difficulty understanding complex sentences, but there is little consensus regarding what makes one sentence more complicated than another. In addition, aphasic individuals might make use of heuristic strategies for understanding sentences. This researc...
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doaj-2f3ae15f35c4443695868427b921399d2020-11-24T21:44:26ZengFrontiers Media S.A.Frontiers in Psychology1664-10782012-05-01310.3389/fpsyg.2012.0013523427Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performanceDavid Glenn Clark0David Glenn Clark1Birmingham VA Medical CenterUniversity of Alabama at BirminghamBackground: Aphasic individuals exhibit greater difficulty understanding complex sentences, but there is little consensus regarding what makes one sentence more complicated than another. In addition, aphasic individuals might make use of heuristic strategies for understanding sentences. This research is a comparison of specific predictions derived from two approaches to the quantification of sentence complexity, one based on the hierarchical structure of sentences (trees), 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. Each metric was 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: The results suggest that storage (i.e., allocation of cognitive resources for anticipated syntactic constituents) is a key resource degraded by aphasia, but aphasic individuals may vary in their tendency to use or accept heuristically generated interpretations.http://journal.frontiersin.org/Journal/10.3389/fpsyg.2012.00135/fullAphasiasyntaxsemanticssentence comprehension |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
David Glenn Clark David Glenn Clark |
spellingShingle |
David Glenn Clark David Glenn Clark Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance Frontiers in Psychology Aphasia syntax semantics sentence comprehension |
author_facet |
David Glenn Clark David Glenn Clark |
author_sort |
David Glenn Clark |
title |
Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance |
title_short |
Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance |
title_full |
Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance |
title_fullStr |
Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance |
title_full_unstemmed |
Storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance |
title_sort |
storage costs and heuristics interact to produce patterns of aphasic sentence comprehension performance |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Psychology |
issn |
1664-1078 |
publishDate |
2012-05-01 |
description |
Background: Aphasic individuals exhibit greater difficulty understanding complex sentences, but there is little consensus regarding what makes one sentence more complicated than another. In addition, aphasic individuals might make use of heuristic strategies for understanding sentences. This research is a comparison of specific predictions derived from two approaches to the quantification of sentence complexity, one based on the hierarchical structure of sentences (trees), 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. Each metric was 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: The results suggest that storage (i.e., allocation of cognitive resources for anticipated syntactic constituents) is a key resource degraded by aphasia, but aphasic individuals may vary in their tendency to use or accept heuristically generated interpretations. |
topic |
Aphasia syntax semantics sentence comprehension |
url |
http://journal.frontiersin.org/Journal/10.3389/fpsyg.2012.00135/full |
work_keys_str_mv |
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