Adding temporal dynamics to models of impaired language production
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1
TEMPLE UNIVERSITY, Communication Sciences and Disorders, United States
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2
University of Illinois, Department of Psychology, United States
Spreading activation models of language production typically attribute aphasia to either a transmission failure (weak connection weights) or a failure in maintaining activation of a unit (too-fast activation decay)1. These models are better at identifying the “where” of a deficit (e.g., lexical-semantic), than distinguishing “mechanisms” of activation transmission vs. maintenance. In Study 1, we introduce a temporal component (response delay) to word retrieval tasks and show that for individuals with aphasia, response accuracy increases for some and decreases for others after a time delay. In Study 2, we present a version of the interactive activation model of naming2 that includes time as a property and offers a preliminary hypothesis about why some people with aphasia benefit from extra time to respond and others are harmed by it.
Study 1. Differential effects of response delay on picture naming and word repetition.
Participants: n=35, chronic aphasia; n=10 age-, education-matched controls.
Picture naming. 30 object pictures presented visually. Cue to name given at a1-sec or 5-sec interval.
Word repetition. 15 concrete words presented auditorily. Cue to repeat given at a1-sec or 5-sec interval.
Results. Controls: highly accurate in both tasks 98-99%, regardless of delay.
Participants-with-aphasia: Accuracy increased or decreased after a 5-sec response delay. To determine whether these changes reflected a true difference in performance we estimated the critical difference in proportion correct between the 1-sec and 5-sec conditions as twice the standard error of the difference of two proportions. Obtained differences that exceed this value (regardless of direction of change) indicate that this difference is likely nonzero. If there were no true differences, one would expect approximately 5% of the participant-test combinations to exceed this criterion.
Proportions of participants whose changes in accuracy exceeded the 5% criterion: naming, 16/35 (46%); repetition, 7/35 (0%).
Example for naming: While G24’s accuracy decreased by 30%. (6333%) after a response delay, KR33’s improved by 30% (6090%).
These results support the hypothesis that for some individuals with aphasia, language performance is affected positively or negatively by additional time to process a response.
Study 2. “Slow” version of the naming model that enables tracking of activation levels over many time steps (e.g. 25) and includes decay rate (d) as a lesionable parameter3,4 .
We simulated normal performance (97% correct) after 8-20 time steps and better and worse performance as a function of response delay (Table 1).The model shows that the pattern of errors being less likely with more time to respond is simulated by lower connection weights (reducing semantic weight and phonological weight from .0003 to .0001). At no delay (time step = 8), performance is poor (47% correct) but improves when more time passes (e.g. 65% at time step 25). The opposite occurs when the lesion leads to an increase in the decay rate. Performance is better with no delay (94%) than at the delay (44% at step 25).
In this way, the new model explains the patient differences; in one case there is weakness in information transmission, in the other, there is a weakness in maintenance.
Acknowledgements
Research reported here was supported by the National Institute on Deafness and Other Communication Disorders of the National Institutes of Health under award numbers R01DC01924 and R01DC013196. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
References
1. Dell, G.S., Schwartz, M.F., Martin, N., Saffran, E.M. and Gagnon, D.A. (1997). Lexical access in aphasic and non-aphasic speakers. Psychological Review, 104 (4), 801-838.
2. Foygel, D., & Dell, G.S. (2000). Models of impaired lexical access in speech production. Journal of Memory and Language, 43, 182-216.
3. Martin, N., Dell, G.S., Saffran, E.M., & Schwartz, M.F. (1994). Origins of paraphasias in deep dysphasia: Testing the consequences of a decay impairment in an interactive spreading activation model of language. Brain and Language, 47, 609-660.
4. Martin, N. Saffran, E.M. & Dell, G.S. (1996). Recovery in deep dysphasia: Evidence for a relation between auditory-verbal STM and lexical errors in repetition. Brain and Language, 52, 83-113.
Keywords:
computer modeling,
Word Processing,
temporal processing,
Aphasia,
Anomia
Conference:
Academy of Aphasia 55th Annual Meeting , Baltimore, United States, 5 Nov - 7 Nov, 2017.
Presentation Type:
poster or oral
Topic:
General Submission
Citation:
Martin
N and
Dell
G
(2019). Adding temporal dynamics to models of impaired language production.
Conference Abstract:
Academy of Aphasia 55th Annual Meeting .
doi: 10.3389/conf.fnhum.2017.223.00110
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Received:
02 May 2017;
Published Online:
25 Jan 2019.
*
Correspondence:
Dr. Nadine Martin, TEMPLE UNIVERSITY, Communication Sciences and Disorders, PHILADELPHIA, PENNSYLVANIA, 19122, United States, nmartin@temple.edu