What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach
Cognitive network science is an emerging approach that uses the mathematical tools of network science to map the relationships among representations stored in memory to examine how that structure might influence processing. In the present study, we used computer simulations to compare the ability of...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
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| Series: | Brain Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3425/11/12/1628 |
| _version_ | 1797506486380789760 |
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| author | Michael S. Vitevitch Gavin J. D. Mullin |
| author_facet | Michael S. Vitevitch Gavin J. D. Mullin |
| author_sort | Michael S. Vitevitch |
| collection | DOAJ |
| description | Cognitive network science is an emerging approach that uses the mathematical tools of network science to map the relationships among representations stored in memory to examine how that structure might influence processing. In the present study, we used computer simulations to compare the ability of a well-known model of spoken word recognition, TRACE, to the ability of a cognitive network model with a spreading activation-like process to account for the findings from several previously published behavioral studies of language processing. In all four simulations, the TRACE model failed to retrieve a sufficient number of words to assess if it could replicate the behavioral findings. The cognitive network model successfully replicated the behavioral findings in Simulations 1 and 2. However, in Simulation 3a, the cognitive network did not replicate the behavioral findings, perhaps because an additional mechanism was not implemented in the model. However, in Simulation 3b, when the decay parameter in <i>spreadr</i> was manipulated to model this mechanism the cognitive network model successfully replicated the behavioral findings. The results suggest that models of cognition need to take into account the multi-scale structure that exists among representations in memory, and how that structure can influence processing. |
| first_indexed | 2024-03-10T04:33:20Z |
| format | Article |
| id | doaj.art-fe053fec80ea425688694b369223ee84 |
| institution | Directory Open Access Journal |
| issn | 2076-3425 |
| language | English |
| last_indexed | 2024-03-10T04:33:20Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj.art-fe053fec80ea425688694b369223ee842023-11-23T04:02:18ZengMDPI AGBrain Sciences2076-34252021-12-011112162810.3390/brainsci11121628What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science ApproachMichael S. Vitevitch0Gavin J. D. Mullin1Department of Psychology, University of Kansas, Lawrence, KS 66045, USADepartment of Psychology, University of Kansas, Lawrence, KS 66045, USACognitive network science is an emerging approach that uses the mathematical tools of network science to map the relationships among representations stored in memory to examine how that structure might influence processing. In the present study, we used computer simulations to compare the ability of a well-known model of spoken word recognition, TRACE, to the ability of a cognitive network model with a spreading activation-like process to account for the findings from several previously published behavioral studies of language processing. In all four simulations, the TRACE model failed to retrieve a sufficient number of words to assess if it could replicate the behavioral findings. The cognitive network model successfully replicated the behavioral findings in Simulations 1 and 2. However, in Simulation 3a, the cognitive network did not replicate the behavioral findings, perhaps because an additional mechanism was not implemented in the model. However, in Simulation 3b, when the decay parameter in <i>spreadr</i> was manipulated to model this mechanism the cognitive network model successfully replicated the behavioral findings. The results suggest that models of cognition need to take into account the multi-scale structure that exists among representations in memory, and how that structure can influence processing.https://www.mdpi.com/2076-3425/11/12/1628phonologynetwork scienceone-phoneme metricphonological neighborsspoken word recognitioncomputer simulation |
| spellingShingle | Michael S. Vitevitch Gavin J. D. Mullin What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach Brain Sciences phonology network science one-phoneme metric phonological neighbors spoken word recognition computer simulation |
| title | What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach |
| title_full | What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach |
| title_fullStr | What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach |
| title_full_unstemmed | What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach |
| title_short | What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach |
| title_sort | what do cognitive networks do simulations of spoken word recognition using the cognitive network science approach |
| topic | phonology network science one-phoneme metric phonological neighbors spoken word recognition computer simulation |
| url | https://www.mdpi.com/2076-3425/11/12/1628 |
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