Classification of types of stuttering symptoms based on brain activity.
Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is w...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22761887/pdf/?tool=EBI |
| _version_ | 1818700915121586176 |
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| author | Jing Jiang Chunming Lu Danling Peng Chaozhe Zhu Peter Howell |
| author_facet | Jing Jiang Chunming Lu Danling Peng Chaozhe Zhu Peter Howell |
| author_sort | Jing Jiang |
| collection | DOAJ |
| description | Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type. |
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| format | Article |
| id | doaj.art-1d7fc459014549eca0bac5d180f1b528 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-17T15:12:31Z |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
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| series | PLoS ONE |
| spelling | doaj.art-1d7fc459014549eca0bac5d180f1b5282022-12-21T21:43:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0176e3974710.1371/journal.pone.0039747Classification of types of stuttering symptoms based on brain activity.Jing JiangChunming LuDanling PengChaozhe ZhuPeter HowellAmong the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22761887/pdf/?tool=EBI |
| spellingShingle | Jing Jiang Chunming Lu Danling Peng Chaozhe Zhu Peter Howell Classification of types of stuttering symptoms based on brain activity. PLoS ONE |
| title | Classification of types of stuttering symptoms based on brain activity. |
| title_full | Classification of types of stuttering symptoms based on brain activity. |
| title_fullStr | Classification of types of stuttering symptoms based on brain activity. |
| title_full_unstemmed | Classification of types of stuttering symptoms based on brain activity. |
| title_short | Classification of types of stuttering symptoms based on brain activity. |
| title_sort | classification of types of stuttering symptoms based on brain activity |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22761887/pdf/?tool=EBI |
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