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  Classification of types of stuttering symptoms based on brain activity

Jiang, J., Lu, C., Peng, D., Zhu, C., & Howell, P. (2012). Classification of types of stuttering symptoms based on brain activity. PLoS One, 7(6): e39747. doi:10.1371/journal.pone.0039747.

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Classification of types of stuttering symptoms based on brain activity.pdf (Verlagsversion), 413KB
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Classification of types of stuttering symptoms based on brain activity.pdf (Verlagsversion), 413KB
Name:
Classification of types of stuttering symptoms based on brain activity.pdf
Beschreibung:
-
OA-Status:
Sichtbarkeit:
Öffentlich
MIME-Typ / Prüfsumme:
application/pdf / [MD5]
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
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 Urheber:
Jiang, Jing1, Autor           
Lu, Chunming1, Autor
Peng, Danling1, Autor
Zhu, Chaozhe1, Autor
Howell, Peter2, Autor
Affiliations:
1State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, China, ou_persistent22              
2Department of Psychology and Language Sciences, University College London, United Kingdom, ou_persistent22              

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 Zusammenfassung: 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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Sprache(n): eng - English
 Datum: 2012-06-25
 Publikationsstatus: Online veröffentlicht
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 Identifikatoren: DOI: 10.1371/journal.pone.0039747
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Titel: PLoS One
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: San Francisco, CA : Public Library of Science
Seiten: - Band / Heft: 7 (6) Artikelnummer: e39747 Start- / Endseite: - Identifikator: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850