A neural theory of speech acquisition and production
This article describes a computational model, called DIVA, that provides a quantitative framework for understanding the roles of various brain regions involved in speech acquisition and production. An overview of the DIVA model is first provided, along with descriptions of the computations performed...
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| Vydáno v: | Journal of neurolinguistics Ročník 25; číslo 5; s. 408 - 422 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
England
Elsevier Ltd
01.09.2012
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| Témata: | |
| ISSN: | 0911-6044, 1873-8052 |
| On-line přístup: | Získat plný text |
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| Abstract | This article describes a computational model, called DIVA, that provides a quantitative framework for understanding the roles of various brain regions involved in speech acquisition and production. An overview of the DIVA model is first provided, along with descriptions of the computations performed in the different brain regions represented in the model. Particular focus is given to the model's speech sound map, which provides a link between the sensory representation of a speech sound and the motor program for that sound. Neurons in this map share with “mirror neurons” described in monkey ventral premotor cortex the key property of being active during both production and perception of specific motor actions. As the DIVA model is defined both computationally and anatomically, it is ideal for generating precise predictions concerning speech-related brain activation patterns observed during functional imaging experiments. The DIVA model thus provides a well-defined framework for guiding the interpretation of experimental results related to the putative human speech mirror system. |
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| AbstractList | This article describes a computational model, called DIVA, that provides a quantitative framework for understanding the roles of various brain regions involved in speech acquisition and production. An overview of the DIVA model is first provided, along with descriptions of the computations performed in the different brain regions represented in the model. Particular focus is given to the model's speech sound map, which provides a link between the sensory representation of a speech sound and the motor program for that sound. Neurons in this map share with “mirror neurons” described in monkey ventral premotor cortex the key property of being active during both production and perception of specific motor actions. As the DIVA model is defined both computationally and anatomically, it is ideal for generating precise predictions concerning speech-related brain activation patterns observed during functional imaging experiments. The DIVA model thus provides a well-defined framework for guiding the interpretation of experimental results related to the putative human speech mirror system. This article describes a computational model, called DIVA, that provides a quantitative framework for understanding the roles of various brain regions involved in speech acquisition and production. An overview of the DIVA model is first provided, along with descriptions of the computations performed in the different brain regions represented in the model. Particular focus is given to the model's speech sound map, which provides a link between the sensory representation of a speech sound and the motor program for that sound. Neurons in this map share with "mirror neurons" described in monkey ventral premotor cortex the key property of being active during both production and perception of specific motor actions. As the DIVA model is defined both computationally and anatomically, it is ideal for generating precise predictions concerning speech-related brain activation patterns observed during functional imaging experiments. The DIVA model thus provides a well-defined framework for guiding the interpretation of experimental results related to the putative human speech mirror system.This article describes a computational model, called DIVA, that provides a quantitative framework for understanding the roles of various brain regions involved in speech acquisition and production. An overview of the DIVA model is first provided, along with descriptions of the computations performed in the different brain regions represented in the model. Particular focus is given to the model's speech sound map, which provides a link between the sensory representation of a speech sound and the motor program for that sound. Neurons in this map share with "mirror neurons" described in monkey ventral premotor cortex the key property of being active during both production and perception of specific motor actions. As the DIVA model is defined both computationally and anatomically, it is ideal for generating precise predictions concerning speech-related brain activation patterns observed during functional imaging experiments. The DIVA model thus provides a well-defined framework for guiding the interpretation of experimental results related to the putative human speech mirror system. This article describes a computational model, called DIVA, that provides a quantitative framework for understanding the roles of various brain regions involved in speech acquisition and production. An overview of the DIVA model is first provided, along with descriptions of the computations performed in the different brain regions represented in the model. Particular focus is given to the model's speech sound map, which provides a link between the sensory representation of a speech sound and the motor program for that sound. Neurons in this map share with "mirror neurons" described in monkey ventral premotor cortex the key property of being active during both production and perception of specific motor actions. As the DIVA model is defined both computationally and anatomically, it is ideal for generating precise predictions concerning speech-related brain activation patterns observed during functional imaging experiments. The DIVA model thus provides a well-defined framework for guiding the interpretation of experimental results related to the putative human speech mirror system. [Copyright Elsevier Ltd.] |
| Author | Vladusich, Tony Guenther, Frank H. |
| AuthorAffiliation | 1 Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA, 02215 3 Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA 4 Center of Excellence for Learning in Education, Science and Technology, Boston University, 677 Beacon Street, Boston, MA, 02215 2 Division of Health Sciences and Technology, Harvard University - Massachusetts Institute of Technology, Cambridge, MA 02139, USA |
| AuthorAffiliation_xml | – name: 3 Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA – name: 2 Division of Health Sciences and Technology, Harvard University - Massachusetts Institute of Technology, Cambridge, MA 02139, USA – name: 4 Center of Excellence for Learning in Education, Science and Technology, Boston University, 677 Beacon Street, Boston, MA, 02215 – name: 1 Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA, 02215 |
| Author_xml | – sequence: 1 givenname: Frank H. surname: Guenther fullname: Guenther, Frank H. email: guenther@cns.bu.edu organization: Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA, 02215, USA – sequence: 2 givenname: Tony surname: Vladusich fullname: Vladusich, Tony organization: Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA, 02215, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/22711978$$D View this record in MEDLINE/PubMed |
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| PublicationDate | September 2012 2012-9-00 2012-Sep-01 20120901 |
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| PublicationTitle | Journal of neurolinguistics |
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| Title | A neural theory of speech acquisition and production |
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