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Using Cognitive Neuroscience to Exam...
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Norton, Elizabeth Spencer.
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Using Cognitive Neuroscience to Examine the Brain Basis of Pre-Reading Skills in Kindergarten Children and Subtypes of Risk for Dyslexia: Toward MRI and EEG Prediction of Reading Outcomes.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Using Cognitive Neuroscience to Examine the Brain Basis of Pre-Reading Skills in Kindergarten Children and Subtypes of Risk for Dyslexia: Toward MRI and EEG Prediction of Reading Outcomes./
作者:
Norton, Elizabeth Spencer.
面頁冊數:
184 p.
附註:
Source: Dissertation Abstracts International, Volume: 73-11(E), Section: B.
Contained By:
Dissertation Abstracts International73-11B(E).
標題:
Developmental psychology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3512425
ISBN:
9781267414168
Using Cognitive Neuroscience to Examine the Brain Basis of Pre-Reading Skills in Kindergarten Children and Subtypes of Risk for Dyslexia: Toward MRI and EEG Prediction of Reading Outcomes.
Norton, Elizabeth Spencer.
Using Cognitive Neuroscience to Examine the Brain Basis of Pre-Reading Skills in Kindergarten Children and Subtypes of Risk for Dyslexia: Toward MRI and EEG Prediction of Reading Outcomes.
- 184 p.
Source: Dissertation Abstracts International, Volume: 73-11(E), Section: B.
Thesis (Ph.D.)--Tufts University, 2012.
Each child must build a reading brain by developing accuracy and speed in the multiple cognitive and linguistic processes required for reading, as well as the ability to integrate these processes for efficient comprehension. A weakness in any component of the brain's "reading circuit" can cause dyslexia, defined as an unexpected difficulty learning to read. In order to prevent the negative consequences of dyslexia, it is important to identify reading difficulties early and accurately. Decades of behavioral research have examined which measures predict later reading outcomes, yet even when the most widely-used and well-designed assessment measures are combined, behavioral models are unable to predict reading outcomes with sufficient accuracy. Findings from behavioral studies, however, converge on three major predictors: phonological awareness (PA), letter knowledge (LK), and rapid automatized naming (RAN). Recently, brain imaging methods including magnetic resonance imaging (MRI) and electroencephalography (EEG) have shown substantial accuracy in predicting reading outcomes. This study used fMRI and EEG brain imaging with 43 kindergarten children to examine the neural correlates of PA, LK, and automaticity. Results revealed differentiated patterns of brain activation for kindergarten children with and without risk for dyslexia as measured by PA, LK, and RAN scores. These patterns of brain activation have the potential to help identify which children will have dyslexia before they struggle with learning to read, and to identify which types of intervention could most effectively be used with individual children.
ISBN: 9781267414168Subjects--Topical Terms:
516948
Developmental psychology.
Using Cognitive Neuroscience to Examine the Brain Basis of Pre-Reading Skills in Kindergarten Children and Subtypes of Risk for Dyslexia: Toward MRI and EEG Prediction of Reading Outcomes.
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184 p.
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Each child must build a reading brain by developing accuracy and speed in the multiple cognitive and linguistic processes required for reading, as well as the ability to integrate these processes for efficient comprehension. A weakness in any component of the brain's "reading circuit" can cause dyslexia, defined as an unexpected difficulty learning to read. In order to prevent the negative consequences of dyslexia, it is important to identify reading difficulties early and accurately. Decades of behavioral research have examined which measures predict later reading outcomes, yet even when the most widely-used and well-designed assessment measures are combined, behavioral models are unable to predict reading outcomes with sufficient accuracy. Findings from behavioral studies, however, converge on three major predictors: phonological awareness (PA), letter knowledge (LK), and rapid automatized naming (RAN). Recently, brain imaging methods including magnetic resonance imaging (MRI) and electroencephalography (EEG) have shown substantial accuracy in predicting reading outcomes. This study used fMRI and EEG brain imaging with 43 kindergarten children to examine the neural correlates of PA, LK, and automaticity. Results revealed differentiated patterns of brain activation for kindergarten children with and without risk for dyslexia as measured by PA, LK, and RAN scores. These patterns of brain activation have the potential to help identify which children will have dyslexia before they struggle with learning to read, and to identify which types of intervention could most effectively be used with individual children.
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