Electrophysiological auditory responses and language development in infants with periventricular leukomalacia
► EEG induced power in infants predicts language development. ► We record EEG responses to syllables and tones in infants with PVL at 46 weeks of PCA. ► A follow-up at 14 months of age allowed the separation in two well-defined groups. ► These 2 groups were well separated by variables obtained from...
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Published in | Brain and language Vol. 119; no. 3; pp. 175 - 183 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier Inc
01.12.2011
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | ► EEG induced power in infants predicts language development. ► We record EEG responses to syllables and tones in infants with PVL at 46
weeks of PCA. ► A follow-up at 14
months of age allowed the separation in two well-defined groups. ► These 2 groups were well separated by variables obtained from the EEG. ► A predictive classification rate of 80% for unseen data was obtained.
This study presents evidence suggesting that electrophysiological responses to language-related auditory stimuli recorded at 46
weeks postconceptional age (PCA) are associated with language development, particularly in infants with periventricular leukomalacia (PVL). In order to investigate this hypothesis, electrophysiological responses to a set of auditory stimuli consisting of series of syllables and tones were recorded from a population of infants with PVL at 46
weeks PCA. A communicative development inventory (i.e., parent report) was applied to this population during a follow-up study performed at 14
months of age. The results of this later test were analyzed with a statistical clustering procedure, which resulted in two well-defined groups identified as the high-score (HS) and low-score (LS) groups. The event-induced power of the EEG data recorded at 46
weeks PCA was analyzed using a dimensionality reduction approach, resulting in a new set of descriptive variables. The LS and HS groups formed well-separated clusters in the space spanned by these descriptive variables, which can therefore be used to predict whether a new subject will belong to either of these groups. A predictive classification rate of 80% was obtained by using a linear classifier that was trained with a leave-one-out cross-validation technique. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 0093-934X 1090-2155 |
DOI: | 10.1016/j.bandl.2011.06.002 |