2015
DOI: 10.1111/epi.13281
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Effects of prenatal antiepileptic drug exposure on newborn brain activity

Abstract: SUMMARYObjective: Prenatal exposure to antiepileptic drugs (AEDs) is associated with an increased risk of cognitive dysfunction at early school age. Our aim was to investigate whether signs of adverse drug effects on brain function could be detected already during the first 2 weeks of life. Methods: We studied prospectively 56 full-term newborns with prenatal exposure to AEDs and 67 unexposed newborns for the following characteristics: Background information, AED exposure data, pregnancy outcome, neuropsycholo… Show more

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Cited by 27 publications
(44 citation statements)
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References 38 publications
(93 reference statements)
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“…Supporting the hypothesis that AED exposure may alter the development of activity-dependent neural networks, we recently found significant differences in the newborn cortical activity after prenatal exposure to AEDs [20]. These findings suggested that prenatal AED exposure might interfere with temporal occurrence and spatial coordination of the developing brain, possibly leading to functional effects that emerge behaviorally in later infancy.…”
Section: Introductionsupporting
confidence: 64%
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“…Supporting the hypothesis that AED exposure may alter the development of activity-dependent neural networks, we recently found significant differences in the newborn cortical activity after prenatal exposure to AEDs [20]. These findings suggested that prenatal AED exposure might interfere with temporal occurrence and spatial coordination of the developing brain, possibly leading to functional effects that emerge behaviorally in later infancy.…”
Section: Introductionsupporting
confidence: 64%
“…One of the proposed mechanisms at cellular level has been altered apoptosis [11][12][13][14] contributing to structural changes in the cerebellum [15], hippocampus, and cortex [16]. Functional changes have been suggested to be due to alterations in synaptic maturation, in organization of neuronal networks, and in electric brain activity [13,[17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%
“…Table 5.3 provides a list of composite features used. [148,195] Higuchi fractal dimension, algorithmic entropy [163] Renyi, Shannon and Tsaillis entropy [164,230] Approximate and Sample entropy [166] Hurst exponent [168,230] Frequency( ) Spectral and relative powerbased features ( ) Spectral Flatness, Flux and Entropy [35] Spectral Edge frequency at 80, 90 and 95% [169,195,222] Spectral Edge power at 80, 90 and 95% [169,195,222] Total power in delta, theta and alpha bands [222] Relative power in delta, theta and alpha bands w.r.t total EEG power [170,222] Delta to theta power ratio (DTR) [231] Delta to alpha power ratio (DAR) [222,232] Mean bout in delta, alpha and theta band [229] Bout percentage in delta, alpha and theta band [229] Time-frequency ( , ) ( , ) -signal based features…”
Section: Composite Features Extractionmentioning
confidence: 99%
“…Low activity duration and Low activity density High activity duration and High activity density Global mean (IBI) [229] Global median (IBI) [229] …”
Section: Composite Features Between Two Channelsmentioning
confidence: 99%
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