Abstract
Electroencephalography (EEG) is frequently used in functional neurological assessment of children with neurological and neuropsychiatric disorders. Multiscale entropy (MSE) can reveal complexity in both short and long time scales and is more feasible in the analysis of EEG. Entropy-based estimation of EEG complexity is a powerful tool in investigating the underlying disturbances of neural networks of the brain. Most neurological and neuropsychiatric disorders in childhood affect the early stage of brain development. The analysis of EEG complexity may show the influences of different neurological and neuropsychiatric disorders on different regions of the brain during development. This article aims to give a brief summary of current concepts of MSE analysis in pediatric neurological and neuropsychiatric disorders. Studies utilizing MSE or its modifications for investigating neurological and neuropsychiatric disorders in children were reviewed. Abnormal EEG complexity was shown in a variety of childhood neurological and neuropsychiatric diseases, including autism, attention deficit/hyperactivity disorder, Tourette syndrome, and epilepsy in infancy and childhood. MSE has been shown to be a powerful method for analyzing the non-linear anomaly of EEG in childhood neurological diseases. Further studies are needed to show its clinical implications on diagnosis, treatment, and outcome prediction.
Highlights
Electroencephalography (EEG) is a commonly-used modality to examine children with neurological or neuropsychiatric disorders
This multiscale approach has found that changes of entropy may only be recognized in either larger or smaller time scales in the studies of childhood neuropsychiatric diseases such as autism spectrum disorders (ASD) and Gilles de la Tourette syndrome (GTS), as well as in childhood neurological disorders such as childhood epilepsy syndromes and neonatal seizures (Table 1)
No differences in EEG power spectra were noted between groups
Summary
Electroencephalography (EEG) is a commonly-used modality to examine children with neurological or neuropsychiatric disorders. Multiscale entropy (MSE) has been introduced to reflect the complexity, or the “meaningful structural richness”, by analyzing the SamEn on a set of coarse-grained time series derived from the original biophysiological signals at different scale factors [8]. This multiscale approach has found that changes of entropy may only be recognized in either larger or smaller time scales in the studies of childhood neuropsychiatric diseases such as autism spectrum disorders (ASD) and Gilles de la Tourette syndrome (GTS), as well as in childhood neurological disorders such as childhood epilepsy syndromes and neonatal seizures (Table 1). Summary of studies using entropy analysis in pediatric neurological and neuropsychiatric disorders
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