Functional Brain Maturation in Neonates As Measured by EEG-sleep Analyses

MS Scher,BL Jones,DA Steppe,DL Cork,HJ Seltman,DL Banks

Clinical Neurophysiology（2003）SCI 3区

Corresponding author. Tel.: +1-216-844-3691; fax: +1-216-844-8966 | Developmental Neurophysiology Laboratory

Cited 43|Views11

Abstract

Objective: Seven measures of neonatal EEG-sleep behavior were evaluated using multivariate analyses to ascertain if physiologic differences exist between healthy full- and preterm cohorts.Methods: A total of 381 24-channel EEG-sleep studies were analyzed, including 125 recordings on 50 healthy fullterm and 256 recordings on 59 asymptomatic preterm infants between 28 and 70.6 weeks post-conceptional age. One EEG study for each subject was randomly assigned (109 studies) within the time window of 38-44 weeks post-conceptional age. A multivariate analytic procedure was applied to the data sets, by which a 'dysmaturity index' was assigned for each infant, based on 7 EEG-sleep measures. This index was defined in terms of the distance from the fullterm group's centroid (i.e. Mahalanobis distance). Receiver-operating characteristic curves (ROCs) were calculated for several different combinations of 7 EEG-sleep measures to describe differences between neonatal cohorts.Results: The ROC curve corresponding to all 7 EEG-sleep measures covered the substantially largest area among the curves for the sets of variables considered, suggesting that all 7 measures of sleep behavior were required to best discriminate between cohorts.Conclusions: This methodology exemplifies how EEG-sleep analyses can be applied to the study of functional brain maturation of infants at risk for neurodevelopment problems.Significance: Changes in EEG-sleep behavior in the preterm infant may represent altered activity-dependent development of neural circuitry, resulting in remodeling of the immature brain as a reflection of adaptation to conditions of prematurity. (C) 2003 International Federation of Clinical Neurophysiology. Published by Elsevier Science Ireland Ltd. All rights reserved.

Translated text

Key words

electroencephalographic sleep,neonate,preterm,fullterm,brain dysmaturity

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper