Pediatric Head Models for Improved Imaging of Neurological Development

描述（由申请人提供）：众所周知，从出生到童年早期，大脑经历了快速的发育变化，但人们对大脑大小和组成变化与认知发展之间的关系知之甚少。然而，一些可能使人衰弱的神经认知障碍是大脑发育迟缓或异常的结果，儿童癫痫已被证明与学习障碍、注意力缺陷多动障碍和抑郁症的风险增加有关。这些关联使得我们有必要更好地理解认知和解剖学发展之间的关系。在儿童中，认知和大脑发育轨迹的研究最好使用非侵入性技术来完成，这种技术不会过度限制运动，也不需要电离辐射。在现有技术中，脑电图（EEG），特别是随着高密度传感器阵列的出现，提供了安全、无创地评估认知功能的能力。我们的中心目标是开发特定年龄的儿童头部模型，以改善儿童人群的当前源定位成像，假设认知重要的大脑区域和网络的功能定位需要准确的头部组织几何和电导率模型。这个第二阶段的项目将建立在第一阶段完成的工作的基础上，创建在大脑和头骨发育方面有显著差异的年龄组。对于每个集群，我们

DESCRIPTION (provided by applicant): While it is well known that the brain undergoes rapid developmental changes from birth to early childhood, remarkably little is understood about the relationship between changes in brain size and composition and cognitive development. Yet several potentially debilitating neurocognitive disorders are a consequence of delays or abnormalities in brain development, and childhood epilepsy has been shown to be associated with an increased risk of learning disabilities, attention-deficit hyperactivity disorder and depression. These associations make it imperative that we gain a better understanding of the relationship between cognitive and anatomical development. In children, the study of cognitive and brain developmental trajectories are best accomplished using non-invasive techniques that are not overly restrictive of movement and do not require ionizing radiation. Of available techniques, electroencephalography (EEG), particularly with the advent of high density sensor arrays, provides the ability to assess cognitive function safely and non-invasively. Our central goal is to develop age- specific pediatric head models to improve current source localization imaging in pediatric populations under the hypothesis that functional localization of cognitively important brain regions and networks requires an accurate model of head tissue geometry and conductivity. This Phase 2 project will build on work accomplished in phase 1 to create age clusters that differ significantly in measures of brain and skull development. For each cluster, we will build and test head models that are accurate both in morphological features and in regional differences in tissue conductivity which plays a critical role in the ability to accurately reconstuct brain network activity from EEG signals. Once age- specific average head models have been developed and tested, we will validate their improved accuracy based on neurophysiological data using EEG and functional magnetic resonance imaging methods in children from infancy to young adulthood. This project will result in the public release of a set of innovative age-specific head models together with newly developed software from our project website (www.pedeheadmod.net). In addition, the project will provide a novel commercial product, Child Geosource(R), which will allow source localization studies without the otherwise limiting need for CT or MR scanning for accurate head models.