Pediatric Head Models for Improved Imaging of Neurological Development

描述（由申请人提供）：虽然众所周知，大脑从出生到幼儿期经历快速的发育变化，但对大脑大小和组成的变化与认知发育之间的关系知之甚少。然而，几种潜在的使人衰弱的神经认知障碍是大脑发育延迟或异常的结果，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。这些关联使得我们必须更好地理解认知和解剖发展之间的关系。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，这些技术不会过度限制运动，也不需要电离辐射。在可用的技术中，脑电图（EEG），特别是随着高密度传感器阵列的出现，提供了安全和非侵入性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科头部模型，以改善儿科人群的电流源定位成像，前提是认知重要的大脑区域和网络的功能定位需要头部组织几何形状和电导率的准确模型。这个第二阶段项目将建立在第一阶段完成的工作基础上，以创建在大脑和头骨发育测量方面存在显著差异的年龄组。对于每个集群，我们 将建立和测试头部模型，这些模型在形态特征和组织电导率的区域差异方面都是准确的，这在从EEG信号准确重建大脑网络活动的能力中起着关键作用。一旦开发和测试了特定年龄的平均头部模型，我们将使用脑电图和功能性磁共振成像方法在婴儿期到青年期的儿童中基于神经生理数据验证其改进的准确性。该项目将导致公开发布一套创新的年龄特定的 头部模型以及我们项目网站（www.pedeheadmod.net）上新开发的软件。此外，该项目还将提供一种新的商业产品Child Geosource（R），它将允许源定位研究，而不需要对精确头部模型进行CT或MR扫描。

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.