Defining the Dynamics of the Default Network with Direct Brain Recordings and fun

描述（由申请人提供）：人类默认网络（DN）内的异常活动模式与许多神经精神障碍（如精神分裂症、抑郁症、自闭症谱系障碍或ADHD）相关的认知和行为障碍有关，DN是在内省思维期间参与并在感觉运动处理期间受到抑制的功能性连接的大脑区域的星座。例如，功能性磁共振成像（fMRI）研究表明，DN活动的异常模式可能部分地协调了精神分裂症的思维障碍特征。功能磁共振成像显示，在各种神经精神疾病状态下，DN功能障碍可能不是共同的病理生理过程的结果。尽管有这样的假设，显着很少有人知道的电生理动力学的DN，信息是至关重要的机械理解异常功能在系统水平。本提案中概述的实验的总体目标是使用两种技术定义DN的电生理学动力学：1，皮质电描记术（ECoG），利用硬脑膜下ECoG电极的标准护理植入对难治性癫痫患者进行术前评估; 2，高频头皮脑电图（EEG）。具体目标1将使用ECoG来确定在诱发事件相关的内省，“自我参照”任务和由语言任务产生的DN抑制期间DN内神经反应的快速和动态定时。在具体目标2中，我们将使用ECoG来表征DN和语言或任务正网络之间的相互作用，以阐明DN干扰任务表现的神经机制。然而，ECoG的使用仅限于需要开颅手术暴露的人群。因此，在具体目标3中，我们将利用EEG方法学中的新方法，并使用ECoG作为金标准，检查EEG将电活动定位到DN深层皮质区域的能力。基于他在功能成像方面的背景，设计了一个培训计划，并组建了一支由神经外科医生、神经学家和电生理学家组成的杰出团队，为候选人提供将电生理学纳入其研究活动所需的知识。未来的应用程序的多模式的方法，采用功能成像和电生理学的追求DN功能的精神病患者提供了一个精致的敏感的手段，分析的范围和贡献的DN功能障碍的生物学基础的心理健康。 公共卫生相关性：这些实验的预期结果将精确地描述人类默认网络的神经生理动力学特征。它们将有助于我们理解默认网络的生物学效用、相关性和功能，并更深入地了解在精神分裂症、自闭症、抑郁症和多动症等各种精神疾病中发生的网络异常如何影响潜在的病理学。

DESCRIPTION (provided by applicant): Abnormal patterns of activity within the human default network (DN), which is a constellation of functionally connected brain regions that is engaged during introspective thought and suppressed during sensorimotor processing, has been linked to the cognitive and behavioral impairments associated with host of neuropsychiatric disorders such as schizophrenia, depression, autism spectrum disorder or ADHD. For instance, functional magnetic resonance imaging (fMRI) studies have revealed that aberrant patterns of DN activity may in part orchestrate disordered-thinking characteristic to schizophrenia. DN dysfunction, as illuminated with fMRI, across various neuropsychiatric disease states is likely not a consequence of a shared pathophysiologic process. Despite this assumption, remarkably little is known about the electrophysiological dynamics of the DN, information that is crucial to a mechanistic understanding of abnormal function at a systems level. The overall goal of the experiments outlined in this proposal is to define the electrophysiological dynamics of the DN using two techniques: 1, electrocortiography (ECoG), capitalizing on the standard-of-care implantation of subdural ECoG electrodes in the presurgical evaluation of individuals with intractable epilepsy and 2, high frequency scalp-based electroencephalography (EEG). Specific Aim 1 will use ECoG to determine the rapid and dynamic timing of neural responses within the DN during an evoked event-related introspective, 'self-referential' task and during DN suppression engendered by a linguistic task. In Specific Aim 2, we will use ECoG to characterize the interactions between the DN and a language or task positive network to elucidate the neuronal mechanisms underlying DN interference on task performance. However, use of ECoG is limited to populations requiring craniotomies for surgical exposure. Therefore, in Specific Aim 3 we will capitalize on new approaches in EEG methodology and examine the ability of EEG to localize electrical activity to the deep cortical regions of the DN, using ECoG as the gold standard. Building upon his background in functional imaging, a training program has been designed and a distinguished team of neurosurgeons, neurologists and electrophysiologists has been assembled to provide the candidate with the knowledge necessary to incorporate electrophysiology into his research activities. The future application of a multimodal approach, employing both functional imaging and electrophysiology to the pursuits of DN function in psychiatric populations provides an exquisitely sensitive means of profiling the range and contributions of DN dysfunction to the biological basis of mental health. PUBLIC HEALTH RELEVANCE: The anticipated results from these experiments will precisely characterize the neurophysiological dynamics of the default network in humans. They will contribute to our understanding of the biological utility, relevance and function of the default network and provide greater insight into how reported network abnormalities occurring in various mental disorders such as Schizophrenia, Autism, depression and ADHD contribute to underlying pathology.