Cortical network underlying executive control of auditory attention in early psychosis - supplement

项目摘要/摘要-不更改原始版本。 选择性注意受损是精神病(FEP)首发时存在的一种基本认知缺陷。 听觉选择性注意可以用脑电(EEG)测量。一种迟发性感觉加工 声音是通过刺激后约100毫秒(N1)出现的事件相关负性来测量的。当个人支付时 注意声音，N1的幅度增大。试验中N1波幅之间的差异 注意与忽略会产生负差异(ND)，这是选择性注意调节的一种具体措施。 我们实验室以前的数据表明，FEP在调节N1的选择性注意方面受到损害(即 ND减少)，我们实验室的试点数据表明，ND与大脑灰质(GM)缺陷有关 行政控制区。神经元记录和人类功能磁共振研究表明，执行控制网络 涉及前额叶皮质(PFC)和后顶叶皮质(PPC)，它们调节感觉皮质 作为听觉皮质(AC)。这个项目将研究听觉执行控制的基础网络 注意调制和FEP中该网络的结构异常。这项建议充分利用了 实验室正在进行的一项研究的基础设施到位，在该研究中，健康参与者和FEP患者 在注意和忽略情况下执行标准的双音古怪任务，而同时进行脑电和 记录脑磁图(MEG)。在目标1中，脑电和脑磁图将与个人合并 在ND的时间窗口内(刺激后约100ms)，结构MRI扫描以源解析活动。这 Project还收集了结构磁共振和静息功能磁共振成像到准功能的大脑皮质，以估计GM 在听觉注意网络的节点内。网络的节点将通过应用Glasser来定义 在所有参与者中，PFC、PPC和AC区域的多模式皮质分离具有最大的活动。在……里面 目标2，高分辨率磁共振数据将通过先进的人类连接组计划(HCP)进行处理 管道，以显著改善皮质区域的登记。GM厚度估计将在 累及大脑皮层，并比较HC和FEP。GM厚度将与认知相关 表现和症状评分。这一项目的结果将使人们深入了解全球变暖 听觉注意网络潜伏在FEP中的选择性注意缺陷。知道哪里存在异常 将允许治疗针对非常特定的大脑区域。我的培训将集中在获得高级 核磁共振处理和分析技术，充分利用了HCP新兴的最先进的方法。在目标1中， 我将学习如何使用脑电和脑磁图数据来估计来源解析的活动。在目标2中，我将获得以下方面的专业知识 HCP管道中用于分析结构数据的高级处理方法。我还会学习扩散 光谱成像(DSI)作为我MRI培训的一部分，我将获得与人群合作的专业知识 精神病和对早期精神病的结构异常的理解。这段经历会对我有帮助 完成我的职业目标，成为临床认知神经科学领域的主要研究人员。

Project Summary/Abstract - no change to original. Impaired selective attention is a fundamental cognitive deficit present in the first episode of psychosis (FEP). Auditory selective attention can be measured with electroencephalography (EEG). Late sensory processing of a sound is measured by the event-related negativity present ~100ms post-stimulus (N1). When individuals pay attention to the sound, the amplitude of the N1 increases. The difference between N1 amplitudes on trials of attend vs ignore produces a negative difference (Nd), a specific measure of modulation with selective attention. Previous data from our lab suggests that FEP are impaired in modulating the N1 with selective attention (i.e. reduced Nd), and pilot data in our lab suggests that the Nd is associated with gray matter (GM) deficits in executive control areas. Neuronal recordings and human fMRI studies suggest an executive control network that involves the prefrontal cortex (PFC) and posterior parietal cortex (PPC), which modulates sensory cortices such as auditory cortex (AC). This project will investigate the network underlying the executive control of auditory attention modulation and structural abnormalities of this network in FEP. This proposal takes advantage of infrastructure in place from an ongoing study in the lab, in which healthy participants and patients with FEP perform a standard two-tone oddball task with attend and ignore conditions, while concurrent EEG and magnetoencephalography (MEG) are recorded. In Aim 1, the EEG and MEG will be merged with individual structural MRI scans to source resolve activity during the time window of the Nd (~100ms post stimulus). This project has also collected structural MR and resting fMRI to quasi-functionally parcellate cortex to estimate GM within nodes of the auditory attention network. The nodes of the network will be defined by applying the Glasser multimodal cortical parcellation to regions of PFC, PPC, and AC with the greatest activity in all participants. In Aim 2, high resolution MR data will be processed through the advanced Human Connectome Project (HCP) pipelines to significantly improve the registration of cortical areas. GM thickness will be estimated within the implicated cortical regions and compared between HC and FEP. GM thickness will be correlated with cognitive performance and symptom scores. The results from this project will give insight to the GM abnormalities in the auditory attention network underlying selective attention deficits seen in FEP. Knowing where abnormalities exist will allow therapies to target very specific brain areas. My training will focus on gaining expertise in advanced MRI processing and analytic techniques capitalizing on the HCP’s emerging state-of-the-art methods. In Aim 1, I will learn how to use EEG and MEG data to estimate source resolved activity. In Aim 2, I will gain expertise in the advanced processing methods used in the HCP pipeline to analyze structural data. I will also learn Diffusion Spectrum Imaging (DSI) as part of my MRI training, and I will gain expertise in working with a population with psychosis and understanding the structural abnormalities of early psychosis. This experience will help me accomplish my career objective of becoming a primary investigator in the field of clinical cognitive neuroscience.