CRCNS: US-German Data Sharing Proposal: Analysis and Visualization of Neural Osci

描述(由申请人提供)：拟议拨款提案的目标是促进两个研究感知和认知的神经元基础的实验室之间的国际合作。赠款的具体目的是分析从脑植入物患者获得的独特数据集，额外收集和分析免费的头皮脑电数据，并创建一个分析工具箱并向更广泛的科学界公开传播。此外，还将编写一份关于实验数据集分析的出版物。这笔补助金将用于支付学生和博士后的工资以及中期交流访问。认知神经科学研究极大地受益于方法学方法和分析技术的快速发展。使用硬膜下电极记录神经外科患者的皮层脑电(ECoG)信号是研究感觉运动和认知过程潜在神经机制的有力手段。虽然ECoG记录提供了一个研究这些过程的机会，具有高空间和时间分辨率的独特组合，但这种方法也有其局限性。电极记录很少在患者之间重叠，ECoG信号通常只从几个皮质区域监测。使用脑电(EEG)或脑磁图(MEG)对人类神经活动的非侵入性记录的空间分辨率要低得多，与ECoG相比，测量大脑信号的信噪比更低，但具有同时覆盖整个头部的优势。此外，最先进的源分析技术，特别是对神经振荡的分析，可以相对充分地估计EEG/MEG信号背后的皮质源，然而，验证它们的源解决方案需要侵入性的电极放置。因此，结合来自同一实验范式的ECoG和EEG/MEG信号的翻译研究特别有希望。然而，到目前为止，还没有专门针对神经振荡的ECoG和EEG/MEG信号比较的分析和可视化工具箱。拟议的项目将融合以下实验室的专业知识 这两个PI将Senkowski实验室的振荡数据分析专业知识应用于之前从特森实验室的侵入性人类颅内记录中收集的独特的多感官ECoG数据集。具体地说，将分析来自感觉间注意范式的可用的ECoG数据，并将其与从相同范式记录的脑电数据进行比较。当前建议的中心目标是(I)开发一个用于分析和可视化ECoG数据中的神经振荡的工具箱，以及(Ii)通过协作数据共享，通过分析来自感觉间注意范式的颅内和EEG数据来测试该工具箱。该工具箱将包括能够将ECoG信号与局部来源的EEG/MEG信号进行比较的功能，将与更广泛的科学界共享。由于它的功能和它与流行的实地考察工具箱(http://fieldtrip.fcdonders.nl)，)的兼容性，ECoG工具箱将特别引起这一认知神经科学领域的大量研究人员的兴趣。总体而言，ECoG工具箱的开发可以促进神经振荡的翻译研究。由于在临床人群中，神经振荡的损害通常与症状学有关，例如在自闭症或精神分裂症患者中，这项研究具有重要的临床意义。更好地了解神经振荡在认知功能中的作用有助于更好地理解这些人群的症状。综上所述，目前的提议将导致基于协作共享来自感觉间注意研究的数据的经验性输出。此外，通过开发一个用户友好的工具箱来分析和可视化ECoG和联合ECoG-EEG数据中的神经同步性，将直接造福于更广泛的科学界。

DESCRIPTION (provided by applicant): The goal of the proposed grant proposal is to foster international collaboration between two laboratories studying the neuronal basis of perception and cognition. Specific aims of the grant is the analysis of a unique data set obtained from patients with brain implants, the additional collection and analysis of complimentary scalp EEG data and the creation and public dissemination of an analysis toolbox to the wider scientific community. In addition, a publication will be prepared on the analysis of the experimental data sets. The grant will support student and postdoc salaries and medium-term exchange visits. Cognitive neuroscience research benefits vastly from the rapid progression of development in methodological approaches and analysis techniques. Recordings of electrocorticographic (ECoG) signals from neurosurgical patients with subdural electrodes represent a powerful approach for examining the neural mechanisms underlying sensorimotor and cognitive processes. While ECoG recordings provide an opportunity to study these processes with a unique combination of high spatial and temporal resolution, this approach also has its limitations. Electrode recordings sites rarely overlap across patients and ECoG signals are usually monitored only from a few cortical regions. Non-invasive recordings of neural activity in humans using electroencephalography (EEG) or magnetoencephalography (MEG) have a much lower spatial resolution and measure brain signals with a reduced signal-to-noise ratio compared to ECoG, but have the advantage of covering the entire head simultaneously. In addition, state-of-the-art source analysis techniques, especially the analysis of neural oscillations, may allow a relatively adequate estimation of the cortical sources underlying EEG/MEG signals, however, validating their source solutions requires invasive electrode placement. Therefore, translational studies combing ECoG and EEG/MEG signals from the same experimental paradigm are particularly promising. To date, however, there is no analysis and visualization toolbox for the comparison of ECoG and EEG/MEG signals that specifically focuses on neural oscillations. The proposed project will fuse the expertise of the laboratories of the two PIs by applying the oscillatory data analysis expertise of the Senkowski Lab to the unique multisensory ECoG data sets previously collected from invasive human intracranial recordings at the Thesen Lab. Specifically, available ECoG data from an intersensory attention paradigm will be analyzed and compared with EEG data recorded from the same paradigm. The central goals of the current proposal are (i) to develop a toolbox for the analysis and visualization of neural oscillations in ECoG data, and (ii) to test this ECoG-toolbox by analyzing intracranial and EEG data from an intersensory attention paradigm through collaborative data sharing. The toolbox, which will include functions enabling the comparison of ECoG signals with source-localized EEG/MEG signals, will be shared with the wider scientific community. Due to its functionality and its compatibility with the popular FieldTrip toolbox (http://fieldtrip.fcdonders.nl), the ECoG-toolbox will be of particular interest to the large numbe of researchers in this growing field of cognitive neuroscience. Overall, the development of the ECoG-toolbox could facilitate the translational research on neural oscillations. Since impairments in neural oscillations have often been linked to symptomatology in clinical populations, such as in patients with autism or schizophrenia, this research has significant clinical implications. A better understanding of the role of neural oscillations in cognitive functions could contribute to a better understanding of the symptomatology in these populations. Taken together, the current proposal will lead to empirical output based on collaborative sharing of data from an intersensory attention study. Furthermore, by developing a user-friendly toolbox for the analysis and visualization of neural synchrony in ECoG and combined ECoG-EEG data, there will be a direct benefit to the wider scientific community.