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实验室之间的国际合作，研究感知和认知的神经元基础。赠款的具体目标是分析从大脑植入患者获得的独特数据集，额外收集和分析免费头皮EEG数据，以及创建和向更广泛的科学界公开传播分析工具箱。此外，还将编写一份关于实验数据集分析的出版物。该赠款将支持学生和博士后的工资和中期交流访问。认知神经科学研究从方法论和分析技术的快速发展中受益匪浅。记录皮质电图（ECoG）信号的神经外科患者与硬膜下电极代表了一个强大的方法来检查神经机制的感觉运动和认知过程。虽然ECoG记录提供了一个机会，以研究这些过程的高空间和时间分辨率的独特组合，这种方法也有其局限性。电极记录部位很少在患者之间重叠，并且ECoG信号通常仅从少数皮质区域进行监测。使用脑电图（EEG）或脑磁图（MEG）对人类神经活动进行非侵入性记录的空间分辨率要低得多，并且与ECoG相比，测量脑信号的信噪比降低，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，特别是神经振荡的分析，可以允许对EEG/MEG信号下的皮层源进行相对充分的估计，然而，验证其源解决方案需要侵入性电极放置。因此，从相同的实验范式结合ECoG和EEG/MEG信号的转化研究是特别有前途的。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。拟议的项目将融合实验室的专业知识， 通过将Senkowski实验室的振荡数据分析专业知识应用于之前在Thesen实验室从侵入性人类颅内记录中收集的独特多感官ECoG数据集，具体而言，从一个感官间注意范式的ECoG数据将进行分析，并从相同的范式记录的EEG数据进行比较。当前提案的中心目标是（i）开发一个工具箱，用于分析和可视化ECoG数据中的神经振荡，以及（ii）通过协作数据共享分析来自感觉间注意范式的颅内和EEG数据来测试此ECoG工具箱。该工具箱将与更广泛的科学界共享，其中包括能够将ECoG信号与源定位EEG/MEG信号进行比较的功能。由于它的功能和它与流行的FieldTrip工具箱（http：//www.example.com）的兼容性，ECoG工具箱将在这个不断发展的认知神经科学领域引起大量研究人员的特别兴趣。fieldtrip.fcdonders.nl总体而言，ECoG工具箱的开发可以促进神经振荡的转化研究。由于神经振荡的损伤通常与临床人群中的神经病学有关，例如自闭症或精神分裂症患者，因此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，有助于更好地了解这些人群的神经病学。总之，目前的建议将导致经验输出的基础上合作共享的数据，从感官间的注意力研究。此外，通过开发一个用户友好的工具箱，用于分析和可视化ECoG和组合ECoG-EEG数据中的神经同步，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.