学　术

　　为搭建我校博士后之间的学术交流平台，促进学术水平提升，学校博士后管理办公室组织开展博士后学术沙龙活动。本次沙龙由我校博士后赵敏、姚树霞、黄柯、Eduardo Gonzalez Moreira和王庆分享其研究成果，诚挚邀请感兴趣的师生参加。

　　一、时　间：2017年10月19日（周四）13：30

　　二、地点：清水河校区经管楼宾诺咖啡

　　三、活动安排：

　　报告一：     

　　主　题：基于EEG的测谎技术

　　主讲人：赵敏　生物医学工程流动站博士后 

　　交流内容：

　　本次报告中，我们介绍基于EEG的现代测谎技术，主要从三个方面进行介绍：1）传统测谎技术的研究现状；2）基于EEG的现代测谎技术及EEG测谎技术存在的问题。

　　首先，从传统测谎技术存在的问题或不足谈起，传统测谎技术主要指多道生理记录仪（Polygraph）测谎技术，其测试机理是依据人说谎时的焦虑和惧怕心理而引发的自主神经系统的生理反应来识别其是否说谎,主要包括皮肤电、脉搏和呼吸等生理参数。传统测谎技术仅仅是依据人说谎时的焦虑和惧怕心理而引发的自主神经系统支配的生理反应测量值来做出判断，而这些生理反应与说谎本身并没有必然的对应关系，因此该项技术存在着诸多争议和质疑。

　　其次，我们讨论基于EEG测谎技术的测谎机理及主要测试指标。现代测谎技术主要通过测试受试者的由中枢神经系统控制的生理参数的变化来判断其是否说谎。测试理论依据：是受试者对犯罪相关信息和无关信息的认知加工存在差异，表现为相关信息诱发的ERP成分波与无关信息诱发的ERP成分存在差异，则可以推断出受试者是否对犯罪相关信息知情（或说谎）。目前，在研究中受到广泛关注的仍然是ERP P300成分。

　　主讲人简介：

　　赵敏，2005-2011年于西安交通大学生命科学技术学院生物医学工程专业博士毕业，现工作于西安武警工程大学，于2017年3月入电子科技大学生命学院博士后流动站，主要从事基于EEG信号的测谎技术研究。

　　报告二：

　　主　题：Oxytocin modulates attention switching between interoceptive signals and external social cues

　　主讲人：姚树霞 生物医学工程流动站博士后 

　　交流内容：

　　Emotional experience involves an integrated interplay between processing of external emotional cues and interoceptive feedback, and this is impaired in a number of emotional disorders. The neuropeptide oxytocin (OT) enhances the salience of external social cues but its influence on interoception is unknown. The present pharmaco-fMRI study therefore investigated whether OT enhances interoceptive awareness and if it influences the interplay between interoceptive and salience processing. In a randomized, double-blind, between-subject, design study 83 subjects received either intranasal OT or placebo. In Experiment 1, subjects performed a heartbeat detection task alone, while in Experiment 2 they did so while viewing both neutral and emotional face stimuli. Interoceptive accuracy and neural responses in interoceptive and salience networks were measured. In Experiment 1, OT had no significant influence on interoceptive accuracy or associated activity in the right anterior insula (AI) and dorsal anterior cingulate cortex. However, in Experiment 2 when face stimuli were also presented, OT decreased interoceptive accuracy and increased right AI activation and its functional connectivity with the left posterior insula (PI), with the latter both being negatively correlated with accuracy scores. The present study provides the first evidence that while OT does not influence processing of interoceptive cues per se it may switch attention away from them towards external salient social cues by enhancing right AI responses and its control over the PI. Thus OT may help regulate the interplay between interoceptive and external salience processing within the insula and could be of potential therapeutic benefit for emotional disorders. 

　　主讲人简介：

　　Shuxia Yao works as a Postdoctoral Fellow in the School of Life Science and Technology of UESTC now. He got his Bachelor degree in Southwest University and Ph.D. degree in UESTC. Dr. Yao is working in the field of social cognition and affective neuroscience. More specifically, he mainly focuses on investigating the neural mechanisms underlying human social behavior and affective processing and developing novel noninvasive therapeutic protocol in treating psychiatric disorders using oxytocin and the real-time fMRI neurofeedback training.

　　报告三：

　　主　题：The application of high performance computing in NGS data processing

　　主讲人：黄柯 生物医学工程流动站博士后

　　交流内容：

　　随着二代测序技术的大规模应用以及测序成本的迅速降低，基因测序数据量呈现出了爆发式的增长，对这些基因数据进行快速的预处理、分析、解读以及管理已经成为迫切需要解决的问题。基因测序数据的处理过程包括下机数据拆分、质量控制、序列比对、排序、去重、突变识别以及解读等多个步骤，涉及多个分析工具，效率低下，极为耗时。为了提高数据分析效率，高性能计算在基因数据的处理中具有迫切的需求。在本次报告中，我们将简要介绍高性能计算，特别是基于现场可编程逻辑门阵列（FPGA）的高性能计算，在基因数据处理中的应用。在本次报告中，我们将首先介绍基因数据分析需求等相关背景；其次，我们将讨论基因数据分析流程以及各个步骤分析的特点；最后，我们将介绍高性能计算如何为这些分析流程提供高效的解决方案。

　　主讲人简介：

　　黄柯2010年本科毕业于电子科技大学，并于2015年在清华大学获得博士学位。黄柯博士现在电子科技大学信息生物学中心进行博士后研究工作，他的研究兴趣包括生物信息学、高性能计算等。

　　报告四：

　　主　题：Neuroinformatic studies and its application to brain model

　　主讲人：Eduardo Gonzalez Moreira 生物医学工程流动站博士后

　　交流内容：

　　Research on neuroinformatic science is one of most promising fields to develop our knowledge about how human brain works. Since the higher temporal resolution showed by EEG/MEG signal compared to fMRI both techniques have been wide used on neurosciences. However, to understand brain functions the reconstruction of the sources localization and connectivity between then is required through inverse problem solutions. The inverse problem is an ill posed problem with not a unique solution. Therefore, prior assumptions must be defined in order to reduce and simplified the problem. On my research, a general framework for sequentially estimating the inverse solution in the frequency domain and its cross-spectra have been develop. It attempts for a generalization of the Variable Resolution Electromagnetic Tomography (VARETA) proposed by Valdes-Sosa and his coworkers (Valdes-Sosa, P. et al. 1996) by means of a penalized maximum a posteriori analysis of the MEG/EEG sources’ cross-spectra. This is a result of using the Expectation Maximization (EM) algorithm for Covariance Components Model (CCM) adapted to the complex case (Dempster, Laird and Rubin, 1977; Liu and Rubin, 1994) and general penalty model over the cross-spectral matrix. Henceforth we refer to this methodology as Expectation Maximization algorithm for Variable Resolution Electric Tomography (EM-VARETA).

　　主讲人简介：

　　Eduardo Gonzalez Moreira is a post-doc majored in neuroinformatic. He obtained bachelor’s degree in Telecommunication and Electronic Engineering in UESTC, then performed PhD research in biomedical engineering advised by Prof. Guang Li in Zhejiang University. His research interests include neurosciences, brain modeling, EEG/MEG/ECG/speech signal analysis, neuroinformatics tools like FieldTrip, Brainstorm, CBRAIN, LORIS, CIVET, Brainsuit and MatLab programing.

　　报告五：

　　主　题：On Ego Communication Networks

　　主讲人：王庆 生物医学工程流动站博士后

　　交流内容：

　　Ego Network (EN) is crucial in anthropology. It is composed of a centered ego, direct contacts namely alters, and the interactions among them. The widespread of mobile communication makes it cheaper and easier for people to communicate with each other. In fact, communication data is valuable and is becoming crucial in studying human behaviors. Can this trend always increase people’s ego network size? Does the layered ego network structure still exist? At the same time, how to interactively explore and visualize large volumes of data is also the key challenge for visual analytics.

　　The answers to the above questions are the 3 main sub-topics of this report and they are as follows: 1) Ego network modeling and its critical size; 2) Layered structure of ego networks. 3) A visual analytics system based on ego network perspective. In order to interacticely explore and visualize huge volumns of communication data, the researchers brought about the multi-scale interface, which is consistent with the idea of this paper, however this design did not support visualizing ENs. Moreover, the EN visualization systems did not show the detailed interactions between an ego and the alters. To interactively explore the communication data from ego network perspective, this thesis brings about a visual analytics system named egoPortray. The main contributions of this system are the interactive 3-scale views, namely, the macroscopic statistical view, which applies scatter layout and gives the information of data distribution and correlation; the mesoscopic group view, which uses matrix layout of glyph-based designs and enables comparing different egos; and the microscopic signature view, which utilizes the stacked layout and chord diagram design for visualizing the detailed interations between ego and alters. The anomalous user detection task is taken as the case study, and the results illustrate the servicebility of this system. In summary, ego network perspective pays more attention on ego itself rather than the whole network, this is consistent with the trend of personalized services, and it can be applied in other scenes and applications where network structure exists.

　　主讲人简介：

　　Qing Wang is a post-doc majored in biomedical engineering. He obtained bachelor’s degree in Electronic Information Science and Technology in CSU, then performed PhD research in Information and Communication Engineering advised by Prof. Hui Tian in BUPT and Prof. Tao Zhou in UESTC. His research interests include complex networks, communication networks, big data, information visualization, neuro networks, and brain connectivity.

　　四、主办单位：电子科技大学博士后管理办公室

　　　　承办单位：生命科学与技术学院

　　　　　　　　　电子科技大学博士后联谊会

                                                                                      　电子科技大学博士后管理办公室

　　　　　　　　　　　　　　　　　　　　　　　　2017年10月16日