Interdisciplinary Training in Computational Neuroscience for Researchers from Graduate and Medical Students to Junior Faculty

 描述(由申请者提供)：真正的神经科学综合和跨学科培训对于了解正常和病理状态下的大脑功能是必要的。由于多种原因，这种培训目前在博士后和初级教职人员层面上是不存在的。我们提出了一种综合的方法来培训来自生物学、心理学、医学、工程学、物理学和数学等多个学科的下一代“神经”研究科学家。具体地说，我们将在过去成功的基础上，通过跨学科神经科学培训，提高计算神经科学日益增长的领域的研究生、博士后学者和初级教师的研究专长。这一增强将通过在密苏里大学哥伦比亚校区举行的为期两周的短期课程实现，每年有24人参加。本课程将通过自由软件(虚拟实验室)实验和一些湿实验室实验来深入强调神经生理学概念，这些实验使用“从生物学到模型再回来”的方法。然后，它将在个人(练习)和两人小组(项目)水平上提供动手软件开发方面的培训，使用软件包Neuron对单个神经元和神经元电路进行建模。我们将重视参与者开发个人计算研究项目，以增强他们将这些工具整合到他们的研究生涯中的信心和能力。由于神经科学的概念和软件开发往往很复杂，我们将为学员提供为期一年的课程所有方面的跟踪，并在此过程中确定在这一新的跨学科领域进行研究培训的障碍。对于感兴趣的教师参与者，我们愿意访问他们的机构，以促进跨学科、研究项目和机构的互动，以计算方法。我们的经验和发现将发表在科学和工程教育期刊上，并在适当的会议上展示。我们的团队包括四名跨学科教员，三名在内容方面有专业知识(1名计算+2名神经学家)，1名在教育学和评估方面。其中两名教师(奈尔和舒尔茨)在过去的8年里一直在跨学科神经科学的研究和教学方面进行合作。在此期间，他们还为两年和四年制大学教师举办了一年一度的夏季研讨会，重点是教授本科生神经科学。我们的经验和发现将发表在科学和工程教育期刊上，并在适当的会议上展示。

 DESCRIPTION (provided by applicant): Truly integrative and interdisciplinary training in neuroscience is necessary to understand brain function in both normal and pathological states. And such training is not available presently at the pre- and post-doctoral and junior faculty level due to a multitude of reasons. We propose an integrated approach to train the next generation of `neuro' research scientists from several disciplines including biology, psychology, medicine, engineering, physics and mathematics. Specifically, we will build on past successes with training in interdisciplinary neuroscience, to enhance the research expertise of graduate students, post-doctoral scholars and junior faculty in the growing area of computational neuroscience. This enhancement will be achieved via a 2-week short course, with 24 participants/year, held on the University of Missouri campus in Columbia. The course will begin with an in-depth emphasis on neurophysiological concepts via free software (virtual lab) experiments and some wet-lab experiments using a "from biology to model and back again" approach. It will then provide training in hands-on software development both at the individual (exercises) and two-person group (projects) levels using the software package NEURON to model single neurons and circuits of neurons. We will place importance on the development of individual computational research projects by participants, to enhance their confidence and ability to integrate such tools into their research careers. Since neuroscience concepts and software development tend to be complex, we will provide follow up to participants for one year on all aspects of the course, and in the process also identify barriers to research training in thi new interdisciplinary area. For interested faculty participants, we are willing to visit their institutions to foster interaction across disciplines, research programs, and institutions, in computational approaches. Our experience and findings will be published in science and engineering education journals and presented at appropriate conferences. Our team includes four interdisciplinary faculty, three with expertise in content (1 computational + 2 neuroscientists) and one in pedagogy and evaluation. Two of the faculty (Nair and Schulz) have been collaborating in research in and teaching interdisciplinary neuroscience for the past 8 years. Over that period they have also been hosting annual summer workshops for 2 and 4-year college faculty with focus on teaching undergraduate neuroscience. Our experience and findings will be published in science and engineering education journals and presented at appropriate conferences.