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

 描述（由申请人提供）：神经科学中真正的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，目前在博士前和博士后以及初级教师一级没有这种培训。我们提出了一个综合的方法来培养下一代的“神经”研究科学家从几个学科，包括生物学，心理学，医学，工程学，物理学和数学。具体来说，我们将建立在跨学科神经科学培训过去的成功，以提高研究生，博士后学者和初级教师在计算神经科学的不断增长的领域的研究专业知识。这一提高将通过在哥伦比亚的密苏里州校园举办为期2周的短期课程来实现，每年有24名参与者。 本课程将开始深入强调神经生理学的概念，通过自由软件（虚拟实验室）实验和一些湿实验室实验，使用“从生物学到模型，再回来”的方法。然后，它将提供在个人（练习）和两人组（项目）水平上的动手软件开发培训，使用软件包NEURON来模拟单个神经元和神经元电路。我们将重视参与者个人计算研究项目的发展，以增强他们将这些工具融入其研究生涯的信心和能力。由于神经科学的概念和软件开发往往是复杂的，我们将为参与者提供为期一年的课程的各个方面的跟进，并在此过程中还确定在这个新的跨学科领域的研究培训的障碍。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，在计算方法。我们的经验和研究结果将发表在科学和工程教育期刊上，并在适当的会议上发表。 我们的团队包括四个跨学科的教师，三个在内容的专业知识（1计算+2神经科学家）和一个在教育学和评估。过去8年来，两位教师（Nair和Schulz）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2年制和4年制大学教师举办年度夏季研讨会，重点是教授本科神经科学。我们的经验和研究结果将发表在科学和工程教育期刊上，并在适当的会议上发表。

 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.