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

为从研究生、医学生到初级教师的研究人员提供计算神经科学跨学科培训

• 批准号: 9037332
• 负责人: Satish S Nair
• 金额: $ 19.91万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-23 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9037332
• 关键词: Active Learning; Address; Advertisements; Area; Back; Behavioral; Biological; Biology; Brain; Code; Cognitive Science; Complex; Computer Simulation; Computer software; Computers; Development; Dimensions; Discipline; Education; Educational process of instructing; Educational workshop; Electrical Engineering; Electronic Mail; Engineering; Evaluation; Exercise; Faculty; Fostering; Foundations; Individual; Institution; Instruction; Journals; Learning; Link; Mathematics; Medical Students; Medicine; Missouri; Modeling; Neurobiology; Neurons; Neurosciences; Participant; Persons; Physics; Physiology; Postdoctoral Fellow; Pre-Post Tests; Process; Property; Psychology; Publishing; Recruitment Activity; Reporting; Research; Research Personnel; Research Project Grants; Research Training; Science; Scientist; Site; Societies; Source; System; Systems Analysis; Testing; Training; Universities; Visit; Work; base; career; college; computational neuroscience; computer science; computerized tools; design; experience; follow-up; graduate student; improved; information processing; interest; mathematical model; meetings; neural circuit; neurophysiology; next generation; pre-doctoral; programs; public health relevance; relating to nervous system; research study; software development; success; symposium; tool; virtual; web site; working group

 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.

 描述（适用提供）：在神经科学中的真正综合和跨学科培训对于了解正常状态和病理状态的大脑功能是必要的。由于多种原因，在博士后和初级教师级别上没有这种培训。我们提出了一种综合方法，以培训来自几个学科的下一代“神经”研究科学家，包括生物学，心理学，医学，工程，物理和数学。具体来说，我们将通过跨学科神经科学的培训来建立过去的成功，以增强研究生，博士后学者和初级教师的研究专业知识。这一增强将通过为期2周的短期课程实现，每年有24名参与者在哥伦比亚大学的密苏里大学校园举行。该课程将从自由软件（虚拟实验室）实验和一些使用“从生物学到模型再返回”方法进行的湿lab实验的深入强调神经生理概念。然后，它将使用软件包神经元对单个（练习）和两人组（项目）级别进行动手软件开发的培训，以建模神经元的单个神经元和电路。我们将对参与者的个人计算研究项目的开发进行重视，以增强他们将这些工具整合到研究职业中的信心和能力。由于神经科学的概念和软件开发往往很复杂，因此我们将在课程的所有方面向参与者提供后续，并且在此过程中还确定了在新的跨学科领域的研究培训的障碍。对于有趣的教师，我们愿意访问他们的机构，以计算方法来促进跨学科，研究计划和机构的互动。我们的经验和发现将在科学和工程教育期刊上发表，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，三个具有内容专业知识（1个计算 + 2个神经科学家），另一个具有教学法和评估。在过去的8年中，两个教师（Nair和Schulz）一直在研究和教授跨学科神经科学的研究。在此期间，他们还曾为2年和4年的大学教职员工举办年度夏季研讨会，重点是教学本科神经科学。我们的经验和发现将在科学和工程教育期刊上发表，并在适当的会议上发表。