Training in Theoretical and Computational Neuroscience

理论和计算神经科学培训

基本信息

批准号：
8104229
负责人：
PETER SAGGAU
金额：
$ 13.89万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-07-01 至 2013-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8104229
关键词：
Training computational neuroscience

项目摘要

DESCRIPTION (provided by applicant): This interdisciplinary and multi-institutional training program seeks to support the education of future researchers who can apply the tools of Mathematics, Physics and Engineering to problems of Brain Research. Traditional Neuroscience uses reductionism to formulate hypotheses and tests them experimentally, while Theroretical and Computational Neuroscience builds on information Theory, Dynamical Systems Theory, and Computer Science to create theoretical models to be tested numerically. Collaborations of Neuroscientists, individually trained in experimental and computational approaches, are not unusual on the basis of experimental data. In extension of this, we advocate a synergistic use of both approaches to control the experiment itself, and propose to train pre- and postdoctoral students accordingly. Commensurate with our escalating knowledge of neural function, the complexity of experiments to analyze both healthy and diseased brain function is ever-increasing. In this situation, it is necessary to utilize the analytic and predictive nature of Theroretical and Computational Neuroscience not only between but rather during experiments. To meet this challenge, we will recruit both pre- post-doctoral students with previous training in Mathmatics, Physics and Engineering, and associate them with dual mentors of expertise in both theoretical and experimental Neuroscience. In addition to using theoretical tools, these students will be trained in state-of-the-art experimental methods, specifically those for complex multidimensional data acquisition, processing and visualization, as these are most prominent in Advanced Imaging Techniques. We have devised a curriculum to best educate these interdisciplinary students. For predoctoral students, training will be a well-balanced combination of classroom instruction and hands-on labs. For both pre- and postdoctoral students, there will be active journal clubs, mentor-guided research with an internship in the lab of the co-mentor, and conference presentations. Our training faculty of 23 is drawn from six institutions in and around the Texas Medical Center in Houston. All faculty members are also members of the Gulf Coast Consortium for Theoretical and Computational Neuroscience, which is part of the Gulf Coast Consortia for Interdisciplinary Bioscience Research and Training. Both our spectrum of represented disciplines and existing facilities makes this an ideal site for the proposed training program.

描述（由申请人提供）：该跨学科和多机构培训计划旨在支持未来的研究人员的教育，这些研究人员可以将数学，物理和工程工具应用于大脑研究问题。传统的神经科学使用还原论来制定假设并通过实验进行测试，而在信息理论，动力学系统理论和计算机科学上则建立了理论和计算神经科学，以创建用于数值测试的理论模型。在实验和计算方法的单独培训的神经科学家的协作并不罕见。为了扩展这一点，我们主张对两种方法来控制实验本身的协同使用，并提议相应地培训前和博士后学生。与我们对神经功能不断升级的知识相称，分析健康和患病脑功能的实验的复杂性越来越不断增加。在这种情况下，有必要不仅在实验中，而且在实验过程中，还要利用治疗和计算神经科学的分析性和预测性质。为了应对这一挑战，我们将招募博士后学生以前的数学，物理和工程学培训，并将他们与理论和实验性神经科学方面的双重指导者联系起来。除了使用理论工具外，这些学生还将接受最先进的实验方法，特别是用于复杂多维数据获取，处理和可视化的方法，因为这些方法在高级成像技术中最为突出。我们已经设计了一项课程，以最好地教育这些跨学科学生。对于专业的学生，培训将是课堂教学和动手实验室的均衡结合。对于学前和博士后学生，将有活跃的期刊俱乐部，在院长实习和会议演讲中实习的导师指导的研究。我们的23名培训学院来自休斯顿德克萨斯州医疗中心及其周围的六个机构。所有教职员工也是墨西哥湾沿岸的理论和计算神经科学联盟的成员，这是墨西哥湾沿岸跨学科生物科学研究和培训的一部分。我们的代表学科和现有设施的范围都使它成为拟议培训计划的理想场所。