Computing and the brain: training the next generation of neuroscientists

描述（由申请人提供）：我们提出了一个本科生和研究生（NRSA和非NRSA）在计算神经科学的培训计划。我们的校园在这一领域有着丰富的历史和广泛的教学和研究，教师导师分布在许多部门和学校，包括生理学和生物物理学，生物结构，计算机科学与工程，应用数学，生物学，心理学和生物工程。对本科生和研究生教育和研究的支持将促进这一领域的持续发展，增强理论家和实验家之间的互动，扩大和整合神经科学定量方法的课程，增强本科生和研究生之间的互动，增强本科生研究的机会，并吸引整个校园的社区，以加强我们已经很好的跨学科交流和合作。 我们的本科培训计划将建立一个为期两年的计算神经科学序列，每年最多有12名来自神经生物学或计算专业（物理，计算机科学与工程，应用和计算数学）的学员。在秋季学期，学生参加一系列研讨会，向他们介绍教师的研究。学员将参加一个共同的核心课程，包括实验室神经生物学课程和定量课程，其中实验室部分通过并行计算课程进行增强。在个性化课程中选择额外的选修课由指导委员会指导。所有学生将完成至少1个，最好是4个季度的指导实验室研究。 我们的研究生培训计划将支持最多6名学生从神经生物学和行为跨部门计划或部门研究生课程加入。学生将在第一年结束时申请培训补助金支持，并开展由两门神经生物学课程和两门定量课程组成的核心课程。将与指导委员会协商设计个性化课程，包括从计算神经科学、数学、计算机科学和物理学课程中选择的选修课。一个双周期刊俱乐部将调查数学和系统神经科学论文，并允许学生研究报告。学生将有机会在本科神经生物学课程的新计算课程教学。 所有学员将参加每月一次的研讨会，并在年度务虚会上介绍他们的研究。 该计划将由生理学和生物物理学副教授Adrienne Fairhall以及生物学教授Bill Moody教授领导团队指导，本科神经生物学课程主任;耳鼻喉科和生理学与生物物理学副教授大卫佩克尔; Fred Rieke教授，生理学和生物物理学，生理学和生物物理学研究生课程的前主任和助理教授Eric Shea-Brown，应用数学 公共卫生相关性：该培训补助金旨在培训年轻的神经科学家使用数学和计算工具来理解大脑和神经回路的高度复杂的动态处理能力。它还将使物理，数学和计算机科学的学生更深入地了解大脑的生物学，以便设计出更合适的理论模型。推进神经科学的这种合作方法将有助于我们干预大脑病理，并最终创造出与神经系统功能相结合的辅助技术。

DESCRIPTION (provided by applicant): We propose an undergraduate and graduate (NRSA and non-NRSA) training program in computational neuroscience. Our campus has a rich history and an enormous breadth of active teaching and research in this area, with faculty mentors distributed through many departments and schools, including Physiology and Biophysics, Biological Structure, Computer Science and Engineering, Applied Math, Biology, Psychology and Bioengineering. Support for undergraduate and graduate education and research will foster the ongoing growth of this area, enhance interaction between theorists and experimentalists, expand and integrate coursework in quantitative approaches in neuroscience, enhance interactions between undergraduate and graduate students, enhance opportunities for undergraduate research and draw together the community across campus to strengthen our already excellent interdisciplinary exchange and collaboration. Our undergraduate training program will establish a two-year sequence in computational neuroscience, with entry points for up to 12 trainees yearly either from neurobiology or from a computational major (Physics, Computer Science and Engineering, Applied and Computational Mathematics). In fall quarter students attend a series of seminars to introduce them to faculty research. Trainees will take a common core curriculum including both laboratory neurobiology courses and quantitative courses, where the laboratory section is enhanced with a parallel computational course. Choice of additional electives in an individualized curriculum is guided by a mentoring committee. All students will complete at least 1 and preferably 4 quarters of mentored laboratory research. Our graduate training program will support up to 6 students joining either from the Neurobiology & Behavior interdepartmental program or from departmental graduate programs. Students will apply for training grant support at the end of the first year and carry out a core curriculum consisting of two neurobiology courses and two quantitative courses. Individually tailored curricula including electives selected from offerings in computational neuroscience, mathematics, computer science and physics will be devised in consultation with a mentoring committee. A biweekly journal club will survey mathematical and systems neuroscience papers and allow student research presentations. Students will have teaching opportunities in new computational courses in the undergraduate Neurobiology program. All trainees will attend a monthly seminar and present their research at an annual retreat. The program will be directed by Assoc. Prof. Adrienne Fairhall, Physiology and Biophysics, and a leadership team of Prof. Bill Moody, Professor of Biology, Director of the Undergraduate Neurobiology Program; Assoc. Prof. David Perkel, Otolaryngology and Physiology and Biophysics; Prof. Fred Rieke, Physiology and Biophysics, former Director of the Physiology and Biophysics graduate program and Asst. Prof. Eric Shea-Brown, Applied Mathematics. PUBLIC HEALTH RELEVANCE: This training grant aims to train young neuroscientists to use mathematical and computational tools to understand the highly complex, dynamical processing capabilities of the brain and neural circuitry. It will also give students in physics, mathematics and computer science deeper insight into the biology of the brain in order to devise more appropriate theoretical models. Advancing this collaborative approach to neuroscience will help us to intervene in brain pathologies and ultimately to create assistive technologies that integrate with nervous system function.