Training a new generation of computational neuroscientists bridging neurobiology

计算神经科学(TPCN)培训计划将支持综合本科生和 在纽约大学接受计算神经科学研究生培训。该节目将由 神经科学中心(CNS)，心理学、数学、 和计算机科学，以及医学院神经科学研究所。TPCN将非常适合 纽约大学的独特优势和最新发展：(1)纽约大学是少数几所拥有大量 计算神经学家。自1994年以来，纽约大学一直有一个斯隆-斯沃茨理论神经科学中心。 仅在过去的三年里，纽约大学就聘请了三名计算神经学家。(2)CNS成立了一个 早在1992年就主修神经科学，因此在本科生中有很长的记录 在教育方面，它在本学年现在有136名学生。(3)CNS近期招聘教师，心理学， 医学院极大地扩展了我们在神经科学领域的教学和研究能力 与精神障碍相关的认知功能及其损害。(3)纽约大学正在进行合并 在两个历史上分离的神经科学研究生项目(在CNS和医学院)中，这 培训拨款将确保在神经科学中不可或缺的计算建模将 在综合研究生项目中处于领先地位。(4)纽约大学是人工智能的主要中心， 数据科学，与Facebook的人工智能中心和西蒙斯数据分析中心有密切联系。我们的培训 教职员工和这些联系将为我们的学生提供大量获得机器学习的机会 数据分析技术和学习类似大脑的人工智能算法。 拟议的培训方案将支持计算方面的本科生和研究生的连贯培训。 纽约大学神经科学专业。它将有几个独特的特点：(1)创新的指导方法：例如， (A)研究生学员将指导本科生学员；。(B)教职员工将在 学术实践；(C)在外部发言者的研讨会后将进行尸检。(2)计算性 精神病学：我们建议新的课程和研究机会，这些课程和研究机会是专门为联系认知而设计的 神经回路的功能和神经生物学。我们建议在新兴领域开展创新教育 计算精神病学，将理论和电路建模引入心理健康的临床研究。(3)宽阔 准备工作：我们的目标是为受训人员做好准备，不仅在学术界，而且在医疗和工业领域 研究。为了实现这一目标，我们将利用我们在机器学习和数据科学方面的优势来扩大 计算神经科学培训。计划总监具有互补的优势，并将拥有 在项目中扮演互补的角色。王将指导研究生实习生，并专注于培训 计算神经科学和计算精神病学的机械/电路层面。马会会 指导本科生，专注于计算/行为方面。

The Training Program in Computational Neuroscience (TPCN) will support integrated undergraduate and graduate training in computational neuroscience at New York University. The program will be hosted by the Center for Neural Science (CNS), with participation of faculty in the Departments of Psychology, Mathematics, and Computer Science, and the Institute of Neuroscience at the School of Medicine. The TPCN will fit well with NYU’s unique strengths and recent developments: (1) NYU is one of a few universities with a critical mass of computational neuroscientists. NYU has had a Sloan-Swartz Center for Theoretical Neuroscience since 1994. In the past three years alone, NYU has hired three computational neuroscientists. (2) CNS established an undergraduate major in neuroscience as early as 1992, and thus has a long track record in undergraduate education, it now has 136 students in the current academic year. (3) Recent faculty hiring in CNS, Psychology, and the School of Medicine has greatly expanded our teaching and research capabilities in the neuroscience of cognitive functions and their impairments associated with mental disorders. (3) As NYU is undertaking a merge of two historically separated neuroscience graduate programs (at CNS and the School of Medicine), this training grant will ensure that computational modeling, which has become indispensible in neuroscience, will be front-and-center in the integrated graduate program. (4) NYU is a major center of Artificial Intelligence and Data Science, with close links to Facebook’s AI Center and the Simons Center for Data Analysis. Our training faculty together with these connections will give our students ample opportunities to acquire machine learning techniques for data analysis and learn about brain-like AI algorithms. The proposed training program will support coherent undergraduate and graduate training in computational neuroscience at NYU. It will have several unique features: (1) Innovative mentorship methods: For example, (a) graduate trainees will mentor undergraduate trainees, (b) faculty will explicitly discuss human factors in academic practice; (c) there will be post-mortems after seminars by outside speakers. (2) Computational psychiatry: We propose new courses and research opportunities that are designed specifically to link cognitive function and the neurobiology of neural circuits. We propose innovative education in the nascent field of Computational Psychiatry, to bring theory and circuit modeling to clinical research in mental health. (3) Broad preparation: We aim to prepare trainees for jobs not only in academia, but also in medical and industry research. To achieve this, we will utilize our strength in machine learning and data science to broaden computational neuroscience training. The Program Directors have complementary strengths and will have complementary roles in the program. Wang will supervise graduate trainees and focus on training in mechanistic/circuit-level side of computational neuroscience as well as computational psychiatry. Ma will supervise undergraduate trainees and focus on the computational/behavioral side.