International Conference on Mathematical Neuroscience

国际数学神经科学会议

• 批准号: 1642544
• 负责人: Zachary Kilpatrick
• 金额: $ 2万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1642544&HistoricalAwards=false
• 关键词: International; Conference; Mathematical; Neuroscience

The Third International Conference on Mathematical Neuroscience will be held in Boulder, Colorado from May 30 to June 2, 2017. The brain is one of the most complex biological structures, and we are still far from understanding how it functions. Understanding the computations performed by the brain will require significant contributions from multiple disciplines. Mathematical techniques have served an integral role in advancing neuroscience research for many decades. The International Conference on Mathematical Neuroscience will provide a forum for researchers to discuss current mathematical innovations emerging in neuroscience. The lectures will discuss new tools and methods for analyzing complex data sets and building rigorous mathematical models of brain function. A major aim of the conference is to attract and train young researchers on current methods in mathematical neuroscience. To fulfill this goal, there will be a tutorial component held the day before the main meeting. For broader impact, a collection of tutorial chapters will be solicited from presenters and published as a collection of lectures, and presentations will be made available on the conference website. The conference is in line with the present national BRAIN initiative, aimed at understanding the mechanisms underlying neural computation. The topics discussed during the tutorial sessions and main meeting are relevant to scientific disciplines beyond neuroscience: including systems biology, economics, and ecology.The meeting provides an opportunity for mathematicians to gain exposure to current research in neuroscience and communicate with neuroscientists. At the same time, it enables experimental neuroscientists to discuss current progress on understanding the dynamics and function of neural systems with mathematicians who develop new tools and methods to address present challenges. The meeting will begin with a tutorial day (May 30) featuring topics from three major areas in mathematical neuroscience: stochastic and nonlinear dynamics, information theory, and probability and statistics. The tutorials will introduce junior researchers to fundamental techniques used in contemporary mathematical neuroscience through lectures given by leaders in the field. The main conference (May 31 - June 2) will feature a broader set of topics in mathematical neuroscience, with a focus on the use of experimental data in modeling studies as well as using theory and models to explore hypotheses and design better experiments. A new challenge in modern neuroscience is to extract understandable patterns and features from high-dimensional data sets including neuronal activity, functional connectivity, and anatomy. To understand how the human brain functions and performs complex computations, improved methods for handling data are needed, together with rigorous mathematical models of neural systems. This conference will bring together leaders in applied mathematics and neuroscience that are developing new mathematical techniques for understanding high-dimensional data sets, building models to capture activity patterns and emergent computation, and working closely with experimentalists to address more targeted questions about brain function. Synergistic interactions between these topics will also be identified, to understand the full complexity of the nervous system. More information is available at the conference website: https://www.math.uh.edu/~zpkilpat/icmns2017.html.

第三届数学神经科学国际会议将于2017年5月30日至6月2日在科罗拉多州博尔德举行。大脑是最复杂的生物结构之一，我们还远未了解它的功能。理解大脑进行的计算将需要来自多个学科的重大贡献。几十年来，数学技术在推进神经科学研究中发挥了不可或缺的作用。国际数学神经科学会议将为研究人员提供一个讨论当前神经科学中出现的数学创新的论坛。讲座将讨论分析复杂数据集和建立大脑功能严格数学模型的新工具和方法。会议的一个主要目的是吸引和培训年轻的研究人员在数学神经科学的当前方法。为了实现这一目标，在主要会议的前一天会有一个辅导课。为了产生更广泛的影响，将向演讲者征集一套教程章节，并作为演讲集出版，并将在会议网站上提供演示文稿。这次会议与目前的国家BRAIN倡议一致，旨在了解神经计算的机制。在辅导课和主要会议期间讨论的主题与神经科学以外的科学学科相关：包括系统生物学，经济学和生态学。这次会议为数学家提供了一个接触当前神经科学研究并与神经科学家交流的机会。同时，它使实验神经科学家能够与开发新工具和方法来解决当前挑战的数学家讨论了解神经系统动力学和功能的最新进展。会议将以指导日（5月30日）开始，主题将来自数学神经科学的三个主要领域：随机与非线性动力学、信息论、概率与统计。这些教程将通过该领域的领导者的讲座，向初级研究人员介绍当代数学神经科学中使用的基本技术。主要会议（5月31日至6月2日）将以数学神经科学的广泛主题为特色，重点是在建模研究中使用实验数据，以及使用理论和模型来探索假设和设计更好的实验。现代神经科学面临的新挑战是从包括神经元活动、功能连接和解剖学在内的高维数据集中提取可理解的模式和特征。为了了解人类大脑的功能和执行复杂的计算，需要改进处理数据的方法，以及神经系统的严格数学模型。本次会议将汇集应用数学和神经科学领域的领导者，他们正在开发新的数学技术来理解高维数据集，建立模型来捕捉活动模式和紧急计算，并与实验家密切合作，以解决有关大脑功能的更有针对性的问题。这些主题之间的协同作用也将被确定，以了解神经系统的全部复杂性。更多信息请访问会议网站：https://www.math.uh.edu/~zpkilpat/icmns2017.html。