INCF Secretariat, Karolinska Institutet, Stockholm, 171 77, Sweden.
Department of Psychology and UVA School of Data Science, University of Virginia, Charlottesville, VA, 22903, USA.
Neuroinformatics. 2024 Oct;22(4):619-622. doi: 10.1007/s12021-024-09693-3.
Neurotechnology and big data are two rapidly advancing fields that have the potential to transform our understanding of the brain and its functions. Advancements in neurotechnology have enabled researchers to investigate the function of the brain at unprecedented levels of granularity at the functional, molecular, and anatomical levels. Thus, resulting in the collection of not only more data, but also larger datasets. To fully harness the potential of big data and advancements in neurotechnology to improve our understanding of the nervous system, there is a need to train a new generation of neuroscientists capable of not only domain expertise, but also the computational and data science skills required to interrogate and integrate big data. Importantly, neuroinformatics is the subdiscipline of neuroscience devoted to the development of neuroscience data and knowledge bases together with computational models and analytical tools for sharing, integration and analysis of experimental data, and advancement of theories about the nervous system function. While there are only a few formal training programs in neuroinformatics, and since neuroinformatics is rarely incorporated into traditional neuroscience training programs, the neuroinformatics community has attempted to bridge the gap between the traditional neuroscience education programs and the needs of the next generation of neuroscience researchers through community initiatives and workshops. Thus, the purpose of this special collection is to highlight several such community efforts which span from in-person workshops to large-scale, global virtual training consortiums and from training students to training-the-trainers.
神经技术和大数据是两个快速发展的领域，有潜力改变我们对大脑及其功能的理解。神经技术的进步使研究人员能够以前所未有的粒度水平研究大脑的功能，包括功能、分子和解剖学水平。因此，不仅收集了更多的数据，而且还收集了更大的数据集。为了充分利用大数据和神经技术的进步来提高我们对神经系统的理解，需要培养新一代的神经科学家，他们不仅要有专业知识，还要有计算和数据科学技能，以便对大数据进行查询和整合。重要的是，神经信息学是神经科学的一个分支，致力于开发神经科学数据和知识库，以及用于共享、整合和分析实验数据的计算模型和分析工具，推进关于神经系统功能的理论。虽然神经信息学方面只有少数几个正式的培训项目，而且由于神经信息学很少被纳入传统的神经科学培训项目中，因此神经信息学社区一直试图通过社区举措和研讨会来弥合传统神经科学教育项目与下一代神经科学研究人员需求之间的差距。因此，本特刊的目的是重点介绍几个这样的社区努力，包括从实地研讨会到大规模的全球虚拟培训联盟，以及从培训学生到培训培训师。
