Editorial: Advances in computer science and their impact on data acquisition and analysis in neuroscience

Abstract

'Shu-Ching Chen'] Overview Unlike other fields of biology, neuroscience and the study of the nervous system across a range of species were characterized early on by the need for the analysis of highly complex data sets. In seminal areas of neuroscience, such as electrophysiology, neuroimaging, and neurophysiology, progress in both data acquisition and data analysis was limited by the capabilities of hardware and software solutions available to researchers. At the same time, critical advances in computer science and software engineering not only led to fundamentally important new discoveries in neuroscience but were often also driven by challenges resulting from paradigm-shifting discoveries in neuroscience, such as the 1981 Nobel Prize in Physiology or Medicine. Similar synergistic relationships between computer science and neuroscience also exist in medical fields related to neuroscience, such as neurology, ophthalmology, and psychiatry, where progress in the development of novel therapeutics and diagnostics depends on the ability to more effectively acquire and analyze data, such as the 2003 Nobel Prize in Physiology or Medicine. The seminal importance of many novel developments in computer science generates a broad impact on basic science approaches in neuroscience, often subsequently or in parallel advancing toward clinical implementation. Novel approaches in the areas of artificial intelligence and machine learning, for example, have found early sites of implementation in neuroscience and related medical fields. At the same time, developments in neuroscience, such as international collaborative efforts in connectomics and brain-computer interface research, provide new concepts and prompt new challenges for computer scientists in fundamental and applied research fields. The Research Topic, [Advances in computer science and their impact on data acquisition and analysis in neuroscience](), brought together experts in both areas, computer science and neuroscience, with interdisciplinary teams presenting innovative approaches and synthesizing insights toward the synergistic advancement of their respective fields.