Adam S Charles, Benjamin Falk, Nicholas Turner, Talmo D Pereira, Daniel Tward, Benjamin D Pedigo, Jaewon Chung, Randal Burns, Satrajit S Ghosh, Justus M Kebschull, William Silversmith, Joshua T Vogelstein
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引用次数: 10
Abstract
As acquiring bigger data becomes easier in experimental brain science, computational and statistical brain science must achieve similar advances to fully capitalize on these data. Tackling these problems will benefit from a more explicit and concerted effort to work together. Specifically, brain science can be further democratized by harnessing the power of community-driven tools, which both are built by and benefit from many different people with different backgrounds and expertise. This perspective can be applied across modalities and scales and enables collaborations across previously siloed communities.
期刊介绍:
The Annual Review of Neuroscience is a well-established and comprehensive journal in the field of neuroscience, with a rich history and a commitment to open access and scholarly communication. The journal has been in publication since 1978, providing a long-standing source of authoritative reviews in neuroscience.
The Annual Review of Neuroscience encompasses a wide range of topics within neuroscience, including but not limited to: Molecular and cellular neuroscience, Neurogenetics, Developmental neuroscience, Neural plasticity and repair, Systems neuroscience, Cognitive neuroscience, Behavioral neuroscience, Neurobiology of disease. Occasionally, the journal also features reviews on the history of neuroscience and ethical considerations within the field.