Connecting the dots in neuroscience research: The future of evidence synthesis

Kaitlyn Hair*, María Arroyo Araujo*, Sofija Vojvodic*, Maria Economou*, Charis Wong*, Francesca Tinsdeall*, Sean Smith*, Torsten Rackoll*, Emily S Sena*, Sarah K McCann*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Making progress in neuroscience research involves learning from existing data. In this perspective piece, we explore the potential of a data-driven evidence ecosystem to connect all primary data streams, and synthesis efforts to inform evidence-based research and translational success from bench to bedside. To enable this transformation, we set out how we can produce evidence designed with evidence curation in mind. All data should be findable, understandable, and easily synthesisable, using a combination of human and machine effort. This will require shifts in research culture and tailored infrastructure to support rapid dissemination, data sharing, and transparency. We also discuss improvements in the way we can synthesise evidence to better inform primary research, including the potential of emerging technologies, big-data approaches, and breaking down research silos. Through a case study in stroke research, one of the most well-established areas for synthesis efforts, we demonstrate the progress in implementing elements of this ecosystem, with an emphasis on the need for coordinated efforts between laboratory researchers and synthesists.

Original languageEnglish
Pages (from-to)115047
JournalExperimental neurology
Early online date5 Nov 2024
DOIs
Publication statusE-pub ahead of print - 5 Nov 2024

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