Data science and its future in large neuroscience collaborations

Manuel Schottdorf; Guoqiang Yu; Edgar Y Walker

doi:10.1016/j.neuron.2024.08.017

Data science and its future in large neuroscience collaborations

Neuron. 2024 Sep 25;112(18):3007-3012. doi: 10.1016/j.neuron.2024.08.017.

Authors

Manuel Schottdorf¹, Guoqiang Yu², Edgar Y Walker³

Affiliations

¹ Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA. Electronic address: [email protected].
² Department of Automation, Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China. Electronic address: [email protected].
³ Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA; Computational Neuroscience Center, University of Washington, Seattle, WA, USA. Electronic address: [email protected].

PMID: 39326391
PMCID: PMC11632705 (available on 2025-09-25)
DOI: 10.1016/j.neuron.2024.08.017

Abstract

Collaborative neuroscience requires systematic data management and analysis. How this is best done in practice remains unclear. Based on a survey across collaborative neuroscience projects, we document the current state of the art focusing on data integration, sharing, and researcher training. We propose best practices and list actions and policies to attain these goals.

MeSH terms

Cooperative Behavior*
Data Science* / trends
Humans
Information Dissemination
Neurosciences* / trends

Abstract

MeSH terms

Grants and funding