Neuroscience research has evolved to generate increasingly large and complex
experimental data sets, and advanced data science tools are taking on central roles in …

This review offers an accessible primer to social neuroscientists interested in neural
networks. It begins by providing an overview of key concepts in deep learning. It then …

Neuroimaging plays a crucial role in understanding brain structure and function, but the lack
of transparency, reproducibility, and reliability of findings is a significant obstacle for the field …

Inclusion at academic events is facing increased scrutiny as the communities these events
serve raise their expectations for who can practically attend. Active efforts in recent years to …

Reproducibility is a core requirement of modern scientific research. For computational
research, reproducibility means that code should produce the same results, even when run …

Abstract NeuroHackademy (https://neurohackademy. org) is a two-week event designed to
train early-career neuroscience researchers in data science methods and their application to …

The rise of large scientific collaborations in neuroscience requires systematic, scalable, and
reliable data management. How this is best done in practice remains an open question. To …

In this perspective, we highlight how emerging artificial intelligence tools are likely to impact
the experiences of researchers conducting computational fMRI analyses. While calls for the …

Programming is a useful skill for students, both in neuroscience research and in the broader
economy. Many instructors, however, may wonder how and when they should integrate it …