Trends in self-citation rates in neuroscience literature by Prof Dustin Scheinost & Matt Rosenblatt

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About the speakers

Dustin Scheinost earned his PhD in biomedical engineering from Yale University and is currently an Assistant Professor in the Department of Radiology & Biomedical Imaging at Yale School of Medicine, where he leads the Multimodal Imaging, Neuroinformatics, and Data Science (MINDS) Lab. Dustin’s research interests include functional connectivity, predictive modeling, software development (BioImage Suite), and fetal-infant fMRI. In addition, Dustin is a founding member of the Fetal, Infant, & Toddler Neuroimaging Group (FIT’NG).

Matt Rosenblatt received his BS in bioengineering from the University of Pittsburgh, and he is currently a biomedical engineering graduate student in the Multimodal Imaging, Neuroinformatics, and Data Science (MINDS) Lab at Yale University. Matt’s main research focus is evaluating and improving the trustworthiness of machine learning for neuroimaging.

About the talk

In this talk, we will summarize our recent bioRxiv preprint “Trends in self-citation rates in neuroscience literature”. Since the downstream effects of self-citations include increased visibility and citations from others, it is crucial to establish baseline self-citation rates in neuroscience literature. We will not only discuss baseline self-citation rates, but also differences in self-citation by year, seniority, country, and gender. Finally, we will highlight a Python tool where authors can evaluate their own self-citation rates.

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