Ryan M Stolier
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I am a post-doctoral researcher in the Department of Psychology at Columbia University, where I work with Dr. Kevin Ochsner in the SCAN Lab. My research bridges methods of psychology and neuroscience to study how we think about other people. I ask these questions broadly, exploring how our impressions of others take into account their behaviors, reputation, appearance, and social category memberships. I am particularly interested in how social conceptual knowledge fundamentally structures our interpretations of others. Major themes of my research are person perception, face perception, stereotyping and prejudice, perceptions of and within relationships and social networks, computational modeling, and multivariate analysis of functional magnetic resonance imaging.
Read more about my research here.
See my published work and research tools below. As well, visit the SCAN Lab site.
Selected PublicationsStolier, R. M., Hehman, E., & Freeman, J. B. (2020). Trait knowledge forms a common structure across social cognition. Nature Human Behaviour. [Preprint] [OSF] [Supplementary Materials]
Stolier, R. M., Hehman, E., Keller, M. D., Walker, M., & Freeman, J. B. (2018). The conceptual structure of face impressions. Proceedings of the National Academy of Sciences of the United States of America, 115(37) 9210-9215. [Preprint] [OSF] [Supplementary Materials]
Stolier, R. M., Hehman, E., & Freeman, J. B. (2018). A dynamic structure of social trait space. Trends in Cognitive Sciences, 22(3), 197-200.
Stolier, R. M. & Freeman, J. B. (2017). A neural mechanism of social categorization. Journal of Neuroscience, 37(23), 5711-5721.
Stolier, R. M. & Freeman, J. B. (2016). Neural pattern similarity reveals the inherent intersection of social categories. Nature Neuroscience, 19(6), 795-797. [Supplementary Materials] [News & Views: 'Facing up to stereotypes' by Hebart M. N. & Baker C. I.]
Click here for a full list of publications.
Face Stimulus & Tool CollectionThe Face Stimulus & Tool Collection is a concise, regularly updated, and curated list of face stimulus databases and editing tools (e.g., morphing).
PyMVPAwPyMVPAw is a wrapper for PyMVPA, a Python package for multi-variate pattern analyses of neuroimaging data. In PyMVPAw, many of PyMVPA's pattern analysis tools are available in single function commands. As well, PyMVPAw includes many additional tools and analyses (further detailed in its github home, wiki, and Jupyter notebook tutorials).
To learn more and/or install, visit the PyMVPAw github home.
afniGLMprepafniGLMprep is a Python package which prepares and runs GLMs on neuroimaging data stored in the BIDS format. In a single line of code, afniGLMprep creates stimulus timeseries and GLM scripts.
To learn more and/or install, visit the afniGLMprep github home.