People
Ethan Meyers
Visiting Associate Professor of Statistics and Data Science
What do you do with Data Science?
Ethan Meyers’ research is at the intersection of Data Science and Neuroscience. In particular, he uses machine learning methods to extract information from high dimensional patterns of neural activity in order to understand how information is transformed as it flows through different brain regions and to understand how information is coded in neural activity. Through collaborations with experimental Neuroscientists, the goal of his work is to understand the neural algorithms that enable complex behaviors. Future directions include developing methods to that can extract insights from larger simultaneously recorded neural data sets, and to create software tools that make it easier for Neuroscientists to conduct reproducible data analyses. Relevant publications include: Meyers E (2013). The Neural Decoding Toolbox. Frontiers in Neuroinformatics, 7:8. Meyers E, Qi XL, Constantinidis C (2012). Incorporation of new information into prefrontal cortical activity after learning working memory tasks. Proceedings of the National Academy of Sciences, 109:4651-4656.