|Title||A Data Science approach to analyzing neural data|
|Publication Type||Conference Paper|
|Year of Publication||2017|
|Conference Name||Joint Statistical Meetings|
Data Science is a field that uses computational tools to extract insight from large noisy data sets. While Data Science borrows heavily from Statistics (and one could reasonably argue that they are the same field), the culture, approach, and tools used by Data Scientists often differ from those that are more commonly used by Statisticians (Breiman 2001, Donoho, 2015). Additionally, while Data Science approaches are most widely used in industry, scientists in academic fields usually use classical statistical approaches. In this paper we illustrate how a Data Science approach can give useful insights into scientific questions by describing our work using machine learning methods to analyzing neural data. We also outline additional ways in which Neuroscience and other fields could benefit from incorporating more Data Science perspectives into how problems are approached, and areas where Data Science approaches could benefit from more rigorous Statistical methods.
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