+DS IPLE: Some Examples of Machine Learning in Neuroscience

Like many fields, neuroscience is experiencing a data deluge. Machine learning techniques are being used to learn better biomarkers, make sense of the brain, and automate tasks. I will introduce some of the methodology and ideas being worked on within this research area, including domain adaptation and automatic behavior extraction from video. These techniques, when harnessed correctly, can help improve the quality of information extracted from collected data and accelerate science; however, interpretation and validation pitfalls can derail researchers from making proper conclusions. I'll introduce how model validation can vary depending on the scientific hypothesis.

This session is part of the Duke+DataScience (+DS) program in-person learning experiences (IPLEs). To learn more, please visit https://plus.datascience.duke.edu/