Cognitive Science 0350 - Analysis of Neural Data

Our brains underlie our ability to perform complex tasks, but exactly how neural activity enables behavior is not well understood. To gain insight into this question, neuroscientists have developed a variety of technologies to record neural activity, however to turn these recorded signals into meaningful insights data analysis methods are needed. In this class students will learn how to analyze neural data by researching how information is coded in neural activity. In particular, the class will work together to analyze data sets that consist of neural spiking activity from different regions of macaque cortex with the aim of producing a publishable quality research paper. Methods that will be covered will range from classical univariate statistics such as ANOVAs, to multivariate machine-learning-based 'decoding' analyses, and students will learn how analyze data using Matlab. We might also examine data from other recording modalities including fMRI, EEG, and behavioral experiments, and students can potentially work on other neural data analysis research projects depending on their interests. Work for this class includes reading research papers, analyzing data in Matlab and R, and presenting on research findings. Prerequisites: prior experience with Statistics and computer programming.

Quantitative Skills Writing and Research Independent Work In this course, students are expected to spend at least six to eight hours a week of preparation and work outside of class time. This time includes reading, writing, programming and research.