project-template

Fall 2015 group project

Team Member: Jon Jara, Juan Shishido, Wendy Xu

Make

In the data/ directory, you can make data to download and extract the data files and make validate to chech hashes.

In the code/ directory, there are several options:

• $ make behavioral_regression to run logstic regression on the behavorial data for each subject
• $ make pda_outliers for plotting outlier volumes for 2 subjects
• $ make pda_smooth to plot a brain image before and after smoothing
• $ make neural_regression to run the regression for all subjects, returning a gridplot for the beta coefficients
• $ make mvpa for our (experimental) MVPA analysis and plots on all 16 subjects

In the report/ directory, make to create the report PDF.

What is this?

Our group is working on the paper The Neural Basis of Loss Aversion in Decision-Making Under Risk, which investigates whether loss aversion reflects the engagement of distinct emotional processes when potential losses are considered and examines the neural systems that process decision utility. The paper can be found in our project

The study has 16 subjects (eight males and eight females with an average age of 22). For each of them, three trials of the mixed gambles task are performed and data sets of blood-oxygen-level-dependent are collected and contrasted. The study uses two modeling approaches for the primary whole-brain analyses---the parametric analysis and the matrix analysis. The paper can be found in Project-eta.

What we plan to do?

We plan to reproduce this study based on the whole-brain statistical analysis. We will look into the two modeling approaches that the authors used, and come up with our own approach based on what we have and what we can do.

Here are a few things we are doing:

1. Data cleaning, normalization

2. GLM

3. Correlate behavioral risk aversion vs neural risk aversion

4. Multi-voxel pattern analysis