A description of my research project and goals

Project Description

The project is tentatively titled "Using Machine Learning to Detect Changes in Working Memory Load and Executive Functioning". The project will conduct a study where participants perform the n-back task of varying difficulty levels (n: 0-2) while a fNIRS device takes readings of the hemodynamics in areas relevant to working memory. Data taken from the study will be used to train a machine learning model; this model will classify data into those which were taken while performing the 0-back, 1-back, or 2-back task.

The final goal of the project is to develop a robust classifier for developing a robust classifier that can classify working memory demand at the 3 levels. This model will be implemented in future studies with more authentic tasks and it will try to classify the working memory demand, based on its training on the n-back data.

As decided by my mentor and I, the project should follow this schedule:

  1. Review literature to understand what is known in psychology and neuroscience about working memory demand and executive functioning, with a focus on the "n-back" task. Emphasis on understanding what the n-back task is and why it is used in studies of working memory and executive. Also emphasis on learning what neuroscientists have discovered about the brain activation associated with different levels of this task using fNIRS, fMRI and PET brain imaging. (Weeks 1-2)
  2. Write software to enable study participants to perform the task. It will need to integrate with all of the lab's experimental software and will log all the data from the user. (Weeks 2-4)
  3. Put together an experiment design and plan the experiment (Weeks 3-5)
  4. Recruit participants for study (Week 5)
  5. Run study (Weeks 6-7)
  6. Machine learning analysis (Weeks 7-10)