Topology of emotion using Film fMRI

Background

How does the brain's functional organization change as we experience dynamic emotions, like the possible "happiness" or "anger" felt while watching a film? This project relies on the rich EmoFilM dataset, where 30 healthy adults watched 14 short films (like "Sintel") in an fMRI scanner. We will use Topological Data Analysis (TDA) to move beyond simple activation and study the evolving "shape" and topology of brain activity over time, linking it to continuous emotional ratings.

Project Description

This is a data-driven computational project, with deep theoretical aspects both at mathematical and neuroscientific level. The student will: 1) Learn and apply advanced TDA methods to the temporal fMRI data. 2) Analyze how the brain's network topology evolves moment-by-moment during film watching. 3) Work to link these topological signatures (e.g., the appearance/disappearance of loops or flares) with the continuous emotional states. The ultimate goal is to develop a new framework to cluster and predict emotions based on brain network topology.

Requirements

• Strong computational skills (Python preferred).
• A keen interest in Topological Data Analysis (TDA), data visualization, and the neuroscience of emotion.
• Previous experience with fMRI data is a plus, but not required.