Investigating higher-order signatures of the human brain using film fMRI.

Background

Characterizing brain dynamics is one of the biggest challenges in neuroscience. We recently developed a novel method to quantify the temporal higher-order effects present in multivariate time series (see Santoro et al., 2023 for more details). In other words, we distinguish in time the “important” information that is only contained in three or more independent variables but cannot be identified by pairs (i.e. two independent ones). The results are promising, and in this project, we propose to apply such methodology to naturalistic neuroscience, an emerging field leveraging film and other stimuli to understand the organisation of complex functions in the brain. We have at our disposal a rich dataset of emotional annotations to several short films and want to relate fluctuations of emotions over time to the dynamic higher-order signature of the brain.

Project description

Dependent on the student’s interest and motivation we create an individual project goal within the wider scope of the research. Indeed, also other brain datasets are available (fMRI/EEG of epileptic patients, or MEG on healthy subjects). All projects will be predominantly computational and aim to teach how to work with brain data, fundamentals of topology, higher-order temporal signals, and relate behavioural scores to the brain data.

Requirements    

  •  The applicants are expected to have knowledge of graph theory, while a basic knowledge of topology is a plus.
  • Good programming skills (Python-numpy). While python is preferred for the final outcome of this project, at least an elementary knowledge of Matlab (to read, understand, and translate code) is required.
  • Desired: Travel to Geneva 1 day per week.

Please contact Andrea Santoro (andrea.santoro@epfl.ch) with your CV and we’ll schedule a meeting to discuss your interests.

References

  • Morgenroth, E., Vilaclara, L., Muszynski, M., Gaviria, J., Vuilleumier, P., & Van De Ville, D. (2022). Probing Neurodynamics of Experienced Emotions-A Hitchhiker’s Guide to Film fMRI.
    1. Santoro, A., Battiston, F., Petri, G., & Amico, E. (2023). Higher-order organization of multivariate time series. Nature Physics, 1-9.
    2. Morgenroth, E., Vilaclara, L., Muszynski, M., Gaviria, J., Vuilleumier, P., & Van De Ville, D. (2022). Probing Neurodynamics of Experienced Emotions-A Hitchhiker’s Guide to Film fMRI.