Functional dependency between EEG oscillatory activity and pupil dilation

Background

Working memory engage the frontal lobes and the autonoumous nervous system. The activation of the frontal lobes can be seen as an increase in frontal midline theta (4-6 Hz) activity in the EEG signal. The activation of the autonomous nervous system can be seen as a dilation of the pupils. These two signals thus co-occur when humans use their working memory. The temporal dependency between the two signals is, however, poorly understood. We do not know, for example, to what extend we can predict the development of one signal from the other. A better understanding of this dependency may provide tools for diagnosing poor working memory function as seen in e.g. patients with dementia. It may also provide a useful tool for detecting extended working memory load and the fatigue that results therefrom.

Project Description and Required Background

In this project we will analyse measurements of brain activity (EEG and pupillometry) in humans during varying working memory load. The aim is to describe the temporal dependence of the two signals. Once a good description has been achieved we may proceed to analyse data from patients with brain disorders to investigate if cognitive impairments affect the dependence between frontal lobes and the autonomous nervous system.

This project is for 1-2 students that have a strong background in data analysis and machine learning, corresponding to at least 02450 Introduction to Machine Learning and Data Mining and preferably additional courses. Good programming skills in Python or Matlab are also necessary. You must also be interested in working collaboratively and proactively in a multidisciplinary research setting. Finally, you should be motivated, ambitious and interested in the opportunity for co-authorship on research publications. The scope of the project can be adapted to suit a bachelor’s or a master’s project.

References

Kosachenko AI, Kasanov D, Kotyusov AI, Pavlov YG. EEG and pupillometric signatures of working memory overload. Psychophysiology. 2023 Jun;60(6):e14275. doi: 10.1111/psyp.14275. Epub 2023 Feb 20. PMID: 36808118.

Pavlov YG, Kasanov D, Kosachenko AI, Kotyusov AI, Busch NA. Pupillometry and electroencephalography in the digit span task. Sci Data. 2022 Jun 17;9(1):325. doi: 10.1038/s41597-022-01414-2. PMID: 35715429; PMCID: PMC9206021.

Supervisors and Contact Details

ou will receive supervision from Associate Professor Tobias Andersen (DTU Compute)

Contact Tobias Andersen for further information.