Quantitative Psychology and Individual Dierences
Faculty of Psychology and Educational Sciences
KU Leuven
Phone: +32 16 30 10 45
Email Tim Loossens
Project
Statistical modelling of emotion dynamics
This research project aims to acquire a thorough understanding of the dynamics driving emotions. To accomplish this, a stochastic non{linear dynamical model is proposed, based on Ising{type networks that help relate basic neurophysiological principles to complex behaviour. In particular, the model aims to describe a person’s non{linear emotional response to the most important affective features of a stimulus, such as pleasantness and unpleasantness.
The research consists of three important steps: studying the mathematical properties of the
model, developing a methodology for statistical interference, and programming a user-friendly software which will allow researchers to
fit the model to their data. In a
first instance, the mathematical tools have to be developed to analyse the model and its properties. This should provide insight in the equilibrium and the non-equilibrium dynamics of the system, allowing a deeper understanding of the response mechanism of a person’s emotional regulatory network. Moreover, this analysis should help simplify the computations required for statistical inference. Creating a methodology for statistical inference is important in order to be able to test model against noisy real-life data. The statistical inference methodology should also deal with a number of other challenges, such as individual differences. Finally, in order for researchers to use the model, a user-friendly and performant software has to be developed.
The model will be tested on a number of prototypical data sets which have been collected in
the lab as well as in daily life. They include both healthy individuals and persons with an
emotional disorder. The model should be able capture certain characteristic features related to the emotional well{being of individuals and their response to stimuli. Furthermore, structural differences between the emotional regulatory networks of healthy individuals and individuals with a disorder are expected.
Supervisors
Francis Tuerlinckx & Stijn Verdonk
Financed by
Period
2016 – 2021