Self, other, and we: mechanisms and dynamics of self-other integration in social observation and interaction

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Ivana Konvalinka


Associate Professor


Technical University of Denmark


DKK 4,797,459




Semper Ardens: Accelerate


Humans are remarkably capable of reading others’ minds, as well as changing their understanding of others through social interaction. We achieve this by incorporating our model of own mental and emotional states with models of others’. Through interaction with others, we also develop a better understanding and awareness of ourselves. However, there is a large variability in how successful we are in reading others, both across people and across different interactions, and the factors that underlie good versus poor understanding of others, and consequently, successful versus unsuccessful interactions, are still poorly understood. The primary hypothesis of this project is that the ability to read and interact with others is influenced by how well we merge the “self” with the “other”, while also being able to distinguish our own actions from those of others – and that this changing process can be measured in the interaction between our own and others’ neural and physiological signals. The aim is to use new experimental paradigms and computational models to measure the evolving dynamics of own and others’ bodily and brain signals between two and three interacting partners, as well as while reading others’ physical and emotional states in real-time.


The quality of our daily social interactions have a profound effect on our well-being, as well as personal development and productivity. However, interacting with others can be difficult, particularly in people who have difficulties monitoring their own actions or reading bodily signals of others, such as people with schizophrenia and autism, conditions that are characterized by impairments in social interaction. Unfortunately, the underlying mechanisms of these conditions are poorly understood. Meanwhile, functional outcomes in schizophrenia have been strongly linked to social cognition. A better understanding of the mechanisms that allow us to “put ourselves in others’ shoes”, while still distinguishing ourselves from others, would provide a crucial pointer to which processes may be impaired in people with social difficulties.


We will measure behaviour, brain activity, and heart rhythms of two or three people during interactive experiments, and when observing and being observed by others. We will apply coupled oscillator models to the data, and develop new computational approaches for measuring interactions between brain states of interacting individuals. The variability in the dynamic merging of self and other will be achieved in two ways: by perturbing the influence of one or two partners’ actions on the interaction outcome, and by varying differences in bodily self-awareness between interacting partners. We will measure how the balance in merging and distinguishing oneself and others influences interaction outcomes.

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