Decoding Neural Representations of People and Personality Traits Using fMRI Multi-Voxel Pattern Analysis
|has title::Decoding Neural Representations of People and Personality Traits Using fMRI Multi-Voxel Pattern Analysis|
|Master:||project within::Computational Intelligence and Selforganisation|
|Student name:||student name::Andrei A. Rusu|
|Second reader:||has second reader::Demis Hassabis|
|Company:||has company::Vrije Universiteit Amsterdam|
Functional magnetic resonance imaging (fMRI) has been successfully used for various feats of “mind reading” by means of multi-voxel pattern analysis [4,5]. Representations of the meaning of written words and images of objects have been successfully decoded using data mining tools. However, it is not currently known how people represent personality traits of other persons when they think about them. Furthermore, the hypothesized connection between the way individuals view themselves and others has generated a long standing debate in psychology. In this study participants were instructed to imagine a number of fictitious people, as well as themselves, in a variety of situations. The aim of this study is to investigate whether such representations of people are consistent enough for accurate classification. This study also attempts to delineate the functional correlates of simulating personalities and their traits. The resulting imaging data will be interpreted using a multi-voxel pattern analysis methodology. Consistent features across conditions are expected, specifically within data from individual participants. It is an open question whether common features across participants do exist; this will be investigated with a group analysis. The findings could reveal insights into the structure and processing of neural representations for episodic memories with people as protagonists. The self condition could also provide valuable evidence into how self representations are related to those of other persons, with respect to their personality traits.
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