PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Neuronal correlates of emotions in human-machine interaction
Benjamin Blankertz, Klaus-Robert Müller and Gabriel Curio
BMC Neuroscience Volume 10, Number (Suppl 1), 80, 2009.

Abstract

Previous neurophysiological studies of emotions have focused on the affective response in the emotional valence of a situation which are reactions to perception or memories [1]. Furthermore emotions have been investigated with regard to the trait of a subject, e.g. anger-out vs. anger control [2] and regarding motivational direction, e.g. approach vs. withdrawal [3]. Aiming at an enhancement of human-computer interaction by incorporating the emotional state of the user, a novel type of investigation is required. Neuronal correlates of emotional reactions which are related to interaction (e.g. annoyance due to one's own failure or an error of the machine; joy of success) have to be analyzed and methods for their detection in real-time need to be developed. In the present study we have acquired multi-channel EEG in 4 subjects while they were interacting with computer applications that have been specifically designed in order to provoke―in alternating phases―neural, positive or negative (stress, annoyance) emotions. In particular, a two-player variant of a 2-alternative forced-choice task had to be performed while in alternating periods either one or the other player was given ‘unfair’ preferential treatment by providing the task stimulus slightly in advance. This bias could not be noticed by the players.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:User Modelling for Computer Human Interaction
Brain Computer Interfaces
ID Code:6443
Deposited By:Stefan Haufe
Deposited On:08 March 2010