Neuronal correlates of emotions in human-machine interaction
Benjamin Blankertz, Klaus-Robert Müller and Gabriel Curio
Number (Suppl 1),
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 . Furthermore emotions have been investigated with
regard to the trait of a subject, e.g. anger-out vs. anger control  and regarding motivational direction, e.g.
approach vs. withdrawal . 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.