Abstract

Emotions play a critical role in rational and intelligent behavior; a better fundamental knowledge of them is indispensable for understanding higher order brain function. We propose a non-invasive brain-computer interface (BCI) system to feedback a person’s affective state such that a closed-loop interaction between the participant’s brain responses and the musical stimuli is established. We realized this concept technically in a functional prototype of an algorithm that generates continuous and controllable patterns of synthesized affective music in real-time, which is embedded within a BCI architecture. We evaluated our concept in two separate studies. In the first study, we tested the efficacy of our music algorithm by measuring subjective affective responses from 11 participants. In a second pilot study, the algorithm was embedded in a real-time BCI architecture to investigate affective closed-loop interactions in 5 participants. Preliminary results suggested that participants were able to intentionally modulate the musical feedback by self-inducing emotions (e.g., by recalling memories), suggesting that the system was able not only to capture the listener’s current affective state in real-time, but also potentially provide a tool for listeners to mediate their own emotions by interacting with music. The proposed concept offers a tool to study emotions in the loop, promising to cast a complementary light on emotion-related brain research, particularly in terms of clarifying the interactive, spatio-temporal dynamics underlying affective processing in the brain.

Highlights

  • Research on emotion has a longstanding tradition that has garnered interest from a variety of scientific fields, such as psychology, sociology, and neuroscience (e.g., [1,2,3,4])

  • Scientists know that there is at least some degree of independence between emotion processing and attentional mechanisms, that the amygdala is crucial in forming conditioned fear responses, and that evoking certain emotional states biases decision making processes [5]

  • The number of notes played within one bar was randomly set based on a probability determined relative to the arousal input parameter according to Eq 2

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Summary

Introduction

Research on emotion has a longstanding tradition that has garnered interest from a variety of scientific fields, such as psychology, sociology, and neuroscience (e.g., [1,2,3,4]). Scientists know that there is at least some degree of independence between emotion processing and attentional mechanisms, that the amygdala is crucial in forming conditioned fear responses, and that evoking certain emotional states biases decision making processes [5]. These findings have shed light on the cognitive, neural, and social factors at play in emotion.

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