No abstract

Music is capable of inducing emotional arousal. While previous studies used brief musical excerpts to induce one specific emotion, the current study aimed to identify the physiological correlates of continuous changes in subjective emotional states while listening to a complete music piece. A total of 19 participants listened to the first movement of Ludwig van Beethoven's 5th symphony (duration: ~7.4 min), during which a continuous 76-channel EEG was recorded. In a second session, the subjects evaluated their emotional arousal during the listening. A fast fourier transform was performed and covariance maps of spectral power were computed in association with the subjective arousal ratings. Subjective arousal ratings had good inter-individual correlations. Covariance maps showed a right-frontal suppression of lower alpha-band activity during high arousal. The results indicate that music is a powerful arousal-modulating stimulus. The temporal dynamics of the piece are well suited for sequential analysis, and could be necessary in helping unfold the full emotional power of music.

Methodological approaches in which data on nonverbal behavior are collected usually involve interpretative methods in which raters must identify a set of defined categories of behavior. However, present knowledge about the qualitative aspects of head movement behavior calls for recording detailed transcriptions of behavior. These records are a prerequisite for investigating the function and meaning of head movement patterns. A method for directly collecting data on head movement behavior is introduced. Using small ultrasonic transducers, which are attached to various parts of an index person's body (head and shoulders), a microcomputer determines receiver-transducer distances. Three-dimensional positions are calculated by triangulation. These data are used for further calculations concerning the angular orientation of the head and the direction, size, and speed of head movements (in rotational, lateral, and sagittal dimensions). Further analyses determine relevant changes in movements, identify segments of movements, and classify the quantifications of movement patterns. The measured patterns of nonverbal behavior can be accurately related to features of verbal communication and other time-related variables (e.g., psychophysiological measures). To estimate the possible meanings of behavioral patterns, a heuristic is proposed that includes the situational context as the basis of interpretation. Movement Notation: "Indirect" Observation or "Direct" MeasurementConducting empirical research in the area of nonverbal behavior requires reliable methods of measuring the behavior evidenced by participants in a conversation. Both Wallbott (1980) and Rosenfeld (1982) distinguish between two different approaches to measuring nonverbal behavior. First, indirect, or observational, methods rely on subjectively applied operational definitions to identify parameters of nonverbal behavior. Since the researchers are usually the ones who do the observing, they are an integral part of the coding process, which is influenced by their interpretations of the nonverbal aspects of behavior. The researchers' ability to judge nonverbal behavior appropriately can be improved with the help of methods that ensure interpretations that are more objective. For instance, when one is videotaping nonverbal behavior in human social interaction, reference points (a coordinate system with adjustable x/y-axes) can be assigned to compare definable points of the body frame-by-frame and to code position changes in quantitative terms (see Wallbott, 1980).

Humans constantly predict their environment to facilitate mutual interaction. Predictions are connected with emotions as nonfatal penalties and rewards (for incorrect and correct expectancies, respectively) that result in negative and positive emotions. Music is an ideal stimulus to explore the underlying neurophysiological mechanisms of prediction related emotions. Using the high spatial and temporal resolution of stereotactic depth electrodes, we identified activation patterns and examined their distribution in the bilateral Amygdalae and the orbitofrontal cortex (OFC). We used music excerpts with either (a) a deceptive cadence (i.e., an unexpected chord/breach) or (b) a tonic chord inserted instead of a deceptive cadence (regular chord/no breach). These events were followed by a chord progression leading to and ending on the tonic after a breach (c) or (d) on a tonic after no breach. We computed the differences of the analytic amplitudes in the theta band at these time-points (i.e., events a–d) by using t tests. We found a significant difference between the unexpected chord (a) and the expected chord (b) in the analytic amplitude of the theta band in the left amygdala. Further we found a difference between the 2 resolutions (c and d) in the analytic amplitude of the theta band within the OFC. In conclusion, our case study supports the notion that the amygdala and the OFC are important for emotional responses to musical expectancy breaches as well as of their resolution.