Harmony Wants to Sit in the Front: Different Brain Responses to Violations in Chord Progressions
نویسندگان
چکیده
Deviations from auditory regularities elicit electric potentials distributed over the frontal regions of the scalp. The mismatch negativity (MMN) is elicited by change in repetitive auditory input, whereas the early right anterior negativity (ERAN) is elicited when sounds deviate from a hierarchically organized musical regularity. In this study we wished to disentangle the functional roles of these two brain processes associated with the detection of sequential vs. hierarchical musical violations by studying the localization of their neural generators. Subjects listened to musical cadences constituted by seven chords, each containing either harmonically congruous chords, harmonically incongruous chords (Neapolitan subdominant), or harmonically congruous but mistuned chords (5 raised 50 cents). Electroencephalography (EEG) was recorded and source analysis was performed. Incongruous chords violating the rules of harmony elicited a bilateral ERAN, whereas mistuned chords within chord sequences elicited a right-lateralized MMN. We found that the dominant neural sources for the ERAN were localized in Broca’s area and its right homologue, whereas the MMN generators were localized in auditory cortex. These findings demonstrate the predominant role of the auditory cortices in detecting sequential scale regularities and of the prefrontal cortex in parsing hierarchical regularities in music. I. SOUND & MUSIC PROCESSING A. Regularity vs Harmony Using Magnetoencephalography (MEG), Maess et al (2001) showed that Western musical harmony (or “syntax” as they call it) is processed in Broca’s area and its right hemispheric homologue. Since then, the processing of musical harmony has been a very important but also quite controversial subject of study. To talk about music processing, first we must understand how the human brain processes sequences of sounds. Regularities in language sounds and other domains are extracted and organized by the brain. These regularities may be the repetition of one feature of the sounds such as e.g. the pitch, or rules of succession of particular sound features e.g., the higher the pitch, the louder the sound intensity is expected to be (Paavilainen et al. 2001). The extraction of sound regularities allows for adaptation to the environment and detection of sound deviations that may be important for survival (Pincze et al. 2002; Bendixen et al. 2007). This is true for humans as well as for animals but, unlike animals, humans can also form hierarchic structures adopted for aesthetic purposes (e.g., (Koelsch and Sammler 2008)), like in visual art and music. A way to study auditory regularities is by using the mismatch negativity (MMN), a component of the event-related potential (Näätänen 1995; Picton et al. 2000). The MMN is an early frontocentral negative potential peaking at around 150-250 ms, which is elicited by deviant stimuli randomly introduced in a train of repetitive stimuli. It occurs automatically, i.e. without any attentional effort or even awareness. The cortical main sources of the MMN are in the auditory cortex (the supratemporal plane), sometimes additional sources in the right inferior frontal gyrus (Opitz et al. 2002), and inferior parietal lobule (Park et al. 2002). The reason for this wide localization of the MMN may be that these cortical sources detect the auditory change, and assess whether it is salient or novel enough to trigger attention (Schonwiesner et al. 2007). The MMN may reflect the automatic formation of brief neural models of regularities in the auditory environment (Winkler et al. 1996). However, the extent to which auditory regularities can be encoded by the auditory-cortex MMN neurons have not yet been fully determined, and to investigate this question we need to further study musical regularities, characterized by different levels of structural complexity. B. More than a word about Music
منابع مشابه
Representation of harmony rules in the human brain: further evidence from event-related potentials.
In Western tonal music, the rules of harmony determine the order and music-structural importance of events in a musical piece: for instance, the tonic chord, built on the first note of the diatonic scale, is usually placed at the end of chord sequences. A brain response termed the early right anterior negativity (ERAN) is elicited when a harmonically incongruous chord is inserted within or at t...
متن کاملA Computational Model That Generalises Schoenberg’s Guidelines for Favourable Chord Progressions
This paper presents a formal model of Schoenberg’s guidelines for convincing chord root progressions. This model has been implemented as part of a system that models a considerable part of Schoenberg’s Theory of Harmony. This system implements Schoenberg’s theory in a modular way: besides generating four-voice homophonic chord progressions, it can also be used for creating other textures that d...
متن کاملDistinct neural responses to chord violations: a multiple source analysis study.
The human brain is constantly predicting the auditory environment by representing sequential similarities and extracting temporal regularities. It has been proposed that simple auditory regularities are extracted at lower stations of the auditory cortex and more complex ones at other brain regions, such as the prefrontal cortex. Deviations from auditory regularities elicit a family of early neg...
متن کاملPsychological and Physiological Influences in Chord Progression Including the Prohibitions
Harmony is one of three major elements in the music. Harmonics are the basic theory of composition. There are several kinds of prohibitions in relation to the chord progression in the rules of Harmonics. When composers compose music pieces, they pay attention not to contain these prohibitions. The prohibitions are empiricallydefined with giving the musical expressions to melody processes by try...
متن کاملGenre classification of music by tonal harmony
We present a genre classification framework for audio music based on a symbolic classification system. Audio signals are transformed to a symbolic representation of harmony using a chord transcription algorithm, by computing Harmonic Pitch Class Profiles. Then, language models built from a groundtruth of chord progressions for each genre are used to perform classification. We show that chord pr...
متن کامل