## 1 Introduction  
Measuring brain responses to music provides important insights into the auditory, non-verbal brain functions of functional hearing and hearing disabilities. The brain response is measured by identifying each time point in the music that evokes the brain response. Typically, the experimenter uses a set of predefined time points and designs artificial music stimuli adapted to the time points. However, this approach limits the opportunities for measuring brain responses to realistic music and restricts the generalization of the findings to ecological listening conditions. Since the artificially designed music differs from real music heard outside the laboratory, there is a growing interest in developing music information retrieval (MIR) methods [1; 2] to identify the time points for measuring brain responses to real music [3; 4; 5; 6; 7]. We have tested a new method, which combines acoustical MIR analysis with modeling of brain mechanisms to automatically extract time points when the brain responds to real music pieces [8].  
Brain responses to acoustical changes in music measured with neurophysiological methods, such as electroencephalography (EEG) and magnetoencephalography (MEG), originate from synchronous post-synaptic electric potentials in coherently oriented groups of pyramidal neurons in the cortical layers of the brain [9]. These are measured with EEG electrodes placed on the scalp, while the magnetic counterpart of the potentials is measured with MEG sensors positioned around the head. While basic brain responses originating from the auditory cortex in reaction to acoustical changes in music can be measured, novel events in music also evoke novelty-related brain responses originating from higher-order cortical structures such as the inferior frontal cortex [10; 11; 12; 13; 14].  
A relevant source of novel events in music is the change of level in acoustical feature parameters. With respect to loudness, the metal subgenre of rock music is in particular attempting to maximize perceived loudness [15]. This is achieved by applying loud bass drums, distortion and brightness increase filters on the bass and guitar, as well as dynamic range compression [15]. The perceived loudness can be further increased by habituating the listener to low levels of loudness and brightness, while subsequently increasing the level for these parameters (e.g., see Figure 1, top). A novelty-related brain response is typically evoked after briefly learning to expect a certain parametric level in acoustical features followed by a change in the acoustical parameter [16]. In addition, the novelty-related brain response can be evoked by novel events, which are infrequent in relation to the listener's prior developed understanding of which events are frequent and infrequent in the music style before hearing the current music piece [13; 14; 17; 18; 19; 20; 21; 22; 23]. To measure such novelty-related brain responses, it would be relevant to analyze the novelty of the musical events.  
In the present study, we investigate whether automatic extraction of acoustical feature increases, based on MIR analysis, can be applied to isolate brain responses to real pieces of different musical genres, such as metal rock music, tango music and modern symphony orchestra music. We also consider whether it is relevant to include an analysis of the novelty in the musical structure to extract brain responses to novel events in the music.