# Music with Concurrent Saliences of Musical Features Elicits Stronger Brain Responses
## 2 Data and Methods
### Processing and Analyzing Data  
Feature extraction was performed by using MIRtoolbox (version 1.7) [31]. MIRtoolbox is a set of MATLAB tools that extract various musical aspects in relation to sound engineering, psychoacoustics, and music theory. MIRtoolbox is designed to process audio files and can process a number of time and frequency features in audio. Brightness, RMS, zero-crossing rate, and spectral flux were the short-term low-level features chosen in this experiment. They were collected in a window of 25 ms with 50% overlap, which is common in Music Information Retrieval (MIR) [32]. The audio signal was sampled at 44,100 Hz, so every frame was 2205 samples long: \(\mathbf{X}=[x_{1},x_{2},\dots,x_{n}]\), with \(n=2205\). With the exception of the RMS, these features coincided with the ones discovered to provoke auditory activation in the temporal cortices in the experiment by [PERSON] et al. [16]. The description of the features is given in the following:  
* Brightness: Brightness is defined as the spectral energy above a certain frequency with respect to the total energy for each analysis window [31]. It can be measured as follows: \[B=\frac{\sum_{i=k}^{N}|X_{i}|^{2}}{\sum_{i=1}^{N}|X_{i}|^{2}}\] (1) where \(N\) is the number of samples of the discrete Fourier transform (DFT) of \(\mathbf{X}\): \(X=[X_{1},X_{2},\dots,X_{N}]\), the signal in the analysis window, and \(k\) stands for the smallest frequency bin corresponding to a frequency larger than the cutoff frequency defined to measure brightness; this frequency was set to 1500 Hz in MIRtoolbox. Low values of brightness mean that a small percentage of the spectral energy is in the higher frequency range of the frequency spectrum, and vice versa. * Root mean square (RMS): This feature is connected to a song's dynamics or loudness. It is defined as the square root of the average of the squared amplitude samples: \[RMS=\sqrt{\frac{\sum_{i=1}^{n}x_{i}^{2}}{n}}\] (2) Lower sounds have lower RMS values [31]. * Zero-crossing rate: This rate is defined by the number of times the audio waveform crosses the zero level per unit of time [33]. It is an accepted indicator of noisiness: A lower zero-crossing rate indicates less noise in the considered audio frame [31]. It can be measured as follows: \[ZCR=\frac{1}{2n-1}\sum_{i=2}^{n}\lvert sign(x_{i})-sign(x_{i-1})\rvert\] (3) with \(sign(x_{*})=1\) for positive amplitudes and \(-1\) otherwise. * Spectral flux: This feature comes from the Euclidean norm of the difference between the amplitude of consecutive spectral distributions [34]: \[SF=||\ |X|-|Y|\ ||\] (4) where \(X\) and \(Y\) stand for the DFT of two consecutive audio frames: the current one, \(\mathbf{X}\), and the previous window, \(\mathbf{Y}\), respectively. \(||\cdot||\) represents the Euclidean norm. The spectral flux value is high in the event of great variation in spectral distribution in two consecutive frames. The curves of spectral flux show peaks at the transition between successive chords or notes [31]. Now, recall that we are considering continuous music listening, so, in our research, the duration of low-level feature values before their swift growth is consistent with the inter-stimulus interval (ISI) of prior studies; there are no recurrent silent intervals in real music. In this paper, we call the ISI-like period the preceding low-feature phase (PLFP). We consider EEG signals linked to concurrent musical properties that are changing and, most specially, doing so concurrently. It is assumed that prolonged ISI enhances the early sensory ERP responses and that extended PLFP will lead to higher ERP amplitudes when listening to continuous music. Thus, we define triggers for instants when some properties rise after long preceding low-feature phases (PLFPs) [24; 25]. Thus, instants with a quick rise of a musical property are located. Specifically, we test different lengths of the PLFPs--from 200 to 1000 msand we set the speed of the growth of the feature to be higher than the magnitude of rapid increase (MoRI) [25], which we set to 75 ms.