# Deep Learning for EEG-Based Preference Classification in Neuromarketing
## 2 Background
### Eeg  
The EEG is a widely used tool that examines the brain activity. The electrical activity is recorded on the scalp by evaluating the voltage variations from neurons firing in the brain. These electrical activities are logged over a period of time using several electrodes positioned on the scalp directly above the cortex. The electrodes are connected in a hat-like device [5; 7]. The EEG has the following key benefits: it is non-invasive, portable, cost effective, and relatively simple to use, and it has an exceptional temporal resolution (up to milliseconds). However, the signal-to-noise ratio and spatial resolution are restricted compared with those of other techniques. Nevertheless, EEG is considered to be the only practical, non-invasive BCI input to realize a repetitive, real-time brain interactive analysis [5; 6; 7]. Therefore, EEG was selected as the input brain signal for the BCI in this research. The brain produces abundant neural activity, which can be captured as EEG signals for the BCI. These neural activities consist of two types: (1) rhythms; and (2) transient activities. The EEG activity can be further categorized on the basis of these types of activities [6; 7]. 1. **Rhythms**:  
Rhythms, neural oscillations, or brainwaves are repetitive forms of neural activity. The rhythms are measures of collective synaptic, neuronal, and axonal activities of the neuronal sets. The EEG activity is characterized by separating the frequencies into bands, denoted as delta, theta, alpha, beta, gamma, and mu rhythms. Table 1 presents the details of the EEG rhythms, ranges of frequency, amplitude, and shape, as well as the brain regions in which these activities are the most common along with the events usually associated with the type of band [6; 7]. These frequency bands have been linked to affective reactions. The theta band in the front-center of the brain reflects the emotional processing when a consumer looks at a product. The alpha band on the prefrontal cortex differentiates between the positive and negative emotional valences. The beta band is correlated with the alterations during affective arousal. Finally, the gamma band is largely associated with the arousal effects [15]. Figure 1: The international 10-20 system. 2. **Transient activities** The transient activities or field potentials replicate the action potentials of certain neurons in a manner similar to spikes. These spikes can be recognized by their position, frequency, amplitude, shape, recurrence, and operational properties. The event-related potentials (ERPs) and event-related spectral perturbations (ERSPs) are common types of transient activities [3; 16]. ERP is the most common spike and arises as a reaction to a specific event or stimulus. These spikes have extremely small amplitudes. Consequently, the EEG samples must be averaged over many iterations to uncover the ERPs and eliminate noise fluctuations [16]. Table 2 presents the common ERPs used in the neuromarketing research. ERSPs compute the reaction to a stimulus over a period of time and are similar to the ERPs. However, the ERSPs split the EEG signals into the diverse frequency bands to test whether a variation exists in the power of a specified frequency band over time [3]. \begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Rhythms** & **Frequency (Hz)** & **Amplitude (\(\mu\)V)** & **Brain Region** & **State of Mind** \\ \hline \(\delta\) (Delta) & \(<4\) & \(50-100\) & Central region & Deep sleep \\ \hline \(\theta\) (Theta) & \(4-8\) & \(<\)100 & Central region & Drowsiness, first step of sleep \\ \hline \(\mu\) (Mu) & Approximately 10 & \(<50\) & Somatosensory cortex & Movement \\ \hline \(\alpha\) (Alpha) & \(8-13\) & \(<10\) & Posterior brain & Opening the and focusing attention \\ \hline \(\beta\) (Beta) & \(13-22\) & \(<20\) & Central region & High state of wakefulness, alert and focused \\ \hline \(\gamma\) (Gamma) & \(22-30\) & \(<2\) & Highly localized & Higher mental activity, including perception and consciousness \\ \hline \hline \end{tabular}
\end{table}