# Evaluation of Emotions from Brain Signals on 3D VAD Space via Artificial Intelligence Techniques
## 1 Introduction  
Emotions emerge in our brains due to interactions caused by neural and hormonal systems [1]. If we look at emotions and their interactions in the brain in detail with examples, the brain controls emotions. The limbic system is important for emotion. The amygdala has a significant role, especially in influencing anger and aggression. Fear can appear due to the stimulated amygdala, i.e., with frightening memory flashbacks. The amygdala can enhance emotional stimuli perception. The septum influences anger and fear [2]. A phobia is an anxiety disorder occurring with extreme fear of the stimuli, such as a fear of heights (acrophobia), spiders (arachnoidphobia), crowds, etc. Physical and emotional symptoms appear with a phobia crisis, such as increased heart rate and breathing, sweating, and difficulty controlling emotions [3]. Besides its other vital functions, the hypothalamus is also crucial in consciousness control, regulating emotions, and responses to stress, as well as pleasure and pain [2]. Emotions affect perception, memory, creativity, behavior, etc. [1]. Perceiving and expressing emotions are abilities related to emotional intelligence. Problem-solving abilities can be positively affected by emotions. Autism also causes somedifficulties in language and emotion. The internal context also affects memory retrieval of emotions, moods, consciousness, etc. [2]. Brain waves are separated into five bands: delta, theta, alpha, beta, and gamma. During a relaxed state, alpha waves dominate the cerebral cortex, gradually disappearing as emotional activity strengthens. During stressed conditions, alpha wave frequency increases and amplitude decreases, and alpha waves gradually turn to beta waves. Beta wave occurrence indicates an excited state in the cerebral cortex [4]. [PERSON] et al. [5] have used the fMRI-EEG system to implement a modified stop-signal task in a virtual battlefield scenario to study the neural mechanism of response inhibition under reward and punishment, which can modulate motivation and emotions and affect cognitive processing. According to their results, positive and negative monetary feedback made a difference for both behavioral indices of inhibition and brain activities. Emotion analysis determines, compares, and evaluates emerging emotions, activating changes using various methods. Recently, emotion analysis has become increasingly attractive, and many intelligent applications for emotion recognition have been presented [6]. Artificial intelligence techniques allow computer programs to gain abilities, such as learning, solving problems, making decisions, etc. [7], and these intelligence techniques can also be used for emotion recognition despite some difficulties and limitations due to some factors, such as hiding feelings [8]. Even though emotions can be recognized by facial expressions, voice, or gesture recognition [6; 9; 10], these methods can be manipulated, preventing actual emotional states from being understood easily and clearly [9; 10]. Because inner systems are affected less by human subjective consciousness, physiological signals can reflect emotions more truly [6]. EEG physiological brain signals remain neutral in this context and help to accurately analyze emotional states with more reliable data [9; 10]. Visual, auditory, both visual and auditory, or memory-based stimuli can be used to obtain emotions. If we look at some definitions and some studies within the scope of mood analysis, two models (discrete and dimensional) are used in emotion prediction. The discrete model has six emotions, which are anger, fear, happiness, hatted, sadness, and surprise [11]. The dimensional emotion model includes 2D and 3D models. The 2D VA model has valence and arousal dimensions. The 3D VAD model has valence, arousal, and dominance dimensions [12]. The valence dimension ranges from negative emotions, such as unpleasant/unhappy/sad, to positive emotions, such as pleasant/happy/joyful. The arousal dimension ranges from calm/bored to stimulated/excited.