To further demonstrate whether these emotion-specific EEG characteristics, i.e., alpha asymmetry or activity in other frequency bands, are strong enough to differentiate between various emotional states, some studies have utilized a pattern classification analysis approach, and the resulting recognition accuracy has generally been above chance –. For example, Sammler and colleagues proposed that pleasant (as opposed to unpleasant) emotion is associated with an increase in frontal midline theta power. In addition to alpha band activity, theta band power at the frontal midline (Fm) has also been found to relate to emotional states. For example, Ekman and Davidson (1993) found that voluntary facial expressions of smiles of enjoyment produced higher left frontal activation, whereas another study found decreased left frontal activity during the voluntary facial expressions of fear. Therefore, the current study aimed to elucidate whether emotional specificity can indeed be better characterized through EEG-based functional connectivity, using the evaluation criterion of whether the latter serves as a better predictor for recognizing different emotional states.Įarlier EEG-based studies of emotional specificity, with analyses at the single-electrode level, have demonstrated that asymmetric activity at the frontal site (especially in the alpha (8–12 Hz) band) is associated with emotion. In agreement with this view, we believe that analyzing emotional specificity at the level of EEG-based functional connectivity in the brain is a more ecologically valid approach. Contrary to this trend of single-electrode-level analysis, Mauss and Robinson (2009), in their recent review paper, have indicated that “emotional state is likely to involve circuits rather than any brain region considered in isolation”, neuroimaging methods that examine interrelated activity among multiple brain sites may hold more promise for understanding whether and how emotional specificity is instantiated in the brain.
![eeg results eeg results](https://kidshealth.org/content/dam/patientinstructions/es/images/EEG-400x356-rd1-esIL.gif)
Researchers have supported this viewpoint using electroencephalographic (EEG) or other neuroimaging (e.g., functional Magnetic Resonance Imaging, fMRI) approaches to investigate the specificity of brain activity associated with different emotional states However, most of the available studies on emotion-specific EEG response have focused on EEG characteristics at the single-electrode level, rather than at the level of EEG-based functional connectivity. Although some evidence for autonomic (i.e., peripheral physiological response) specificity has been reported –, many other studies have indicated that the physiological correlates of emotions are likely to be found in the central nervous system (CNS) rather than simply in peripheral physiological responses –. The question of whether different emotional states are associated with specific patterns of physiological response has long captivated emotion research –.