On the analysis of EEG power, frequency and asymmetry in Parkinson’s disease during emotion processing

Abstract

ObjectiveWhile Parkinson’s disease (PD) has traditionally been described as a movement disorder, there is growing evidence of disruption in emotion information processing associated with the disease. The aim of this study was to investigate whether there are specific electroencephalographic (EEG) characteristics that discriminate PD patients and normal controls during emotion information processing.MethodEEG recordings from 14 scalp sites were collected from 20 PD patients and 30 age-matched normal controls. Multimodal (audio-visual) stimuli were presented to evoke specific targeted emotional states such as happiness, sadness, fear, anger, surprise and disgust. Absolute and relative power, frequency and asymmetry measures derived from spectrally analyzed EEGs were subjected to repeated ANOVA measures for group comparisons as well as to discriminate function analysis to examine their utility as classification indices. In addition, subjective ratings were obtained for the used emotional stimuli.ResultsBehaviorally, PD patients showed no impairments in emotion recognition as measured by subjective ratings. Compared with normal controls, PD patients evidenced smaller overall relative delta, theta, alpha and beta power, and at bilateral anterior regions smaller absolute theta, alpha, and beta power and higher mean total spectrum frequency across different emotional states. Inter-hemispheric theta, alpha, and beta power asymmetry index differences were noted, with controls exhibiting greater right than left hemisphere activation. Whereas intra-hemispheric alpha power asymmetry reduction was exhibited in patients bilaterally at all regions. Discriminant analysis correctly classified 95.0% of the patients and controls during emotional stimuli.ConclusionThese distributed spectral powers in different frequency bands might provide meaningful information about emotional processing in PD patients.

The neural correlates of two forms of spiritual love: an EEG study

“…It is notable that an increase in alpha 1 power was observed at electrodes T8 and P8 for the both the LKM and prayer versus baseline activity. In addition to the correlation between right temporal and parietal activity with anxiety as mentioned above (Mathersul et al, 2008), an increase in alpha power over the right parietal lobe has also been observed during responses to both positive and negative emotional cues, including happy, sad, afraid, angry, surprised and disgust emotional responses (Yuvaraj et al, 2014), consistent with the notion that activity in this region is associated with emotion processing and arousal, rather than the valence of emotion experienced (Heller, 1993).…”

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

“…However, only certain types of emotions can be recognized using EEG. Moreover, finding key emotional states to be recognized is mandatory; for example, six emotions were detected in [42,45,106,120,122,192], whereas in [108], a real-time EEG signal to classify happy and unhappy emotions was proposed, and in [113], a fear evaluation system was proposed. In our review, we found that most of the articles aim to detect unpleasant, pleasant, and neutral emotions, such as in [105,217], or positive, negative, and neutral emotions that are based on the valence-arousal dimensional emotion model, as in [159,206].…”

“…Research findings on the reason for this are inconclusive. Nine articles discussed the idea of using EEG-based emotion detection to provide assistance, monitoring, assessment, and diagnosis of Parkinson's disease in patients [47,106,107,114,[118][119][120][121][122].…”

Electroencephalogram Profiles for Emotion Identification over the Brain Regions Using Spectral, Entropy and Temporal Biomarkers

“…Thus, these waveforms can be classified into five specific frequency power bands: the delta band (δ), the theta band (θ), the alpha band (α), the beta band (β), and the gamma band (γ) [40,41]. Studies on EEG signal processing have been conducted to identify the brain activity patterns involved in cognitive science, neuropsychological research, clinical assessments, and consciousness research [42][43][44][45][46][47]. Recently, EEG has been widely used to assess and evaluate the human emotional states with excellent time resolution [3,15,[28][29][30]48].…”