Alterations of Resting EEG in Hallucinating and Nonhallucinating Schizophrenia Patients

Abstract

Auditory hallucinations (AHs) are a common symptom of schizophrenia and contribute significantly to disease burden. Research on schizophrenia and AHs is limited and fails to adequately address the effect of AHs on resting EEG in patients with schizophrenia. This study assessed changes in frequency bands (delta, theta, alpha, beta) of resting EEG taken from hallucinating patients (n = 12), nonhallucinating patients (n = 11), and healthy controls (n = 12). Delta and theta activity were unaffected by AHs but differed between patients with schizophrenia and healthy controls. Alpha activity was affected by AHs: nonhallucinators had more alpha activity than hallucinators and healthy controls. Additionally, beta activity was inversely related to trait measures of AHs. These findings contribute to the literature of resting eyes closed EEG recordings of schizophrenia and AHs, and indicate the role of delta, theta, alpha, and beta as markers for schizophrenia and auditory hallucinations.

Resting-State EEG and MEG Correlates of Auditory Hallucinations in Adults With Schizophrenia: A Systematic Review

“…Although, Van Lutterveld, Hillebrand, et al (2012) found experiencing AH was associated with reduced theta-band power (in the right hippocampus), Ishii et al (2000) found that experiences of AH were associated with increased theta-band activity. Other studies have failed to find alterations of theta power to be associated with AH, finding such changes to relate to schizophrenia per se instead (Arora et al, 2021). There is hence a need for a clearer picture of the role (if any) of theta-band changes in relation to AH.…”

“…In terms of alpha-band power, the work of Arora et al (2021) has provided evidence of lower alpha activity in frontal areas bilaterally being associated with both trait and state AH. Similarly, Van Lutterveld, Hillebrand, et al (2012) found state experiences of AH were associated with a decrease in alpha-band power (specifically in the right inferior frontal gyrus).…”

“…In terms of beta activity, two studies found decreased beta-band activity to be associated with trait AH (Arora et al, 2021;Lee et al, 2006). Decreased beta-band activity was also associated with more severe AVH (Arora et al, 2021) and experience of AH (Van Lutterveld, Hillebrand, et al, 2012).…”

Accurate neural network classification model for schizophrenia disease based on electroencephalogram data

“…Finally, the parameters checked to measure performance are: {R}{e}{c}{a}{l}{l} \left({\%}\right)=\frac{{T}{P}}{{T}{P}+{F}{N}} {x} 100 (6) {S}{p}{e}{c}{i}{f}{i}{c}{i}{t}{y} \left({\%}\right)=\frac{{T}{N}}{{T}{N}+{F}{P}} {x} 100 (7) {P}{r}{e}{c}{i}{s}{i}{o}{n} \left({\%}\right)=\frac{{T}{P}}{{F}{P}+{F}{P}} {x} 100 (8) {B}{a}{l}{a}{n}{c}{e}{d} {a}{c}{c}{u}{r}{a}{c}{y} \left({\%}\right)=\frac{{R}{e}{c}{a}{l}{l}+{S}{p}{e}{c}{i}{f}{i}{c}{i}{t} {y}}{2} {x} 100 (9) In these equations, TP indicates the number of positive cases, TN is the true negatives, FN the false negatives and FP indicates the false positive cases. In addition, the {{F}}_{1} score and Matthew's correlation coe cient (MCC) were employed during the study.…”

“…Currently, there is no objective examinations that can con rm the disease. Nevertheless, the monitoring of neurophysiological activity through encephalograms (EEGs) provides decisive information that can lead to a possible diagnosis [8][9][10][11]. EEGs offers an effective means of evaluating brain function, remaining an essential tool in neurology, particularly in serious neurological conditions.…”