Comparison of Frontal Alpha Asymmetry Among Schizophrenia Patients, Major Depressive Disorder, and Healthy Controls

Electroencephalography (EEG) frontal alpha asymmetry (FAA) has been observed in several psychiatric disorders. However, dominance in left or right frontal alpha activity remains inconsistent in patients with major depressive disorder (MDD), patients with schizophrenia, and healthy controls. This study compared FAA among patients with MDD, schizophrenia, and healthy control. We recruited 20 patients with MDD, 18 patients with schizophrenia, and 16 healthy individuals. The EEG alpha frequency ranged from 8.0 to 12.0 Hz. FAA was expressed as the difference between absolute power values in both the right and left electrodes in the alpha frequency range (common-log-transformed F4–F3 and F8–F7). Hamilton depression and anxiety rating scales were evaluated in patients with MDD. Positive and negative syndrome scales were evaluated in patients with schizophrenia.

measure anxiety, mood, eating, substance use, and psychotic disorders. According to DSM-4 criteria, and patients with MDD and schizophrenia were diagnosed. Clinical symptoms were evaluated by a trained psychiatrist. Hamilton Depression and Anxiety [33,34] rating scales were evaluated in patients with MDD. Positive and Negative Syndrome Scales [35] were evaluated in patients with schizophrenia. Healthy participants were recruited through public advertising in Seoul, Korea. The mean (± SD) age of all participants was 37.63 ± 11.38 years (range, 19-59 years). The present study was conducted in compliance with the principles of the Declaration of Helsinki and was approved by the Institutional Review Board of Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea (approval number KC14DDSE0479). All participants provided written informed consent. All experimental procedures followed relevant institutional guidelines and regulations.

Resting state EEG paradigm and alpha asymmetry calculation
Resting EEG was recorded with eyes open and closed for 5 min each. Eye blinking artifacts can have an undesirable effect on EEG band power, and therefore they were corrected using established mathematical procedures [36,37]. Additionally, based on VEO, positive and negative components exceeding 300 μV from before and after a maximum peak of blinking interval (-100 ms to 300 ms) in the frontal regions were considered covariant. Data were re-analyzed using Matlab 2016 software (Mathworks, Inc, Natick, MA, USA) including a fast Fourier transform with a 1-50 Hz bandpass lter to calculate the absolute power in delta (1 Hz to 4 Hz), theta (4 Hz to 8 Hz), alpha (8 Hz to 12 Hz), beta (12 Hz to 30 Hz), and gamma (30 Hz to 50 Hz) bands . The power values were displayed as averaged points in the frequency range. Artifacts exceeding ±100 μV were rejected at all electrode sites. For each participant, 30 randomized artifact-free epochs (epoch length 2.048 s) were used in the analysis. The F4 and F3 electrodes covered the middle-frontal scalp region, while the F8 and F7 electrodes covered the lateral-frontal scalp areas, both of which are associated with frontal alpha asymmetry for depressive disorder (Figure 1-a) [11]. Additionally, four electrodes pairs were also included in sub-analysis: FP2-FP1, AF4-AF3, F6-F5, and F2-F1. Delta band frequency was considered as ensuring the effect of residual ocular artifact on the present results (Supplementary Table 1). To normalize the FAA data, a common log transformation was applied to the power values of selected electrodes [38]. FAA has been de ned as hemispheric differences [39], which were calculated as the difference between selected electrodes, right frontal alpha power, and left frontal alpha power [40][41][42][43][44]. More negative value of FAA indicates a relatively higher alpha activity in left frontal brain as low metabolic brain activations of left-side. To calculate power spectrum (PS) in a speci c frequency range, the fast Fourier transformation analysis was performed to estimate the discrete Fourier transformation [45].

Statistical analysis
Demographic statistics with age and sex between participant groups were tested using analysis of variance (ANOVA) or chi-squared tests. A comparison of alpha asymmetry was performed using multivariate analysis of covariance. Within-subject factors included alpha asymmetry values (log-transformed rightside electrode-left-side electrode at frontal lobe) with eyes open and closed. The groups constituted the between-subject factors. Age and sex were considered as covariates. Partial correlations between alpha asymmetry and clinical symptoms were analyzed to account age and sex. Bootstrapping tests were performed in the correlation analysis, and the sampling number was 10,000, which has been accepted in previous studies [46][47][48]. Alpha asymmetry between men and women was compared and analyzed using ANOVA. The p-values were corrected using the Bonferroni method, which is applied to multiple comparisons of several experimental conditions and variables [49,50].
The mean age of the patients with MDD and schizophrenia, and healthy controls was 42.60 ± 11.48, 32.00 ± 10.45, and 37.75 ± 9.78 years, respectively.
Descriptive characteristics of study participants are summarized in Table 1. The group difference in age was signi cant between patients with MDD and those with schizophrenia (f = 4.68, p = 0.014). Individual demographic data and clinical symptom scores of each participant were presented in Table 2. In delta band frequency with eyes-open condition, none of residual ocular artifact was con rmed through no signi cant differences of delta power between participant groups (Supplementary Table 1). Alpha asymmetry in the schizophrenia group was lower than that in the healthy controls (-0.10 ± 0.04 vs. -0.05 ± 0.05, corrected p = 0.027, 95% CI = 0.01 to 0.10) (Figure 1-b and Table 3). There were no signi cant differences in F4-F3 with the eyes-open condition between patients with MDD and healthy controls (corrected p = 0.630, 95% CI = -0.02 to 0.07), or between MDD and schizophrenia patients (corrected p = 0.434, 95% CI = -0.02 to 0.08). Furthermore, there were no signi cant differences in F4-F3 with eyes-closed (f [2,49]

Discussion
The present study quantitatively compared electroencephalographic FAA among MDD patients, schizophrenia patients, and healthy controls. Our results indicated that patients with schizophrenia exhibited a lower alpha asymmetry than healthy participants, and this difference was signi cant when alpha asymmetry recordings were conducted under eyes-open conditions. Our ndings concerning FAA in patients with schizophrenia are supported by a previous study, which showed that patients with schizophrenia had reduced alpha asymmetry of functional connectivity than healthy controls [51]. A lower alpha activity which a low brain activation at left frontal region could be implicated that malfunctions in the positive emotional or behavioral approach system of left frontal brain are dominant in patients with schizophrenia. On the other hand, deeply carved approaches with negative emotion or behavior corresponding to right frontal activation could be a representative pathological attribute of schizophrenia.
Although the design of the present study focused on the identi cation of between-subjects effects, none of signi cant results was found between MDD patients and healthy controls, or between MDD patients and schizophrenia patients. This lack of signi cance might be attributed to the small sample size, which make it di cult to generalize the results. Potential limitations of our small sample size were revealed by statistical analysis and data processing as well as a lack of information such as duration of illness and pharmacological history. Thus, these should be taken into consideration when interpreting the present ndings. There were no associations between FAA and clinical symptoms, and it should be also interpreted carefully. Withdrawal motivation in patients with depression and schizophrenia is closely related to relative increases in right frontal brain activation or relative decreases in right alpha activity [30,52]. However, the present study showed an absence of measurement in withdrawal and avoidance behavior that should be taken into consideration. The balance of interhemispheric activity may play a role in maintaining mental health across the neurodevelopment of schizophrenia [53], and our study ndings partially support this hypothesis. Schizophrenic patients have been shown to exhibit more breaking of rhythmic activity as part of left alpha dominance, compared to healthy participants. Previous studies have also reported that patients with schizophrenia exhibit hyper-activation at high-frequency alpha network in the left frontal area during working memory tasks [54]. Additionally, the present study concerning alpha asymmetry has implications for high stability representing alpha asymmetry recorded when the patient's eyes were open that was a more useful predictor of disease speci city than data gathered under eyes-closed conditions [55], although eyes-open condition includes blinking noise which should be carefully handled in preprocessing with artifact removal. Furthermore, the present study showed a signi cant effect during eyes-open conditions. In the present nding, variation of FAA scores with eyes-open was larger than those with eyes-closed as well as eyes-closed alpha activity leading to reduced baseline levels of brain activity compared to eyes-open activity [56]. Alpha asymmetry in the mid-frontal area is commonly observed in patients with psychiatric disorders [21,30]. Metabolic and structural alterations in the mid-frontal region are thought to be dominant in patients with schizophrenia [57]. In addition, low-alpha band asymmetry (8 Hz to 10 Hz) was associated with cognitive de cits in patients with MDD and positively correlated with suicidal behavior in the left-side dominant group [58]. Exploring the effect of asymmetric alpha sub-band power on several psychiatric disorders would be helpful to understand brain hemispheric activity completely. Future studies should conduct the association between cognitive de cits and alpha sub-band power asymmetry in patients with schizophrenia.
None of differences were found between patients with MDD and healthy individuals. It has been suggested that FAA does not work as a biomarker to differentiate patients with MDD and patients with non-MDD or healthy controls [59]. Some of ndings showed that FAA could be more speci c for treatment response of medication [59,60]. Furthermore, FAA was involved in the risky trait such as a suicidal behavior or ideation in patients with MDD [58,61]. These studies hereby concluded that FAA might be a prognostic biomarker to assess neurophysiological progressions in patients with MDD, but not to differentiate patients with MDD and healthy individuals.
The present study had several limitations: we lacked patient information regarding medication, the age at onset of the disorder, handedness, behavioral assessment, and level of (formal) education. All these factors could have affected FAA and, therefore, could have in uenced our results. In addition, our sample size was insu cient to generalize our ndings. This study had an absence of consistent assessment in clinical symptoms and withdrawal/avoidance behavior. Future studies should use clinical scales that consistently evaluate withdrawal/avoidance in all participant groups. Although we suspect that a cross-sectional study may replicate some of our clinical ndings, a longitudinal study that investigates alpha asymmetry in a larger cohort would help to verify and expand upon our ndings.

Conclusion
FAA may be a useful neurophysiological biomarker to distinguish between patients with schizophrenia and healthy individuals. Although our ndings may have been underpowered due to the small sample size, our present ndings suggest that neurobiological abnormalities in FAA are remarkably presented in a left lateralized alpha activity of the patients with schizophrenia.