EEG coherences of the default mode network among patients comorbid with major depressive disorder and anxiety symptoms.

BACKGROUND: Higher functional connectivity within the default mode network (DMN) has been found in functional magnetic resonance imaging (fMRI) studies of major depressive disorder (MDD). We used electroencephalogram (EEG) coherence as an index of functional connectivity to examine group differences in DMN between the MDD and healthy control (HC) groups during the resting state. METHODS: MDD patients with comorbid anxiety symptoms (n = 154) and healthy controls (n = 165) completed the questionnaires of depression, anxiety, and rumination. A 19-channel EEG recording was measured under resting state for all participants. EEG coherences of the delta, theta, alpha, beta, and high beta in the anterior DMN (aDMN), posterior DMN (pDMN), aDMN-pDMN, DMN-parahippocampal gyrus (PHG), and DMN-temporal gyrus were compared between the two groups. The correlations between rumination, anxiety, and DMN coherence were examined in the MDD group. RESULTS: (1) No difference was found in the delta, theta, alpha, and beta within the DMN brain regions between the two groups; the MDD group showed higher high beta coherence within DMN brain regions than the HC group. (2) Rumination was negatively correlated with theta coherence of aDMN, and positively correlated with beta coherence of aDMN and with alpha coherence of pDMN and DMN-PHG. (3) Anxiety was positively correlated with high beta coherence of aDMN, pDMN, and DMN-PHG. CONCLUSIONS: MDD patients with comorbid anxiety symptoms exhibited hypercoherence within the DMN brain regions. Hypercoherences were related to symptoms of rumination, and anxiety may be a biomarker for MDD patients with comorbid anxiety symptoms.

Developing a Five-Minute Normative Database of Heart Rate Variability for Diagnosing Cardiac Autonomic Dysregulation for Patients with Major Depressive Disorder.

Heart rate variability (HRV) is related to cardiac vagal control and emotional regulation and an index for cardiac vagal control and cardiac autonomic activity. This study aimed to develop the Taiwan HRV normative database covering individuals aged 20 to 70 years and to assess its diagnosing validity in patients with major depressive disorder (MDD). A total of 311 healthy participants were in the HRV normative database and divided into five groups in 10-year age groups, and then the means and standard deviations of the HRV indices were calculated. We recruited 272 patients with MDD for cross-validation, compared their HRV indices with the normative database, and then converted them to Z-scores to explore the deviation of HRV in MDD patients from healthy groups. The results found a gradual decline in HRV indices with advancing age in the HC group, and females in the HC group exhibit higher cardiac vagal control and parasympathetic activity than males. Conversely, patients in the MDD group demonstrate lower HRV indices than those in the HC group, with their symptoms of depression and anxiety showing a negative correlation with HRV indices. The Taiwan HRV normative database has good psychometric characteristics of cross-validation.

The effects of swLORETA Z-score neurofeedback for patients comorbid with major depressive disorder and anxiety symptoms.

BACKGROUND: Patients with major depressive disorder (MDD) exhibit atypical brain activities in the frontal, temporal, and parietal lobes. The study aimed to investigate the effects of standardized weighted low-resolution electromagnetic tomography Z-score neurofeedback (swLZNFB) on symptoms of depression and anxiety, electroencephalography (EEG) parameters, and deep brain activities in patients with MDD. METHOD: Forty-eight patients with MDD comorbid with anxiety symptoms were assigned to the swLZNFB group and the control group. Participants completed the Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) and a 5-minute resting EEG at the pre-and post-tests. The swLZNFB group received ten sessions of one-hour treatment twice weekly. The control group received treatment as usual. The scores for BDI-II and BAI, number of EEG abnormalities, percentage of EEG abnormalities, and current source density (CSD) measured in the prefrontal cortex (PFC), anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and amygdala were compared at pre-and post-tests between the two groups. RESULTS: There were decreased scores of BDI-II and BAI, number of EEG abnormalities, and percentage of EEG abnormalities at post-test compared with pre-test in the swLZNFB group, and lower scores of BDI-II and BAI at post-test in the swLZNFB group compared with the control group. Moreover, decreased CSD of beta1 and beta3 in the PFC, ACC, PCC, and amygdala at post-test compared to pre-test in the swLZNFB group. LIMITATIONS: Not a randomized controlled trial. CONCLUSION: Ten sessions of swLZNFB reduced clinical symptoms and atypical brain activities, it serves as a potential psychological intervention for patients with MDD.

Using Machine Learning for the Risk Factors Classification of Glycemic Control in Type 2 Diabetes Mellitus.

Several risk factors are related to glycemic control in patients with type 2 diabetes mellitus (T2DM), including demographics, medical conditions, negative emotions, lipid profiles, and heart rate variability (HRV; to present cardiac autonomic activity). The interactions between these risk factors remain unclear. This study aimed to use machine learning methods of artificial intelligence to explore the relationships between various risk factors and glycemic control in T2DM patients. The study utilized a database from Lin et al. (2022) that included 647 T2DM patients. Regression tree analysis was conducted to identify the interactions among risk factors that contribute to glycated hemoglobin (HbA1c) values, and various machine learning methods were compared for their accuracy in classifying T2DM patients. The results of the regression tree analysis revealed that high depression scores may be a risk factor in one subgroup but not in others. When comparing different machine learning classification methods, the random forest algorithm emerged as the best-performing method with a small set of features. Specifically, the random forest algorithm achieved 84% accuracy, 95% area under the curve (AUC), 77% sensitivity, and 91% specificity. Using machine learning methods can provide significant value in accurately classifying patients with T2DM when considering depression as a risk factor.

EEG coherences of the fronto-limbic circuit between patients with major depressive disorder and healthy controls.

BACKGROUND: Imaging studies found that patients with major depressive disorder (MDD) showed abnormal functional connectivity in the fronto-limbic circuit, including the prefrontal cortex (PFC), anterior cingulate cortex (ACC), and limbic system (amygdala). This study used electroencephalography (EEG) coherence as an indicator of functional connectivity in the fronto-limbic circuit and examined the group differences between the MDD group and healthy controls (HC group), and the associations between EEG coherence and depressive symptoms. METHODS: 125 and 132 participants in the MDD and HC groups have measured the symptoms of depression and anxiety, and delta, theta, alpha, and beta1-beta4 EEG coherences in the fronto-limbic circuit and examined the differences between the two groups, and the associations between the EEG coherence and depressive symptoms were examined. RESULTS: Lower theta, alpha, beta1, beta3, and beta4 coherence in the fronto-limbic circuit and higher beta2 coherence between the PFC and limbic system in the MDD group than in the HC group. Negative correlations between delta, theta, beta1, beta3, and beta4 coherence and total depression, cognitive depression, and somatic depression; positive correlations between beta2 coherences in the PFC and limbic system, and total depression and cognitive depression scores in the MDD group. LIMITATIONS: Whether low EEG coherence in the fronto-limbic circuit is applicable to other subtypes of MDD requires further study. CONCLUSIONS: Low EEG coherences in the fronto-limbic circuit were related to depressive symptoms, and increased functional connectivity in the fronto-limbic circuit can be applied by neurofeedback in future studies.

The Resting State of Taiwan EEG Normative Database: Z-Scores of Patients with Major Depressive Disorder as the Cross-Validation.

This study referred to the standard of electroencephalography (EEG) collection of normative databases and collected the Taiwan normative database to examine the reliability and validation of the Taiwan EEG normative database. We included 260 healthy participants and divided them into five groups in 10-year age-group segments and calculated the EEG means, standard deviation, and z-scores. Internal consistency reliability was verified at different frequencies between the three electrode locations in the Taiwan normative database. We recruited 221 major depressive disorder (MDD) patients for cross-validation between the Taiwan and NeuroGuide normative databases. There were high internal consistency reliabilities for delta, theta, alpha, beta, and high-beta at C3, Cz, and C4 in the HC group. There were high correlations between the two z-scores of the Taiwan and NeuroGuide normative databases in the frontal, central, parietal, temporal, and occipital lobes from MDD patients. The beta z-scores in the frontal lobe and central area, and the high-beta z-scores in the frontal, central, parietal, temporal, and occipital lobes were greater than one for MDD patients; in addition, the beta and high-beta absolute value z-scores in the whole brain were greater than the ones of MDD patients. The Taiwan EEG normative database has good psychometric characteristics of internal consistency reliability and cross-validation.

Size Reduction of the Right Amygdala in Chronic Pain Patients with Emotional Stress: A Systematic Review and Meta-Analysis.

The structural impact of chronic pain on amygdala in chronic pain (CP) patients remains unclear, although major depression and anxiety are known to be associated with its increase and decrease in size, respectively. This study aimed at examining the relationship between emotional stress and amygdala size in CP patients. The effects of mediating and moderating variables were also examined. The PubMed, Embase, and Web of Science databases were searched for English clinical trials from inception to February 2022 using the appropriate keyword strings. We compared the differences in amygdala size assessed with magnetic resonance imaging between CP patients with emotional stress and healthy counterparts. Of the 49 full-text articles identified, 13 studies enrolling 1,551 participants including 738 CP patients with emotional stress and 813 controls were analyzed. Emotional stress evaluated with questionnaires based on Beck depression inventory, Hamilton depression/anxiety scale, state-trait anxiety inventory, and hospital anxiety and depression scale revealed significant differences between CP patients with emotional stress and controls, indicating a subclinical but significant level of emotional stress in CP patients. The results demonstrated an amygdala shrinkage among CP patients with emotional stress compared to the controls, especially the right side (P = .02). Besides, pain from a single body region was more likely to impact the amygdala size compared to diffuse pain (P = .02). Regression analysis revealed no significant association between continuous variables (age, gender, pain duration/intensity) and amygdala size. Our findings demonstrated that emotional stress was associated with a reduced right amygdala size in CP patients.

Four Sessions of Combining Wearable Devices and Heart Rate Variability (HRV) Biofeedback are Needed to Increase HRV Indices and Decrease Breathing Rates.

Heart rate variability biofeedback (HRVB) is a behavioral intervention that uses resonance frequency breathing to synchronize the heart rate and breathing patterns. This study aimed to explore how many sessions of wearable HRVB devices are needed to increase the HRV index and decrease breathing rates and to compare the HRVB protocol with other psychological intervention programs in HRV indices and breathing rates. Sixty-four participants were randomly assigned to either the HRVB or relaxation training (RT) group. Both groups received interbeat intervals (IBIs) and breathing rates measurement at the pre-training baseline, during training, and post-training baseline from weeks 1 to 4. IBIs were transformed into HRV indices as the index of the autonomic nervous system. The Group × Week interaction effects significantly in HRV indices and breathing rates. The between-group comparison found a significant increase in HRV indices and decreased breathing rates in the HRVB group than in the RT group at week 4. The within-session comparison in the HRVB group revealed significantly increased HRV indices and decreased breathing rates at weeks 3 and 4 than at weeks 1 and 2. There was a significant increase in HRV indices and a decrease in breathing rates at mid- and post-training than pre-training in the HRVB group. Therefore, 4 weeks of HRVB combined with a wearable device are needed in increasing HRV indices and decrease breathing rates compared to the relaxation training. Three weeks of HRVB training are the minimum requirement for increasing HRV indices and reducing breathing rates compared to the first week of HRVB.

Affective Computing Based on Morphological Features of Photoplethysmography for Patients with Hypertension.

Negative and positive emotions are the risk and protective factors for the cause and prognosis of hypertension. This study aimed to use five photoplethysmography (PPG) waveform indices and affective computing (AC) to discriminate the emotional states in patients with hypertension. Forty-three patients with essential hypertension were measured for blood pressure and PPG signals under baseline and four emotional conditions (neutral, anger, happiness, and sadness), and the PPG signals were transformed into the mean standard deviation of five PPG waveform indices. A support vector machine was used as a classifier. The performance of the classifier was verified by using resubstitution and six-fold cross-validation (CV) methods. Feature selectors, including full search and genetic algorithm (GA), were used to select effective feature combinations. Traditional statistical analyses only differentiated between the emotional states and baseline, whereas AC achieved 100% accuracy in distinguishing between the emotional states and baseline by using the resubstitution method. AC showed high accuracy rates when used with 10 waveform features in distinguishing the records into two, three, and four classes by applying a six-fold CV. The GA feature selector further boosted the accuracy to 78.97%, 74.22%, and 67.35% in two-, three-, and four-class differentiation, respectively. The proposed AC achieved high accuracy in categorizing PPG records into distinct emotional states with features extracted from only five waveform indices. The results demonstrated the effectiveness of the five indices and the proposed AC in patients with hypertension.

Association of depression and parasympathetic activation with glycemic control in type 2 diabetes mellitus.

AIM: Patients with type 2 diabetes mellitus exhibited autonomic nervous system (ANS) dysfunction and comorbidities with depressive or anxiety symptoms were related to poor glycemic control. Heart rate variability (HRV) converted from electrocardiogram (ECG) has been used as the ANS index. The study aimed to explore the associations between depression, anxiety, HRV, and glycemic control in patients with type 2 diabetes mellitus. METHODS: The Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) questionnaires were used to assess depressive and anxiety symptoms in 647 patients with type 2 diabetes mellitus (mean age was 63 ± 10 years, 56 % males). The ECG raw signals were collected from a 5-min sitting and resting baseline and then transformed to HRV indices referring ANS activation. Blood glucose and lipid profiles including glycated hemoglobin (HbA1c), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglyceride were obtained from the electronic medical records. RESULTS: Ninety-nine (15 %) participants had depressive symptoms and 59 (9 %) had anxiety symptoms. Depression and HbA1c were negatively correlated with parasympathetic activation. Depression and anxiety were positively correlated with sympathetic activation. After controlling for demographic data and lipid profiles, depression was a significant positive predictor for HbA1c levels; and HRV indices (lnLF and lnHF) were the significant negative predictors for HbA1c levels. Mediation effect analysis showed that depression was a mediator between parasympathetic activation and glycemic control. CONCLUSIONS: Lower parasympathetic activation and higher depressive symptoms may affect glycemic control in patients with type 2 diabetes mellitus. Intervention programs targeting to increase parasympathetic activities and reducing depression could be further tested for their effects on glycemic outcomes for potential clinical use.

Anxiety Is a Mediator between Heart Rate Variability and Quality of Life in Chronic Obstructive Pulmonary Disease.

Autonomic nervous system (ANS) dysregulation is an important pathophysiological mechanism in patients with chronic obstructive pulmonary disease (COPD). Heart rate variability (HRV) is a common index for ANS, and HRV has been used to explore the association between ANS and clinical illnesses. This study aimed to explore the group differences in HRV, depression, anxiety, and quality of life between participants with COPD and healthy controls (HC group), and whether emotion plays a mediating role between HRV and quality of life in participants with COPD. A total of ninety-six participants with COPD and 59 participants in the HC group completed the Beck Depression Inventory-II (BDI-II), Beck Anxiety Inventory (BAI), and Saint George's Respiratory Questionnaire (SGRQ). Assessment of spirometry pulmonary function and five minute lead II electrocardiography (ECG) were also performed under the resting baseline. The COPD group had higher depression scores (F = 4.10, p = 0.008), and a lower quality of life (F = 14.44, p < 0.001) and HRV indices (such as standard deviation of RR intervals (F = 5.49, p < 0.05) and low frequency (F = 3.03, p < 0.05)) compared to the HC group. Sympathetic activation was positively correlated with depression (r = 0.312, p < 0.01), anxiety (r = 0.420, p < 0.001), and poor quality of life (r = 0.467, p < 0.001) in the COPD group. After controlling for age and sex, anxiety (ß = 0.585, p < 0.001) and sympathetic activation (ß = 0.231, p < 0.05) positively predicted poor quality of life, and lung function (ß = −0.251, p < 0.01) negatively predicted poor quality of life. Therefore, anxiety is a mediator between sympathetic activation and quality of life. Emotional and HRV screening should be applied to COPD patients in clinical practice, and emotional management or HRV biofeedback training can be used to improve anxiety and HRV for future studies.

Cardiac Autonomic and Cardiac Vagal Control During and After Depressive and Happiness Autobiographical Memories in Patients With Major Depressive Disorder.

Background: Heart rate variability (HRV) and respiratory sinus arrhythmia (RSA) are indices of cardiac autonomic and cardiac vagal control (CVC), both of which are markers of emotional regulation and physical health. This study examined (1) the differences in cardiac autonomic regulation and CVC during baseline, depressive, and happiness autobiographical memory tasks between participants with major depressive disorder (MDD group) and healthy controls (HC group); (2) the associations between depressive symptoms and cardiac autonomic and CVC; and (3) the reactivity and recovery of cardiac autonomic and CVC between the MDD and HC groups. Methods: A total of 168 and 178 participants were included in the MDD and HC groups, respectively. Demographic data and the Beck Depression Inventory-II were collected before the experimental procedure. Lead II electrocardiograph (ECG) was measured during baseline, depressive, and happiness autobiographical memory tasks, and then interbeat intervals from ECG were converted to the time and frequency domains of HRV and RSA. Results: The participants in the MDD group showed lower HRV (including standard deviation of normal to normal intervals, low frequency, the natural logarithm of low frequency, and the natural logarithm of high frequency) and CVC (RSA and lnRSA) than those in the HC group. Depressive symptoms were positively correlated with heart rate and negatively correlated with the indices of cardiac autonomic and CVC. There was significantly increased reactivity and recovery of cardiac autonomic and CVC during and after depressive and happiness autobiographical memory tasks in the HC group, but not in the MDD group. Discussion: Participants with MDD had cardiac autonomic and CVC dysregulation, decreased reactivity, and did not recover to baseline after emotional provocations. These results can be the theoretical basis for clinical intervention by using HRV biofeedback to restore cardiac autonomic regulation and CVC during and after emotional events in the future.

The Effects of Heart Rate Variability (HRV) Biofeedback on HRV Reactivity and Recovery During and After Anger Recall Task for Patients with Coronary Artery Disease.

Patients with coronary artery disease (CAD) often experience anger events before cardiovascular events. Anger is a psychological risk factor and causes underlying psychophysiological mechanisms to lose balance of the autonomic nervous system (ANS). The heart rate variability (HRV) was the common index for ANS regulation. It has been confirmed that heart rate variability biofeedback (HRV-BF) restored ANS balance in patients with CAD during the resting state. However, the effects of HRV-BF during and after the anger event remain unknown. This study aimed to examine the effects of HRV-BF on ANS reactivity and recovery during the anger recall task in patients with CAD. This study was a randomized control trial with a wait-list control group design, with forty patients in the HRV-BF group (for six sessions) and 44 patients in the control group. All patients received five stages of an anger recall task, including baseline, neutral recall task, neutral recovery, anger recall task, and anger recovery. HRV reactivity in the HRV-BF group at the post-test was lower than that in the control group. HRV recovery at the post-test in the HRV-BF group was higher than that in the control group. The HRV-BF reduced ANS reactivity during anger events and increased ANS recovery after anger events for CAD patients. The possible mechanisms of HRV-BF may increase total HRV, ANS regulation, and baroreflex activation at anger events for patients with CAD, and may be a suitable program for cardiac rehabilitation.

Prefrontal Lobe and Posterior Cingulate Cortex Activations in Patients with Major Depressive Disorder by Using Standardized Weighted Low-Resolution Electromagnetic Tomography.

BACKGROUND: The differences in brain activity between patients with major depressive disorder (MDD) and healthy adults have been confirmed by functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and electroencephalography (EEG). The prefrontal lobe and posterior cingulate cortex (PCC) are related to emotional regulation in patients with MDD. However, the high cost and poor time resolution of fMRI and PET limit their clinical application. Recently, researchers have used high time resolution of standardized weighted low-resolution electromagnetic tomography (swLORETA) to investigate deep brain activity. This study aimed to convert raw EEG signals into swLORETA images and explore deep brain activity in patients with MDD and healthy adults. METHODS: BrainMaster EEG equipment with a 19-channel EEG cap was used to collect resting EEG data with eyes closed for 5 min. NeuroGuide software was used to remove the EEG artifacts, and the swLORETA software was used to analyze 12,700 voxels of current source density (CSD) for 139 patients with MDD and co-morbid anxiety symptoms (mean age = 43.08, SD = 13.76; 28.78% were male) and 134 healthy adults (mean age = 40.60, SD = 13.52; 34.33% were male). Deep brain activity in the frontal lobe and PCC at different frequency bands was analyzed, including delta (1-4 Hz), theta (5-7 Hz), alpha (8-11 Hz), beta (12-24 Hz), beta1 (12-14 Hz), beta2 (15-17 Hz), beta3 (18-24 Hz), and high beta (25-29 Hz). RESULTS: There was lower delta and theta and higher beta, beta1, beta2, beta3, and high-beta activity at the prefrontal lobe (dorsal medial prefrontal cortex [dmPFC], ventral medial prefrontal cortex [vmPFC], and dorsal lateral prefrontal cortex [dlPFC], ventral lateral prefrontal cortex [vlPFC], orbital frontal cortex [OFC]) and PCC in MDD patients compared with healthy adults. There was no significant difference in alpha activity between the two groups. CONCLUSION: This study indicates brain hyperactivity in the right prefrontal lobe (dlPFC and vmPFC) and PCC in patients with MDD with co-morbid anxiety symptoms, and the dlPFC and PCC were also related to emotion regulation in MDD. Inhibiting high-beta activity or restoring delta and theta activity to the normal range in the right frontal lobe and PCC may be possible in z-score neurofeedback protocols for patients with MDD in future studies.

Electroencephalogram patterns in patients comorbid with major depressive disorder and anxiety symptoms: Proposing a hypothesis based on hypercortical arousal and not frontal or parietal alpha asymmetry.

BACKGROUND: Major depressive disorder (MDD) is often comorbid with anxiety disorders or symptoms. Brain hyperactivity, frontal alpha asymmetry (FAA), and parietal alpha asymmetry (PAA) have been considered as trait markers in patients with MDD. This study investigated the electroencephalogram (EEG) patterns among patients with MDD comorbid with anxiety symptoms. METHODS: One hundred and thirty-five patients with MDD comorbid with anxiety (MDD group) and 135 healthy controls (HC group) were analyzed. The Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) were completed, and 19 EEG channels were measured during the resting state, depressive recall and recovery tasks, and happiness recall and recovery tasks. FAA and PAA were computed by log (F4 alpha)-log (F3 alpha) and log (P4 alpha)-log (P3 alpha). RESULTS: The FAA and PAA indices between the two groups showed no significant differences; however, compared with the HC group, the MDD group had lower total delta and theta values, and higher total beta, low beta, and high beta values in the resting state. The total beta value positively correlated with the BDI-II and BAI scores in the MDD group. LIMITATIONS: Most patients had anxious MDD and taking prescriptions, antidepressants or benzodiazepine may affect EEG patterns. CONCLUSION: Compared with HCs, patients with MDD comorbid with anxiety had a higher beta activity in the entire brain region, supporting the role of brain hyperactivity, instead of FAA or PAA, as a trait marker in these patients. A neurofeedback protocol could be developed in future based on the brain hyperactivity findings.

A Single Session of Heart Rate Variability Biofeedback Produced Greater Increases in Heart Rate Variability Than Autogenic Training.

Heart rate variability biofeedback (HRV-BF) has been confirmed to increase heart rate variability (HRV) and cardiac outflows by baroreflex in healthy populations and clinical patients. Autogenic training (AT) is common used in the psychological intervention. This study integrates a single-session of HRV-BF and AT into a high-technology mobile application (app), and examines the effects on HRV indices, breathing rates, and subjective relaxation scores. Healthy college students were recruited and assigned to the single-session HRV-BF group or AT group. Participants in the HRV-BF group received HRV-BF combined with paced breathing training, which gradually stepped down their breathing rates from 12, to 8, to 6 breaths/per min; and received feedback of HRV indices from the app. Participants in the AT group received autogenic training and feedback of heart rate from the app. A chest belt Zephyr BioHarness was connected through Bluetooth to a Zenfone5 mobile phone, it collected the signals of interbeat intervals and breathing rates at pre-training, mid-training, and post-training stages. The Kubios HRV software was used to analyze HRV indices. The results reveal higher HRV indices and lower breathing rates during mid-training and post-training in the HRV-BF group compared to the AT group. There were higher high-frequency of HRV at post-training than pre-training in the AT group. Participants of both groups increased their subjective relaxation scores after training. The HRV-BF protocol increased cardiac outflows by baroreflex and decreased breathing rates, and the AT protocol increased high-frequency of HRV. These high-technology wearable devices combined with psychological interventions will apply to various populations in the future.

The learning effects and curves during high beta down-training neurofeedback for patients with major depressive disorder.

BACKGROUND: Electroencephalography (EEG) has revealed increased beta activity in patients with comorbid major depressive disorder (MDD) and anxiety symptoms. Negative emotions and high beta activity could be decreased by a high beta down-training neurofeedback (NFB) protocol. The present study utilized three objective parameters - trainability, independence, and interpretability - to validate the effects of high beta down-training sessions. METHODS: EEG data were collected from 23 patients with comorbid MDD and anxiety symptoms during high beta down-training sessions. Participants received five weeks of training, two sessions per week, to down-train high beta amplitude (20-32 Hz) at EEG sites P3 and P4. Three efficacy parameters were examined by comparing pre-training and post-training EEG. RESULTS: The trainability index revealed the learning curves of reduced high beta activity at P3 and P4, confirming training effects across and within sessions. The independence index revealed only beta band activity decreased. The interpretability index revealed the decreased high beta activity was positively correlated with decreased severity of depression, especially for cognitive depression. LIMITATIONS: With only ten sessions in this study, it is unknown whether the NFB training caused extended and stable learning effects. Additionally, combining high beta down-training protocol with enhancing another target band could better ensure the desired changes in brain activity. Finally, the effect of medication on EEG cannot be excluded in present study. CONCLUSIONS: The trainability, independence and interpretability of the high beta down-training NFB protocol were confirmed, supporting the protocol's use in future research and clinical applications.

The effects of alpha asymmetry and high-beta down-training neurofeedback for patients with the major depressive disorder and anxiety symptoms.

BACKGROUND: Alpha-asymmetry neurofeedback (ALAY) was applied to patients with major depressive disorder (MDD) based on the theory of frontal alpha asymmetry. Neurophysiological studies have found a higher high-beta activity of electroencephalography (EEG) at the posterior cortex among patients with comorbid MDD and anxiety symptoms. The present study examined the effects of ALAY and high-beta down-training (Beta) neurofeedback in symptoms of depression and anxiety and EEG parameters. METHOD: Eighty-seven patients with comorbid MDD and anxiety symptoms were allocated to the ALAY, Beta, or control groups. Both neurofeedback groups received ten-session neurofeedback. All participants completed the Beck Depression Inventory II (BDI-II), Beck Anxiety Inventory (BAI), and five minutes resting EEG recording at pre-test and post-test. EEG raw signals were transformed into an A1 score [log (F4 alpha) - log (F3 alpha)], P3 and P4 high-beta power. RESULTS: BDI-II and BAI scores decreased at post-test in both ALAY and Beta groups, but no significant difference between the two groups. No significant interaction effect in A1 score at pre-test and post-test between the ALAY, Beta, and control groups. The P3 high-beta was significantly decreased in the Beta group, an increase in the control group, and no change in the ALAY group at post-test compared to the pre-test. CONCLUSIONS: Both neurofeedback groups decreased symptoms of depression and anxiety. The Beta group was more effective in decreasing high-beta power at the parietal cortex compared to other groups. This non-invasive psychological intervention can be used in the future for patients with comorbid MDD and anxiety symptoms.

Erratum: Title Correction.

Clin Psychopharmacol Neurosci 2019;17(2):222-232.

Heart Rate Variability Biofeedback Increased Autonomic Activation and Improved Symptoms of Depression and Insomnia among Patients with Major Depression Disorder.

OBJECTIVE: Autonomic imbalance is considered a psychopathological mechanism underlying major depressive disorder (MDD). Heart rate variability (HRV) is an index for autonomic activation. Poor sleep quality is common among patients with MDD. HRV biofeedback (BF) has been used for regulating autonomic balance among patients with physical illness and mental disorders. The purpose of present study was to examine the effects of HRV-BF on depressive symptoms, sleep quality, pre-sleep arousal, and HRV indices, in patients with MDD and insomnia. METHODS: In this case-controlled study, patients with MDD and Pittsburgh Sleep Quality Index (PSQI) score higher than 6 were recruited. The HRV-BF group received weekly 60-minute protocol for 6 weeks, and the control group who have matched the age and sex received medical care only. All participants were assessed on Beck Depression Inventory-II, Back Anxiety Inventory, PSQI, and Pre-Sleep Arousal Scale. Breathing rates and electrocardiography were also performed under resting state at pre-testing, and post-testing conditions and for the HRV-BF group, also at 1-month follow-up. RESULTS: In the HRV-BF group, symptoms of depression and anxiety, sleep quality, and pre-sleep arousal were significantly improved, and increased HRV indices, compared with the control group. Moreover, in the HRV-BF group, significantly improved symptoms of depression and anxiety, decreased breathing rates, and increased HRV indices were detected at post-testing and at 1-month follow-up, compared with pre-testing values. CONCLUSION: This study confirmed that HRV-BF is a useful psychosocial intervention for improving autonomic balance, baroreflex, and symptoms of depression and insomnia in MDD patients.