Xixi Zhao

Background: Major Depressive Disorder (MDD) is a prevalent and disabling psychiatric disorder. Its clinical heterogeneity undermines diagnostic precision and treatment effectiveness. While DSM-5 defines melancholic and anxious subtypes based on symptoms, their neurophysiological bases remain unclear. Resting-state electroencephalography (EEG) provides a non-invasive approach for investigating neurophysiological heterogeneity in depression. Beta-band oscillations are associated with reward processing, motivation, and cortical arousal, which may differ across subtypes. Methods: We analyzed 325 patients with MDD, classified into melancholic ( n = 108), anxious ( n = 102), and non-melancholic and non-anxious ( n = 115) groups. Relative spectral power and phase-locking value (PLV) in beta1 (12–20 Hz) and beta2 (20–30 Hz) bands were compared. Logistic regression and subtype-specific correlation analyses assessed classification and clinical associations. Results: Melancholic depression was associated with widespread reductions in beta2 power and higher suicide risk, whereas anxious depression showed altered beta-band functional connectivity, particularly involving left temporal-region connections. Both subtypes shared reduced prefrontal–temporal connectivity. Exploratory classification analyses showed modest discriminative performance after leakage-controlled cross-validation. Associations between beta1 activity and symptom severity were observed only in the anxious subtype. Conclusions: Melancholic and anxious depression showed partially distinct beta-band EEG patterns. These findings provide preliminary evidence that beta-band EEG features may capture subtype-related neurophysiological heterogeneity in MDD, with subtype-specific associations between neural activity and symptom severity. Further validation is required before these features can be considered clinically applicable. Trial registration: The trial was registered at the Chinese Clinical Trial Registry on 04/23/2022 ( www.chictr.org.cn ChiCTRID ChiCTR2200059053).

Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset neurobiological disorder that often persists into adulthood. Adult ADHD is an important public health concern due to its great social damage and challenges in clinical recognition, resulting in a significant disease burden. Nonetheless, the diagnosis of adult ADHD remains challenging due to the absence of specific symptoms and biological markers. The aims of this systematic review were as follows: (1) To discern whether there were any differences in resting-state electroencephalogram (EEG) and event related potential (ERP) between adult ADHD and healthy controls (HCs). (2) To ascertain whether ERP specific manifestations associated with executive function (EF) deficiencies. (3) To conduct an exploration into the mechanisms of specific electrophysiologic alterations. This review was conducted in PubMed-Medline and Web-of-Science from 1971 to August 15th, 2024 to summarize the EEG changes of adult ADHD. We focused on resting-state EEG to report spectral power across different frequency bands and ERPs under different experimental tasks, 68 studies were finally included. When studying the characteristics of resting-state EEG in adult ADHD patients, we observed that theta power exhibits a consistent upward trend. Congruous reduction Pe, P3, and N2 amplitudes during response inhibition tasks, with a further decrease in P3 and N2 amplitudes in sustained attention tasks. These EEG changes may stem from impairments in error detection, cognitive control, and attention allocation, meaning that core EFs are affected in adults with ADHD. Overall, consistent changes in resting-state EEG and ERPs could provide insight for the identification of ADHD in adults.

Schizophrenia (ScZ) is characterized by prominent perceptual abnormalities. A deeper understanding of the neural mechanisms underlying these abnormalities is crucial for developing precise treatment strategies. Our study aimed to address the following primary questions. First, the functional role of various sub-oscillations within the alpha band remains unclear. Second, we aimed to identify biomarkers for the diagnostic purposes of ScZ. Third, the broader question of whether the diagnostic biomarker can also function as a treatment biomarker remains unknown. Resting-state EEG data from 55 ScZ patients and 61 healthy controls were analyzed to compare different sub-oscillations in the alpha band and their correlation with clinical symptoms (as measured by the general psychopathology scale). We discovered that distinct topographic patterns in low (~8 Hz) and high (~12 Hz) alpha may serve specific diagnostic and evaluative purposes respectively. Moreover, a pronounced gender bias was also observed. Low-alpha-band activity appeared to have more diagnostic relevance in females. On the other hand, the high-alpha difference was more relevant for evaluating the severity of symptoms in ScZ males. Our research has brought new insights into the neural oscillation mechanism of schizophrenia, which could substantially assist the formulating diagnosis of ScZ and the development of its treatment strategies.

Background: The pursuit of sleep quality has become an important aspect of people’s global quest for overall health. However, the objective neurobiological features corresponding to subjective perceptions of sleep quality remain poorly understood. Although previous studies have investigated the relationship between electroencephalogram (EEG) and sleep, the lack of longitudinal follow-up studies raises doubts about the reproducibility of their findings. Objective: Currently, there is a gap in research regarding the stable associations between EEG data and sleep quality assessed through multiple data collection sessions, which could help identify potential neurobiological targets related to sleep quality. Methods: In this study, we used a portable EEG device to collect resting-state prefrontal cortex EEG data over a 3-month follow-up period from 42 participants (27 in the first month, 25 in the second month, and 40 in the third month). Each month, participants’ sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) to estimate their recent sleep quality. Results: We found that there is a significant and consistent positive correlation between low α band activity in the prefrontal cortex and PSQI scores (r=0.45, P<.001). More importantly, this correlation remained consistent across all 3-month follow-up recordings (P<.05), regardless of whether we considered the same cohort or expanded the sample size. Furthermore, we discovered that the periodic component of the low α band primarily contributed to this significant association with PSQI. Conclusions: These findings represent the first identification of a stable and reliable neurobiological target related to sleep quality through multiple follow-up sessions. Our results provide a solid foundation for future applications of portable EEG devices in monitoring sleep quality and screening for sleep disorders in a broad population.

BACKGROUND The pursuit of sleep quality has become an important aspect of people’s global quest for overall health. However, the objective neurobiological features corresponding to subjective perceptions of sleep quality remain poorly understood. Although previous studies have investigated the relationship between electroencephalogram (EEG) and sleep, the lack of longitudinal follow-up studies raises doubts about the reproducibility of their findings. OBJECTIVE Currently, there is a gap in research regarding the stable associations between EEG data and sleep quality assessed through multiple data collection sessions, which could help identify potential neurobiological targets related to sleep quality. METHODS In this study, we used a portable EEG device to collect resting-state prefrontal cortex EEG data over a 3-month follow-up period from 42 participants (27 in the first month, 25 in the second month, and 40 in the third month). Each month, participants’ sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) to estimate their recent sleep quality. RESULTS We found that there is a significant and consistent positive correlation between low α band activity in the prefrontal cortex and PSQI scores (r=0.45, P<.001). More importantly, this correlation remained consistent across all 3-month follow-up recordings (P<.05), regardless of whether we considered the same cohort or expanded the sample size. Furthermore, we discovered that the periodic component of the low α band primarily contributed to this significant association with PSQI. CONCLUSIONS These findings represent the first identification of a stable and reliable neurobiological target related to sleep quality through multiple follow-up sessions. Our results provide a solid foundation for future applications of portable EEG devices in monitoring sleep quality and screening for sleep disorders in a broad population.

Bipolar disorder (BD) is a severe psychiatric disease with high rates of misdiagnosis and underdiagnosis, resulting in a significant disease burden on both individuals and society. Abnormal neural oscillations have garnered significant attention as potential neurobiological markers of BD. However, untangling the mechanisms that subserve these baseline alternations requires measurement of their electrophysiological underpinnings. This systematic review investigates consistent abnormal resting-state EEG power of BD and conducted an initial exploration into how methodological approaches might impact the study outcomes. This review was conducted in Pubmed-Medline and Web-of-Science in March 2024 to summarize the oscillation changes in resting-state EEG (rsEEG) of BD. We focusing on rsEEG to report spectral power in different frequency bands. We identified 10 studies, in which neural oscillations was compared with healthy individuals (HCs). We found that BD patients had abnormal oscillations in delta, theta, beta, and gamma bands, predominantly characterized by increased power, indicating potential widespread neural dysfunction, involving multiple neural networks and cognitive processes. However, the outcomes regarding alpha oscillation in BD were more heterogeneous, which is thought to be potentially influenced by the disease severity and the diversity of samples. Furthermore, we conducted an initial exploration into how demographic and methodological elements might impact the study outcomes, underlining the importance of implementing standardized data collection methods. Key aspects we took into account included gender, age, medication usage, medical history, the method of frequency band segmentation, and situation of eye open/eye close during the recordings. Therefore, in the face of abnormal multiple oscillations in BD, we need to adopt a comprehensive research approach, consider the multidimensional attributes of the disease and the heterogeneity of samples, and pay attention to the standardized experimental design to improve the reliability and reproducibility of the research results.